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- Business Model Innovation
Product and service innovation are essential, but business model innovation can deliver more lasting competitive advantage, particularly in disruptive times. BCG helps leaders leverage innovative business models to tackle their most pressing challenges and capture their greatest opportunities.
In the past 50 years, the average business model lifespan has fallen from about 15 years to less than five. As a result, business model innovation is now an essential capability for organizations seeking to drive breakout growth, reinvigorate a lagging core, or defend against industry disruption or decline.
What Is Business Model Innovation?
Business model innovation is the art of enhancing advantage and value creation by making simultaneous—and mutually supportive—changes both to an organization’s value proposition to customers and to its underlying operating model. At the value proposition level, these changes can address the choice of target segment, product or service offering, and revenue model. At the operating model level, the focus is on how to drive profitability, competitive advantage, and value creation through these decisions on how to deliver the value proposition:
- Where to play along the value chain
- What cost model is needed to ensure attractive returns
- What organizational structure and capabilities are essential to success
Business model innovation is also critical to business transformation . Many organizations share a common set of concerns: What type of business model innovation will help us achieve breakout performance? How do we avoid jeopardizing the core business? How do we build the capability to develop, rapidly test, and scale new models? Inspiring an organization to change is not a trivial undertaking, but given the current strategic environment, it’s a critical one.
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Our Approach to Business Model Innovation
Companies hoping to drive growth through business model innovation face a number of critical questions: How broad should the scope of the effort be? What’s the appropriate level of risk to take? Is it a onetime exercise, or does it call for an ongoing capability?
To answer those questions, it’s important to realize that not all business model innovation efforts are alike. Understanding the four distinct approaches to business model innovation can help executives make effective choices in designing the path to growth:
1. The reinventor approach is deployed in light of a fundamental industry challenge, such as commoditization or new regulation, in which a business model is deteriorating slowly and growth prospects are uncertain. In this situation, the company must reinvent its customer-value proposition and realign its operations to profitably deliver on the new superior offering.
2. The adapter approach is used when the current core business, even if reinvented, is unlikely to combat fundamental disruption. Adapters explore adjacent businesses or markets, in some cases exiting their core business entirely. Adapters must build an innovation engine to persistently drive experimentation to find a successful “new core” space with the right business model.
3. The maverick approach deploys business model innovation to scale up a potentially more successful core business. Mavericks—which can be either startups or insurgent established companies—employ their core advantage to revolutionize their industry and set new standards. This requires an ability to continually evolve the competitive edge or advantage of the business to drive growth.
4. The adventurer approach aggressively expands the footprint of a business by exploring or venturing into new or adjacent territories. This approach requires an understanding of the company’s competitive advantage and placing careful bets on novel applications of that advantage in order to succeed in new markets.
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BCG helped a Southeast Asian bank develop a new business model that delivered superior results at 50% of the cost of the traditional model.
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Four Paths to Business Model Innovation
- Karan Girotra
- Serguei Netessine
The secret to success lies in who makes what decisions when and why.
Drawing on the idea that any business model is essentially a set of key decisions that collectively determine how a business earns its revenue, incurs its costs, and manages its risks, the authors view innovations to the model as changes to those decisions: What mix of products or services should you offer? When should you make your key decisions? Who are your best decision makers? and Why do key decision makers choose as they do? In this article they present a framework to help managers take business model innovation to the level of a reliable and improvable discipline. Companies can use the framework to make their innovation processes more systematic and open so that business model reinvention becomes a continual, inclusive process rather than a series of isolated, internally focused events.
Idea in Brief
Business model innovation is typically an ad hoc process, lacking any framework for exploring opportunities. As a result, many companies miss out on inexpensive ways to radically improve their profitability and productivity.
Drawing on the idea that a business model reflects a set of decisions, the authors frame innovation in terms of deciding what products or services to offer, when to make decisions, who should make them, and why the decision makers choose as they do.
Traditional call centers hire a staff to supply services as needed from a place of work, incurring significant up-front costs and risks. LiveOps created a new model by revising the order of decisions: It employs agents as calls come in by routing the calls to home-based freelancers who have signaled their availability.
Business model innovation is a wonderful thing. At its simplest, it demands neither new technologies nor the creation of brand-new markets: It’s about delivering existing products that are produced by existing technologies to existing markets. And because it often involves changes invisible to the outside world, it can bring advantages that are hard to copy.
The challenge is defining what business model innovation actually entails. Without a framework for identifying opportunities, it is hard to be systematic about the process, which explains why it is generally done on an ad hoc basis. As a result, many companies miss out on inexpensive ways to improve their profitability and productivity.
In the following pages we present a framework to help managers take business model innovation to the level of a reliable and improvable discipline. Drawing on the idea that any business model is essentially a set of key decisions that collectively determine how a business earns its revenue, incurs its costs, and manages its risks, we view innovations to the model as changes to those decisions: what your offerings will be, when decisions are made, who makes them, and why. Successful changes along these dimensions improve the company’s combination of revenue, costs, and risks.
What Mix of Products or Services Should You Offer?
Uncertain demand is a challenge all businesses face and is in most cases their major source of risk. One way to reduce that risk is to make changes to your company’s mix of products or services. In finance, if you have two portfolios offering a 20% return, you choose the less risky one, because it will create more value over time. The same is true with product portfolios.
Companies looking to recalibrate their product or service mix have essentially three options:
In October 2010 Bloomberg Businessweek ran a cover story with the sensationalist title “What Amazon Fears Most.” The article profiled Quidsi, a relatively small New Jersey–based internet start-up cofounded by Marc Lore (a former student of ours) and best known for its main venture, the online retailer Diapers.com.
Diapers would appear to be a terrible product to sell on the internet. They are bulky and expensive to ship, and they have low margins because everyone —from convenience stores to Costco—sells them. But diapers have one thing going for them: Demand is highly predictable—birthrates are stable, and infants pee and poop constantly over an extended period of time. Also, product variety is limited, because there are only three or four major diaper manufacturers, and diapers come in just a few sizes. Given that every newly acquired customer will use the product repeatedly for two years or more, the company can count on a steady revenue stream with little or no risk for a long time to come.
Focused business models are most effective when they appeal to distinct market segments with clearly differentiated needs. So if your business currently serves multiple segments, it may be best to subdivide into focused units rather than try to apply one model. Amazon, which bought both Quidsi and the online shoe and apparel retailer Zappos, allows its focused acquisitions considerable autonomy in serving their segments.
The main drawback for a focused business is that it must rely on a single product, service, or customer segment—and it may omit key customer needs. People buy both bread and butter.
Search for commonalities across products.
The success of Volkswagen owes much to a strategy whereby its cars share components. Although the strategy does not protect VW from general demand swings, it reduces demand variability for individual components, because shared components make it easy for VW to switch production at its plants from one model to another whenever the demand for car models shifts.
Commonalities aren’t just shared components among different products. They may also be the capabilities needed to serve various product, customer, and market segments. Consequently, companies can add to their mix products or services that reflect new applications of their capabilities. For instance, in the late 1990s Amazon expanded from books into music, video, and games—all of which required the same logistics capabilities that books did. This allowed the company to cover the risk of failing to acquire enough share in any one of these categories with a potentially superior share in another.
Founded in 1994 with the U.S. book market in mind, Amazon has adopted many of the strategies in our framework over the years.
Pass the decision risk to the party that can best manage the consequences:
Cash-strapped, the company gets distributors and publishers to carry slow-moving inventory, rather than stocking the books itself.
Integrate the incentives:
Partners can’t keep up with Amazon’s growth and quick shipping promise, so the company reverses course and builds its own warehouses.
Search for commonalities across products:
Success with books leads to expansion into music, video, and games—where the company’s logistics competencies can be applied.
Amazon hosts the websites of Toys“R”Us, Borders, and Target and performs most site development, order fulfillment, and customer service.
Change the revenue stream:
Per-item shipping costs deter many customers, so Amazon offers Amazon Prime: Customers buy a shipping subscription rather than paying for individual shipments. This also encourages impulse purchases.
Postpone the decision:
The acquisition of BookSurge (on-demand book publishing) and CreateSpace (self-publishing of books, CDs, DVDs, and video) allows Amazon to delay publication decisions until customer tastes are known.
Appoint a better-informed decision maker:
Amazon takes over retailers’ A-to-Z fulfillment function—a logical extension of its third-party services.
Create a hedged portfolio:
Amazon expands into computing services including storage, simple queue service (SQS), cloud computing, and electronic data systems.
Amazon realizes efficiencies by acquiring focused verticals: Diapers.com (baby consumables) and Zappos (shoes). Acquired retailers operate independently to maintain these efficiencies.
Commonality can, however, carry significant costs if components must be engineered for a wide range of makes and models. What’s more, the strategy requires that the component-sharing products not all experience their demand highs and lows simultaneously.
Create a hedged portfolio.
Just as financial institutions try to create portfolios of investments that will hedge one another’s risks, companies can select an assortment of products or markets to reduce the overall riskiness of the business model. Chile’s LAN Airlines takes such an approach: Unlike most major U.S. carriers, which derive less than 5% of their revenue from cargo, LAN uses the same wide-body planes, flying international routes, to transport both passengers and cargo.
Because almost all travel from the Americas to Europe is on overnight flights, passenger-only airlines keep their planes on the ground for long periods. LAN uses the downtime to carry cargo: A plane to Santiago that has picked up cargo in Europe can deliver it to other Chilean cities before returning to Santiago for its next overnight flight.
This approach reduces the risks associated with LAN’s capacity decisions. Airlines make such decisions infrequently—by ordering new airplanes—and they are hard to reverse, leaving the companies vulnerable to periods of over- or underutilized capacity, with harsh effects on revenue. Hedging passengers with cargo mitigates this risk because their respective demand curves rarely rise or fall in concert. Moreover, carrying cargo allows the airline to fly profitably with fewer passengers, so it can afford to serve destinations that other airlines avoid.
Clearly, the approach works mainly for product and market combinations in which demand fluctuations are negatively correlated. For example, a manufacturer of ski apparel could hedge sales in North America with sales in South America—where the seasons are opposite. Overall demand stays fairly constant.
When Should You Make Your Key Decisions?
Decisions must often be made before you have enough information to make them with confidence. We have identified three strategies that, depending on the circumstances, can improve a business model by changing the timing of decisions.
Postpone the decision.
In many industries companies make firm decisions about prices well before they actually sell anything. This, of course, often exposes them to risk. It’s risky to price airplane seats early, for instance, because demand on any given route is highly contingent on economic and other conditions and can vary by the time of day, the day of the week, or the week of the month.
American Airlines solved this problem in the 1980s by using the booking system known as SABRE (for semi-automated business research environment), which makes it relatively easy to alter prices quickly by factoring in new information. The ability to price dynamically changed the airline industry forever. On any given flight, the price that passengers have actually paid to fly—even within the same seating class—can vary tremendously. Recently Uber, a company that matches customers who need rides with vehicles for hire, borrowed the same toolbox: In high-demand periods, the company implements “surge pricing,” whereby prices for rides go up, reducing demand while increasing supply.
Price quotes can be delayed at the individual level. The casino and hospitality company Caesars Entertainment uses a sophisticated database compiled by its Total Rewards loyalty program. When a repeat customer calls to make a reservation, the agent asks for his Total Rewards number, which links to detailed information about the customer’s gambling habits (including average bet size) and hence the profit he is likely to bring the casino. Depending on what the agent sees, the customer may hear anything from “Sorry, all our rooms are booked” to “You’re in luck! We can offer you a complimentary stay in our Presidential Suite!”
Change the order of your decisions.
Some companies don’t have the option of changing the time frame within which they operate, but they can shuffle the order in which decisions are made in order to delay investment commitments until pertinent information is known.
Most product development, for example, begins with proposing a solution or a technology for a customer need. If, after initial investments, the solution proves to be a dud, then it’s back to the drawing board. But an increasing number of companies, including the open-innovation pioneers InnoCentive and Hypios, have figured out that if they switch that sequence to performance first, investment after, they can shift much of the risk of R&D onto others.
These companies offer clients (“seekers”) a secure website on which to present R&D problems to a global freelance community of qualified engineers, product designers, and scientists (“solvers”). The companies help seekers define their problems—which might range from the chemical synthesis of a specific molecule to designing the look and feel of a new product—with enough specificity to interest an appropriately skilled subset of solvers. Seekers offer monetary rewards for the right solutions (sometimes more than one is selected), and solvers compete to develop the best solutions and win the rewards.
A similar change in sequence explains the success of one company in the call center industry: LiveOps. Traditional centers make up-front investments in facilities and hard infrastructure (primarily communications) before they sign a single client or take their first call. They must also decide how many agents to hire, at what levels of skill and expertise, and provide training. Next they must sign up clients whose needs match the capabilities they have assembled. Finally, they must develop daily and weekly staffing plans to ensure that enough agents with the right skills will be available to handle calls.
LiveOps, in contrast, employs agents as the calls come in. Its agents work independently from home and signal LiveOps when they are ready to take calls. They are paid according to the duration of a call and—because calls are automatically recorded and scored—their skill at meeting callers’ needs. Intelligent software routes callers to the most qualified agents available according to the nature of the call, so capacity and staffing are constantly adjusted in real time to meet actual demand.
This approach has its limits. Training on-demand employees in advance is difficult, and because they assume the risk of being idle and making no money, the business model depends on having an ample supply of people for whom downtime has a relatively low cost.
Split up the key decisions.
The lean start-up movement is taking the corporate innovation and start-up worlds by storm (see “Why the Lean Start-Up Changes Everything,” HBR May 2013). At the heart of the movement is a new approach for entrepreneurs who are making decisions about their businesses. In the past, starting a risky new venture involved putting together a detailed business plan that would cover all essential pieces of the business model and then executing on the plan. All the key decisions were made at once and up front.
The lean start-up approach divides up the key decisions. A venture starts with relatively imprecise and limited hypotheses about where an opportunity may lie. Multiple stages of information gathering and “pivoting” follow, as the business model is revised to arrive at the final, validated version. Typically, the founders radically change their hypotheses as the venture unfolds.
In the start-up world, this approach is today the rule rather than the exception. BBureau, a mobile beauty and wellness service that was born in our classroom (one of us is an investor and board member), is a case in point. Rather than commit up front to one target market and a fixed portfolio of services, BBureau ran a number of small experiments on many different markets to identify the combinations of customers and services that would be most lucrative for its pop-up delivery model, effectively splitting the venture-design decision into a number of smaller ones.
After numerous rounds of experimentation and refinement, the team converged on a business model that included offering wellness services (such as massages) at boutique hotels and frequently repeated beauty services (such as nail treatments) at office locations. Those combinations kept the company’s delivery costs low while ensuring a high customer willingness to pay.
This approach depends on finding decisions that can be divided up. In some cases the decision process is indivisible. (You can’t price a little bit now and a little bit later.) In other cases it can be divided up only at some additional cost, and risk-return calculations should be performed.
Who Are the Best Decision Makers?
Many companies find that they can radically improve decision making in the value chain simply by changing the people who make the calls. Companies can:
Appoint a better-informed decision maker.
The whole employee empowerment movement is based on giving decision rights to the most informed person or organization. Google’s engineers, for example, have extraordinary freedom to decide what development projects the company should pursue, because Google believes they are better informed about technologies and tastes than the company’s executives are.
The best-informed people aren’t always in the company. More than 25 years ago, Walmart transferred some decision rights about stocking its store shelves to Procter & Gamble, because it saw that a supplier had the right combination of information and incentives to keep Walmart well stocked with products by optimizing delivery and production schedules. This has become a standard arrangement with the company’s large suppliers.
More recently, we’ve seen decisions being made by algorithms. In the restaurant business, for example, servers are often scheduled for shifts they would rather not work and not scheduled for those they want. Worse, the least-productive servers are frequently put on the most-profitable shifts.
To get around this problem, the Boston-based restaurant chain Not Your Average Joe’s uses an analytic tool called Muse, which was developed by Objective Logistics, a start-up in Cambridge, Massachusetts (in which one of us is both an adviser and an investor). Muse tracks servers’ performance over time according to sales per customer (as measured by check size) and customer satisfaction (as measured by tips or directly). This has enabled the chain to develop a productivity-based ranking system whereby servers can schedule themselves, choosing both their shifts and the tables they serve.
Although the advantages of making decisions using better information are obvious, empowering employees, suppliers, or customers and collecting extensive data often entail costs and difficulties. Walmart made a considerable up-front investment in the largest private satellite network in the world in order to enable seamless data flow, and the company had to negotiate and coordinate complicated new relationships with trading partners.
Pass the decision risk to the party that can best manage the consequences.
The key to Amazon’s early prosperity was its drop-shipping model, which allowed it to offer more than a million books while stocking only 2,000 or so of the most popular titles. For the rest, Amazon forwarded orders to book wholesalers or publishers, who then often shipped the products directly to customers using Amazon packaging.
In this innovative model, Amazon’s network of wholesalers and publishers independently managed their inventories. They, not Amazon, bore the risk of carrying books without knowing the likely demand for them. But because the risk was widely distributed, all were able to manage their own bits of it with relative ease.
Shifting the decision risk to the party best able to bear it is often an attractive strategy when no decision maker clearly has superior information. In its early years, Amazon was too small and too cash constrained to stock every single book in its catalog, whereas bigger wholesalers were well positioned to match supply with demand from Amazon and thousands of other small retailers. But for this strategy to work, the replacement decision maker’s incentives must be aligned with yours. Amazon’s model would have failed if the publishers had been motivated to poach its customers.
Select the decision maker with the most to gain.
In many business models, key decisions are made by those with less to gain than others in the chain. A company’s customers, for example, often feel that they gain less when they buy a company’s products than the company does. That was a problem facing Netafim, the Israeli market leader in drip-irrigation technology.
Drip irrigation is the watering method of choice for small farmers in hot countries. Netafim developed a technology that fine-tunes water application according to the soil’s water content, salinity, and fertilization and to meteorological data. The company demonstrated to farmers that its system could increase crop yields by 300% to 500%, making it a potentially lucrative investment.
Initially, though, the technology was a hard sell. Small farmers were reluctant to engage with and pay for anything so sophisticated. They did not trust the company and felt that they were shouldering a lot of risk in adopting its approach. Netafim solved the problem by offering them a free integrated package that included system design and installation, all required hardware, and periodic maintenance. Payback came from a share of each farmer’s increased crop yields. Thus Netafim took on all the risks of the decision, and farmers simply said yes or no to a strong chance of earning more money with no downside.
Netafim could do this because it realized that it had the most to gain from the adoption of its technology. Given its expertise and access to sophisticated forecasting systems, the risks were a lot smaller for the company than for the individual farmers. Moreover, it could spread the risk: If the system failed at one farm, Netafim could make up for it elsewhere. As farmers achieved greater success, word would spread; Netafim would increase its sales and realize economies of scale.
Something similar is at work with energy-efficiency companies, many of which essentially take on energy management for their customers, implementing whatever efficiencies they think necessary and bearing all the up-front costs. They then share the savings that result from these improvements with the customers. Like Netafim, they bear additional risk quite easily, because they understand the technology and can predict its performance. And as resistance to adoption declines, their revenues scale up.
There are catches. A company can safely take on more risk only if the relevant technology is very reliable. And behavioral issues may arise: The savings from energy-efficient equipment will shrink if customers decide that they can economically leave their lights on longer.
Why Do Key Decision Makers Choose as They Do?
When decision makers collaborate to create value, they must also be able to pursue their private objectives without damaging the value chain. Many business model innovations, therefore, come from adjusting decision makers’ motivations. There are three ways of doing this:
Change the revenue stream.
Traditionally, when the U.S. Department of Defense bought aircraft, it would agree to a time-and-materials contract, under which suppliers charged for labor and materials consumed (on a cost-plus basis) in the course of each maintenance event—just as a mechanic does for car repairs. Unfortunately, this model doesn’t provide suppliers with customer-friendly incentives; from their point of view, the more problems the client has, the better. It has been estimated that for every dollar the government spent to buy a new airplane, it spent seven more over the plane’s life.
Until, that is, the DoD gave suppliers a reason to care about engine reliability. In 2003, facing pressure to cut costs and improve performance, the department adopted what’s called performance-based contracting, which changed the revenue model for contractors. They would be paid for the amount of time the aircraft was actually in service, with the DoD specifying, for example, 95% availability as its threshold. As a result, the longer a jet performed without needing to be taken out of service for maintenance or repair, the more the contractor earned.
When decision makers collaborate to create value, they must also be able to pursue their private objectives.
Changing the revenue stream to align the interests of a decision’s stakeholders works best when performance can be fully and unambiguously defined. It would be difficult to set reasonable performance standards and develop appropriate metrics for, say, a new airplane that relied on advanced technologies and materials, because the unknowns involved would simply be too numerous.
Synchronize the time horizons.
Traditionally, sourcing relied on competitive-bidding rituals that ensured low prices and moderate but acceptable quality. The chosen provider won the business for a relatively short period of time, after which the bidding process was repeated.
But as overseas sourcing increased, this model developed flaws. Faraway suppliers cut corners on quality control and materials reliability. Worse, revelations of abusive labor practices, product diversion, and the counterfeiting of goods emerged. And because most sourcing transactions were one-off deals, shoddy providers faced few consequences—until, of course, multinationals felt the corrosive impact of repeated performance problems on their brands.
Enter Li & Fung, a Hong Kong–based company that has changed the world of outsourcing by creating a new business model based on combining the flexibility of competitive sourcing with the confidence of long-term relationships. It selects, verifies, and approves suppliers and allocates their business among its manufacturing clients, and it manages each client’s relationship with each supplier—including performance, compliance, and crafting incentives for suppliers to invest in people, facilities, and materials. Given the potential for an enduring relationship with Li & Fung, suppliers are motivated to create long-term value for manufacturing partners.
But companies like Li & Fung are few and far between. If your organization sources in sectors or regions where you lack recourse to a trusted intermediary, you will need to manage such relationships directly, which can be difficult.
Integrate the incentives.
Companies without a trusted intermediary can develop contractual arrangements and management systems (such as the famous balanced scorecard) to focus independent agents on maximizing an agreed-upon outcome. This is essentially what one of the most promising reforms to U.S. health care is about: Under the bundled payments system, all parties involved in a patient’s treatment agree to measure performance according to the outcome for the patient (see “How to Design a Bundled Payment Around Value,” on hbr.org).
Sometimes such contractual arrangements can be so complex that it’s easier to simply integrate operations. Quad/Graphics, a printing company with approximately 25,000 employees and annual revenue of more than $4 billion, has created its own health care system, complete with doctors and hospitals, lowering health care costs for its employees by some 30% in the process. Patient outcomes have improved as well: For example, the rate of cesarean-section births among women in the Quad health care system is only 12%, compared with 26% nationally.
Achieving full integration is not trivial; many organizations rightly hesitate to take on directly performing activities that are outside their core competencies. Thus we tend to regard it as a last resort, to be applied only when other approaches won’t suffice. Using a framework like ours, any experienced manager can find ways to create a better business model. Companies can also use the framework to make their innovation processes more systematic and open, with business model reinvention becoming a continual, inclusive process rather than a series of isolated, internally focused events. When they do, they find that the resulting capabilities offer a sustainable competitive advantage.
- KG Karan Girotra is the Charles H. Dyson Family Professor of Management at Cornell Tech and the Johnson College of Business at Cornell University, and a coauthor, with Serguei Netessine, of The Risk-Driven Business Model: Four Questions That Will Define Your Company (HBR Press, 2014). Follow him on Twitter: @Girotrak
- Serguei Netessine is the vice dean for global initiatives and the Dhirubhai Ambani Professor of Innovation and Entrepreneurship at the University of Pennsylvania’s Wharton School and a coauthor, with Karan Girotra, of The Risk-Driven Business Model: Four Questions That Will Define Your Company (HBR Press, 2014). Follow him on Twitter: @snetesin
Business Model Innovation : comment innover ?
Grâce aux notions abordées dans les différentes pages, vous êtes désormais en mesure de déterminer quel sera le modèle économique de votre entreprise. Vous êtes également en mesure de lui donner corps à travers le business model canvas . Ce document, très simple à utiliser, permet de voir en un seul coup d’oeil les informations les plus importantes relatives à votre entreprise : structure des coûts, financement de l’entreprise, proposition de valeur, etc…
Toutefois, un point important demeure : celui de l’innovation. C’est l’objet de cette page, qui vous explique comment vous démarquer de la concurrence. Il n’est pas forcément nécessaire, comme vous allez le voir, de mettre sur le marché un produit ou un service complètement nouveau. L’innovation peut être obtenue par d’autres moyens.
L’innovation par le business model
Trouver une idée de projet innovant : les techniques.
- Deux exemples d’innovation par le business model
Des ressources complémentaires sur l'innovation de business model
L’innovation peut porter sur le produit / service mais elle peut également venir d’une innovation sur un ou plusieurs aspects du business model . Il s'agit de trouver un ou plusieurs éléments pour vous différencier de vos concurrents ou pour obtenir plus de clients.
De fait, de nombreuses entreprises ont fait (et gagné) ce pari, en proposant non pas de nouveaux produits ou services, mais en adaptant leur business model pour les présenter différemment, les proposer à un autre public démocratiser leur accès...
Rank Xerox en passant de la vente de photocopieurs à la vente de l’usage du photocopieur : location sur une longue durée avec un nombre minimum de photocopies incluses
Ryan air, en Europe, en inventant le vol low-cost
Ford en créant des voitures identiques, montées à la chaine
Free a créant des forfaits téléphoniques à low cost
Les journaux gratuits…
Ces entreprises ont innové sur la base d’un produit connu.
La question est bien sûr : comment faire ? Voici quelques techniques d'innovation.
L’innovation par les épicentres
Nous pouvons distinguer quatre épicentres d’innovation par les épicentres : les ressources, l’offre, les clients et les finances. Chacun des quatre épicentres peut servir de point de départ à un changement important de modèle économique . Dans certain cas, l’innovation émergera de plusieurs épicentres.
Une innovation pilotée par les ressources. Ces innovations trouvent leur source dans l’infrastructure ou les partenariats existants d’une organisation pour étendre ou transformer le Business Model.
Par exemple, les Web Services d’Amazon s’appuient sur l’infrastructure de distribution existante d’Amazon pour proposer des capacités de serveur et de l’espace de stockage de données à d’autres entreprises.
Une innovation pilotée par l’offre. Ces innovations créent de nouvelles propositions de valeur qui ont un impact sur les autres blocs du Business Model.
Une innovation pilotée par la finance. Ces innovations reposent sur de nouveaux flux de revenus, de nouveaux mécanismes de prix ou des structures de coûts plus performantes.
Par exemple : Xerox qui est passé d’un business model de vendeur de copieur à celui de location de copieur et “vendeur d’un nombre de forfaits de copies”.
Une innovation pilotée par le client. Ces innovations sont basées sur les besoins des clients / consommateurs, une meilleure accessibilité ou une plus grande commodité. Ces innovations influencent les autres blocs du canevas
Par exemple : 23andMe à mis les tests ADN à la portée du plus grand nombre, jusque-là réservés aux seuls chercheurs et professionnels de santé. Les conséquences sur la proposition de valeur ainsi que sur la délivrance des résultats a été considérable. C’est pourquoi 23andMe utilise des profils Web de personnalisation de masse.
Plusieurs innovations en même temps
L'innovation par un jeu de questions
Posez-vous (au moins), les sept questions suivantes :
Quelles facilités ou difficultés ont les clients pour partir vers la concurrence ? Il s'agit de "bloquer" votre client en mettant un coût s'il veut changer pour un autre acteur (System Lock-in). Par exemple, Apple, en interconnectant tous ses produits, rend difficile le départ vers la concurrence
Est-ce que chaque vente est un nouvel effort ou résulte-t-il d’un renouvellement automatique ? Comment sont lissés vos revenus sur l’année ? Il s'agit de trouver une solutions pour générer des revenus récurrents. Par exemple, Zara qui réassort ses magasins en nouveaux produits de façon très rapide ou les ventes par abonnements
Gagnez-vous de l’argent avant d’en dépenser ? Il s'agit de trouver une solution pour encaisser avant de payer ! Par exemple, la grande distribution qui paie ses fournisseurs après avoir vendu
Votre structure de coûts est-elle différente et meilleure que celle de vos concurrents ? Par exemple, transformer des charges fixes en charges variables en louant du matériel plutôt que de l’acheter
A quel niveau de contribution vos clients ou tierces parties participent à la création de valeur de votre business model ? Il s'agit de faire faire le travail par les autres (notamment vos clients !) Par exemple, LinkedIn qui fait son business sur les données que les utilisateurs déposent
A quelle vitesse et facilité pouvez-vous faire croître votre Business Model sans rencontrer d’obstacles sur votre route ? (ex: infrastructure, support client, etc...)
Découvrez les 55 questions à se poser pour construire et challenger son business model :
Onopia - 55 questions pour imaginer votre business model from Onopia .
L’innovation par l’expérience client
L’une des clés pour dépasser les attentes des clientes est d’offrir à vos clients une expérience inattendue à chacun des interactions avec lui. On appelle ce concept, l’expérience client . Elle est constituée par la somme des interactions entre une entreprise et ses clients.
C’est donc une combinaison de performances physiques, de stimulations sensorielles, d’émotions et d’interactions humaines, chacune confrontée de manière inconsciente par le consommateur avec ses besoins et ses attentes, et cela à chaque point de contact.
3 chiffres à ce sujet :
50% de la décision provient des émotions ressenties.
95% des gens ont décidé d’agir après avoir eu une mauvaise expérience de service client.
85% sont prêts à payer 25% de plus pour s’assurer d’avoir un service client à la hauteur.
L’expérience client cherche à dépasser la satisfaction (ai-je atteint mon but, mon problème est-il résolu ?) pour aller vers le plaisir.
Comprendre l'expérience-client en vidéo :
Vous pouvez donc vous positionner pour que son expérience avec vous soit meilleure qu’avec vos concurrents.
L'innovation par le SWOT du business model
Il s’agit de regarder chaque case du business model et d’examiner ses forces, ses faiblesses, ses opportunités et ses menaces en y intégrant une échelle.
Par exemple :
Deux exemples d'innovation par le business model
Notez bien les deux points suivants :
Les exemples ne sont pas de réelles entreprises, ils n’ont pas d’autres vocations que de mettre en application les explications théoriques.
Les données chiffrées sont des exemples destinés à faire comprendre l’exercice uniquement et ne doivent pas servir de base à vos réflexions.
Exemple 1 : des bijoux fantaisie fabriqués avec une imprimante 3D et conçus sur la base des bijoux portés par les people du moment. Vendus en commerce ambulant à Tours
Business model de base :
Les innovations possibles :
Une innovation pilotée par les ressources : voir pour faire concevoir les modèles par la foule (crowdsourcing) plutôt que par des designers professionnels. Ou, dans un premier temps, passer par des écoles de design pour avoir des stagiaires.
Innovation sur les revenus : je vais ajouter une possibilité d’abonnement mensuel ou annuel.
Mes produits étant plutôt des achats « coup de cœur », je dois travailler pour que l’expérience que vivront mes clientes soit magique pour qu’elles reviennent voire s’abonnent.
Business model ajusté :
Business model en clair :
Nous créons un commerce qui rendra accessibles les bijoux des stars à toutes les adolescentes grâce à l'innovation. A moyen terme, il s'agit d'ouvrir une chaîne de boutiques proposant des bijoux "tendance" créés via une imprimante 3D. Pour démarrer, un pilote sera lancé en commerce ambulant dans la ville de Tours avec une collection différente par mois créée en fonction des nouveautés des "people".
Les collections seront créées grâce à la communauté d'adolescentes qui se retrouvera sur le Facebook et l'Instagram de la marque et pourra donner son avis sur les collections et proposer des modèles.
Nous travaillerons avec des designers indépendants et fabriquerons à la demande dans un premier temps puis nous lancerons les abonnements permettant ainsi aux adolescentes de recevoir leurs bijoux préférés chaque mois à leur domicile.
Exemple 2 : faire du conseil en sécurisation des données informatiques pour les petites entreprises en proposant un choix de solutions techniques adaptées aux problématiques du client.
Le business model de base :
Les innovations possibles
Coûts du Changement / System Lock-in : le SAV à vie rend le client captif
Ayant besoin de la confiance et du bouche-à-oreille pour rassurer mes prospects, je vais travailler sur l’expérience client que je peux faire vivre à mes clients.
Suite à ce travail, je fais évoluer ma proposition de valeur et j’ajoute sur mon site Internet un système de diagnostic du niveau de sécurisation actuel des données de l’entreprise avec une préconisation pour la rendre plus performante.
Le business model ajusté :
Le business model en clair :
Nous lançons une solution intégrée pour simplifier et faciliter la sécurisation des données informatiques pour tous les dirigeants de TPE. Nous voulons devenir une marque de référence dans la facilitation de la sécurisation des données informatiques des TPE.
Notre offre sera facturée sur devis et s'articule autour de 3 points :
Une offre de conseil qui se compose de 4 prestations : la découverte du besoin du client, la comparaison des solutions possibles, le choix de la meilleure solution, l’implémentation dans l’entreprise de la solution.
Une offre de SAV à vie.
Un site d’information qui proposera : un auto-diagnostic du système actuel utilisé par l’entreprise, des explications théoriques sur la sécurisation des données, les risques en cas de non-sécurisation dans certaines activités particulières, des exemples..., des cas pratiques avec les coûts des solutions, une présentation détaillée de mon profil et de mon expérience, une veille sur toutes les solutions disponibles avec leurs analyses.
Pour tester l'offre, nous lançons un pilote sur un département avant de déployer sur la France entière.
Suivez le webinaire "Business model Innovation" proposé par notre partenaire Onopia.
Echec de business models : 10 exemples et 5 raisons ! from Elton-Pickford (qui est devenu Onopia )
5 business models disruptifs : dans le secteur bancaire, les opticiens, le marketing, la médecine.
Comprendre le business model du compte NICKEL , un service français de carte bancaire prépayée nominative et non nominative, alternatif du compte bancaire comme moyen de paiement, créé en 2012 par la société la Financière des paiements électroniques (FPE), avec comme cofondateurs et développeurs l’ingénieur en électronique Ryad Boulanouar et le financier Hugues le Bret.
Découvrir le business model de Number 26 . Cette startup fintech propose un compte bancaire est une carte de paiement gratuits.
Comprendre le business model de A Little Market . ALittleMarket est la première plateforme française créée par la société Incubart, qui permet aux “petits créateurs” de vendre leurs créations au plus grand nombre.
Le site s’est rapidement positionné en tant que référence sur l’artisanat – notamment avec une importante emprunte locale – avec pour principe de mettre directement en relation le vendeur et l’acheteur.
- Management de l'innovation
- Chapitre 6. Innovation de business...
- Chapitre 6. Innovation de business model
- Suivre cet auteur Marie Eyquem-Renault
- Dans Management de l'innovation (2017) , pages 203 à 241
Sur un sujet proche
Les deux premières capitalisations boursières mondiales, Apple et Alphabet (Google), ont introduit des business models nouveaux dans leurs secteurs respectifs. Apple s’appuie sur une convergence technologique et tire ses revenus de la complémentarité de ses produits avec ses places de marché, iTunes et App Store. Google a certes bâti son succès sur un algorithme mais il a surtout été capable de trouver une manière rentable de capturer de la valeur à partir d’une demande non solvable : les utilisateurs de son moteur de recherche. La facturation de publicités contextualisées a généré une rentabilité inédite et a exclu d’autres moteurs pourtant entrés plus tôt sur le marché. Il est possible de multiplier les exemples d’entreprises qui ont bouleversé des secteurs d’activité matures en introduisant des business models innovants, et ce, il y a parfois plusieurs décennies : Southwest avec le modèle low cost dans le secteur de l’aviation, Swatch dans celui de l’horlogerie ou encore Zara dans le textile et l’habillement. Les technologies numériques, qui accélèrent ce mouvement, et les préoccupations sociétales liées à la soutenabilité de modèles socioéconomiques actuels enclenchent des mutations profondes qui traversent tous les secteurs d’activité. Aussi, les entreprises remettent plus volontiers en question leur business model pour survivre. Cet impératif d’innovation est exacerbé par la menace de nouveaux entrants agiles qui renouvellent les manières de créer et de capturer de la valeur…
- Section 1. L’innovation de business model : définition et spécificités
- 1. Qu’est-ce qu’un business model ?
- 2. Les innovations de business model
- 2.1 Business model « véhicule » de l’innovation ou objet d’innovation
- 2.2 Design ou reconfiguration de business model
- 2.3 Les business models disruptifs ou de renforcement
- 3. L’innovation de business model est-elle source d’un avantage concurrentiel durable ?
- 3.1 Emprunt de la notion d’innovation architecturale et sources de l’avantage concurrentiel
- 3.2 L’avantage architectural ou la contestation du design dominant
- Section 2. Méthodes, outils et compétences nécessaires pour développer un nouveau business model
- 1. Les canevas
- 1.1 La proposition de valeur
- 1.2 L’architecture de valeur
- 1.3 Le modèle économique (ou équation de profit)
- 1.4 Business model canvas : l’outil standard qu’il faut manipuler avec méthode
- 2. Les méthodes d’utilisation du BMC pour innover
- 2.1 Les épicentres de l’innovation dans la méthode BMC
- L’innovation par l’offre
- L’innovation par le client
- L’innovation par les ressources
- L’innovation par la finance
- 2.2 Le GRP Lab, solution digitale et collaborative pour le design de nouveaux business models
- 3. Innover par la combinaison et l’adaptation de business models génériques
- 4. Le contexte d’émergence et d’adoption de l’innovation de business model et les compétences organisationnelles
- 4.1 Le business model, méthode pour tester le projet de création d’entreprise
- 4.2 L’ambidextrie, une caractéristique organisationnelle à développer pour reconfigurer le business model
- Section 3. Les nouveaux modèles de l’économie collaborative et digitale
- 1. Tentative de définition et ébauche des principes économiques clés
- 1.1 Les principaux secteurs de l’économie collaborative
- 2. Les recettes de l’économie collaborative
- 2.1 Contexte et contours du « déplacement collaboratif »
- 2.2 Changer les utilisations des attributs du droit de propriété
- 2.3 Les contreparties entre utilisateurs
- 2.4 Communauté et confiance
- 2.5 L’effet de réseau au cœur de la création de valeur
- 2.6 Les modèles de revenu et structure des coûts
- 3. Les enjeux économico-juridiques des nouveaux modèles de l’économie collaborative et digitale
- Section 4. Conclusion
- 5 • L’innovation de business model
- Dans Management de l'innovation
- Dunod, 2022
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The Hard Truth About Business Model Innovation
Many attempts at business model innovation fail. To change that, executives need to understand how business models develop through predictable stages over time — and then apply that understanding to key decisions about new business models.
- Business Models
- Developing Strategy
- Executing Strategy
- Skills & Learning
Surveying the landscape of recent attempts at business model innovation, one could be forgiven for believing that success is essentially random. For example, conventional wisdom would suggest that Google Inc., with its Midas touch for innovation, might be more likely to succeed in its business model innovation efforts than a traditional, older, industrial company like the automaker Daimler AG. But that’s not always the case. Google+, which Google launched in 2011, has failed to gain traction as a social network, while at this writing Daimler is building a promising new venture, car2go, which has become one of the world’s leading car-sharing businesses. Are those surprising outcomes simply anomalies, or could they have been predicted?
To our eyes, the landscape of failed attempts at business model innovation is crowded — and becoming more so — as management teams at established companies mount both offensive and defensive initiatives involving new business models. A venture capitalist who advises large financial services companies on strategy shared his observation about the anxiety his investors feel about the changes underway in their industry: “They look at the fintech [financial technology] startups and see their business models being unbundled and attacked at every point in the value chain.” And financial services companies are not alone. A PwC survey published in 2015 revealed that 54% of CEOs worldwide were concerned about new competitors entering their market, and an equal percentage said they had either begun to compete in nontraditional markets themselves or considered doing so. 1 For its part, the Boston Consulting Group reports that in a 2014 survey of 1,500 senior executives, 94% stated that their companies had attempted some degree of business model innovation. 2
We’ve decided to wade in at this juncture because business model innovation is too important to be left to random chance and guesswork. Executed correctly, it has the ability to make companies resilient in the face of change and to create growth unbounded by the limits of existing businesses. Further, we have seen businesses overcome other management problems that resulted in high failure rates. For example, if you bought a car in the United States in the 1970s, there was a very real possibility that you would get a “lemon.” Some cars were inexplicably afflicted by problem after problem, to the point that it was accepted that such lemons were a natural consequence of inherent randomness in manufacturing. But management expert W. Edwards Deming demonstrated that manufacturing doesn’t have to be random, and, having incorporated his insights in the 1980s, the major automotive companies have made lemons a memory of a bygone era. To our eyes, there are currently a lot of lemons being produced by the business model innovation process — but it doesn’t have to be that way.
In our experience, when the business world encounters an intractable management problem, it’s a sign that business executives and scholars are getting something wrong — that there isn’t yet a satisfactory theory for what’s causing the problem, and under what circumstances it can be overcome. This is what has resulted in so much wasted time and effort in attempts at corporate renewal. And this confusion has spawned a welter of well-meaning but ultimately misguided advice, ranging from prescriptions to innovate only close to the core business to assertions about the type of leader who is able to pull off business model transformations, or the capabilities a business requires to achieve successful business model innovation.
The hard truth about business model innovation is that it is not the attributes of the innovator that principally drive success or failure, but rather the nature of the innovation being attempted. Business models develop through predictable stages over time — and executives need to understand the priorities associated with each business model stage. Business leaders then need to evaluate whether or not a business model innovation they are considering is consistent with the current priorities of their existing business model. This analysis matters greatly, as it drives a whole host of decisions about where the new initiative should be housed, how its performance should be measured, and how the resources and processes at work in the company will either support it or extinguish it.
This truth has revealed itself to us gradually over time, but our thinking has crystallized over the past two years in an intensive study effort we have led at the Harvard Business School. As part of that research effort, we have analyzed 26 cases of both successful and failed business model innovation; in addition, we have selected a set of nine industry-leading companies whose senior leaders are currently struggling with the issue of conceiving and sustaining success in business model innovation. (See “About the Research.”) We have profiled these nine companies’ efforts extensively, documented their successes and failures, and convened their executives on campus periodically to enable them to share insights and frustrations with each other. Stepping back, we’ve made a number of observations that we hope will prove generally helpful, and we also have a sense of the work that remains to be done.
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There are a number of lessons that managers can learn from past successes and failures, but all depend on understanding the rules that govern business model formation and development — how new models are created and how they evolve across time, the kinds of changes that are possible to those models at various stages of development, and what that means for organizational renewal and growth.
The Business Model’s Journey
The confusion surrounding business model innovation begins, appropriately enough, with confusion about the term “business model.” In our course at the Harvard Business School, we teach students to use a four-box business model framework that we developed with colleagues from the consulting firm Innosight LLC. This framework consists of the value proposition for customers (which we will refer to as the “job to be done”); the organization’s resources , such as people, cash, and technology; the processes 3 that it uses to convert inputs to finished products or services; and the profit formula that dictates the margins, asset velocity, and scale required to achieve an attractive return. 4 (See “The Elements of a Business Model.”) Collectively, the organization’s resources and processes define its capabilities — how it does things — while its customer value proposition and profit formula characterize its priorities — what it does, and why. 5
This way of viewing business models is useful for two reasons. First, it supplies a common language and framework to understand the capabilities of a business. Second, it highlights the interdependencies among elements and illuminates what a business is in capable of doing. Interdependencies describe the integration required between individual elements of the business model — each component of the model must be congruent with the others. They explain why, for example, Rolls-Royce Motor Cars Ltd. is unable to sell cheap bespoke cars and why Wal-Mart Stores Inc. is unable to combine low prices with fancy stores.
Understanding the interdependencies in a business model is important because those interdependencies grow and harden across time, creating another fundamental truth that is critical for leaders to understand: Business models by their very nature are designed not to change, and they become less flexible and more resistant to change as they develop over time. Leaders of the world’s best businesses should take special note, because the better your business model performs at its assigned task, the more interdependent and less capable of change it likely is. The strengthening of these interdependencies is not an intentional act by managers; rather, it comes from the emergence of processes that arise as the natural, collective response to recurrent activities. The longer a business unit exists, the more often it will confront similar problems and the more ingrained its approaches to solving those problems will become. We often refer to these ingrained approaches as a business’s “culture.” 6
In fact, this pattern is so consistent and important that we’ve begun to think of the development of a business model across time as resembling a journey whose progress and route are predictable — although the time that it takes a business model to follow this journey will differ by industry and circumstance. (See “The Three Stages of a Business Model’s Journey.”) As the diagram depicts, a business model, which in an established company is typically embodied in a business unit, 7 travels a one-way journey, beginning with the creation of the new business unit and its business model, then shifting to sustaining and growing the business unit, and ultimately moving to wringing efficiency from it. Each stage of the journey supports a specific type of innovation, builds a particular set of interdependencies into the model, and is responsive to a particular set of performance metrics. This is the arc of the journey of virtually every business model — if it is lucky and successful enough to travel the entire length of the route. Unsuccessful business units will falter before concluding the journey and be absorbed or shuttered. Now, let’s explore each of the three stages and how the business model evolves through them.
Peter Drucker once said that the purpose of a business is to create a customer. 8 That goal characterizes the first stage of the journey, when the business searches for a meaningful value proposition, which it can design initial product and service offerings to fulfill. This is the stage at which a relatively small band of resources (a founding team armed with an idea, some funding and ambition, and sometimes a technology) is entirely focused on developing a compelling value proposition — fulfilling a significant unmet need, or “job.” 9 It’s useful to think of the members of the founding team as completely immersed in this search. The information swirling around them at this point in the journey — the information they pay the most attention to — consists of insights they are able to glean into the unfulfilled jobs of prospective customers.
We emphasize the primacy of the job at this point of the journey because it is very difficult for a business to remain focused on a customer’s job as the operation scales. Understanding the progress a customer is trying to make — and providing the experiences in purchase and use that will fulfill that job perfectly — requires patient, bottom-up inquiry. The language that is characteristic of this stage is the language of questions, not of answers. The link between value proposition and resources is already forming, but the rest of the model is still unformed: The new organization has yet to face the types of recurrent tasks that create processes, and its profit formula is nascent and exploratory. This gives the business an incredible flexibility that will disappear as it evolves along the journey and its language shifts from questions to answers.
2. Sustaining Innovation
Business units lucky and skilled enough to discover an unfulfilled job and develop a product or service that addresses it enter the sustaining innovation phase of the business model journey. At this stage, customer demand reaches the point where the greatest challenge the business faces is no longer determining whether the product fulfills a job, but rather scaling operations to meet growing demand. Whereas in the creation phase the business unit created customers, in the sustaining innovation phase it is building these customers into a reliable, loyal base and building the organization into a well-oiled machine that delivers the product or service flawlessly and repeatedly. The innovations characteristic of this phase of the business model journey are what we call sustaining innovations — in other words, better products that can be sold for higher prices to the current target market.
A curious change sets in at this stage of the journey, however: As the business unit racks up sales, the voice of the customer gets louder, drowning out to some extent the voice of the job. Why does this happen? It’s not that managers intend to lose touch with the job, but while the voice of the job is faint and requires interrogation to hear, the voice of the customer is transmitted into the business with each sale and gets louder with every additional transaction. The voice of the job emerges only in one-to-one, in-depth conversations that reveal the job’s context in a customer’s life, but listening to the voice of the customer allows the business to scale its understanding. Customers can be surveyed and polled to learn their preferences, and those preferences are then channeled into efforts to improve existing products.
The business unit is now no longer in the business of identifying new unmet needs but rather in the business of building processes — locking down the current model. The data that surrounds managers is now about revenues, products, customers, and competition. While in the creation phase, the founding team had to dig to discover data, data now floods the business’s offices, with more arriving with each new transaction. Data begs to be analyzed — it is the way the game is scored — so the influx of data precipitates the adoption of metrics to evaluate the business’s performance and direct future activity to improving the metrics. The performance metrics in this phase focus on the income statement, leading managers to direct investments toward growing the top line and maximizing the bottom line.
At some point, however, these investments in product performance no longer generate adequate additional profitability. At this point, the business unit begins to prioritize the activities of efficiency innovation, which reduce cost by eliminating labor or by redesigning products to eliminate components or replace them with cheaper alternatives. (There is, however, always some amount of both types of innovation — sustaining and efficiency — occurring at any point of a business’s evolution.) Broadly, the activities of efficiency innovation include outsourcing, adding financial leverage, optimizing processes, and consolidating industries to gain economies of scale. While many factors can cause businesses to transition into the efficiency innovation phase of their evolution, one we have often observed is the result of performance “overshoot,” in which the business delivers more performance than the market can utilize and consumers become unwilling to pay for additional performance improvement or to upgrade to improved versions. Managers should not bemoan the shift to efficiency innovation. It needs to happen; over time, business units must become more efficient to remain competitive, and the shift to efficiency innovations as the predominant form of innovation activity is a natural outcome of that process.
To managers, the efficiency innovation phase marks the point where the voice of the shareholders drowns out the voice of the customer. Gleaning new understanding of that initial job to be done is now the long-lost ambition of a bygone era, and managers become inundated with data about costs and efficiency. The business unit frequently achieves efficiency by shifting to a modular structure, standardizing the interdependencies between each of the components of its business model so that they may be outsourced to third parties. In hardening these interdependencies, the business unit reaps the efficiency rewards of modularization but leaves flexibility behind, firmly cementing the structure of its business model in place. Deviations from the existing structure undermine the modularity of the components and reduce efficiency, so when evaluating such changes, the business will often choose to forsake them in pursuit of greater efficiency.
Now, when the business unit generates increasing amounts of free cash flow from its efficiency innovations, it is likely to sideline the capital, to diversify the company, or to invest it in industry consolidation. This is one of the major drivers of merger and acquisition (M&A) activity. Whereas the sustaining innovation phase was exciting to managers, customers, and shareholders, the efficiency innovation phase reduces degrees of managerial freedom. Efficiency innovations lure managers with their promises of low risk, high returns, and quick paybacks from cost reduction, but the end result is often a race to the bottom that sees the business’s ability to serve the job and customers atrophy as it improves its service to shareholders.
The natural evolution of business units occurs all around us. Consider the case of The Boeing Co. and its wildly successful 737 business unit. The 737 business was announced in 1965 and launched its first version, the 737-100, in 1967, with Lufthansa as its first customer. With orders from several additional major airlines, the new business unit demonstrated that its medium-haul plane fulfilled an important job to be done. Before even delivering the first -100, Boeing began improving the 737 and launched a stretched version, the -200, with a longer fuselage to meet demands from airlines requiring greater seating capacity. Boeing entered the sustaining innovation phase and continued to improve its product by developing several generations of new 737s, stretching the fuselage like an accordion while nearly doubling the plane’s range and more than doubling its revenue per available seat mile. The business continued to improve how it served customers with the Next Generation series in the 1990s, which offered even bigger aircraft and better avionics systems.
Facing increased competition and demands for improved financial performance, the 737 business shifted its focus to efficiency innovation in the early 2000s. To free resources and liberate capital, Boeing began to outsource aspects of 737 production. Most notably, Boeing sold a facility in Wichita, Kansas, that manufactured the main fuselage platform for the 737 to the Toronto-based investment company Onex Corp. in 2005. Outsourcing subsystem production allowed the business to improve its capital efficiency and deliver improved returns on capital. 10
Given that road map, what is the hope for companies that seek to develop new business models or to create new businesses? Thus far in this article we’ve explored the journey that business units take over time. And while we’re not sure that a business unit can break off from this race, we know that its parent companies can — by developing new businesses. Although the processes of an individual business unit’s business model propel it along this journey, the opportunity exists to develop a process of business creation at the corporate level. But doing so successfully requires paying careful attention to the implications of the business model road map.
Implications For Business Model Innovation
It’s worth internalizing the road map view of business model evolution because it helps explain why most attempts to alter the course of existing business units fail. Unaware of the interdependencies and rigidities that constrain business units to pursuing their existing journey, managers attempt to compel existing business units to pursue new priorities or attempt to create a new business inside an existing unit. Using the road map as a guiding principle allows leaders to correctly categorize the innovation opportunities that appear before them in terms of their fit with their existing business model’s priorities. Several recommendations for managers emerge from this insight.
Determine how consistent the opportunity is with the priorities of the existing business model. The only types of innovation you can perform naturally within an existing business model are those that build on and improve the existing model and accelerate its progress along the journey — in other words, those innovations that are consistent with its current priorities — by sharpening its focus on fulfilling the existing job or improving its financial performance. Therefore, a crucial question for leaders to ask when evaluating an innovation opportunity is: To what degree does it align with the existing priorities of the business model?
Many failed business model innovations involve the pursuit of opportunities that appear to be consistent with a unit’s current business model but that in fact are likely to be rejected by the existing business or its customers. (See “Evaluating the Fit Between an Opportunity and an Existing Business.”) To determine how consistent an opportunity is with the priorities of the existing business model, leaders should ask: Is the new job to be done for the customer similar to the existing job? (The greater the similarity, the more appropriate it is for the existing business to pursue the opportunity.) How does pursuit of the opportunity affect the existing profit formula? Are the margins better, transaction sizes larger, and addressable markets bigger? If so, it is likely to fit well with the existing profit formula. If not, managers should tread with caution in asking an existing business to take it on — and should instead consider creating a separate unit to pursue the new business model.
This distinction helps explain the performance of the two innovations with which we opened this article. Google saw Google+ as an extension of its search business and chose to integrate Google+ into its existing products and business. Google+ accounts were integrated into other Google products, and the business saw the incorporation of information from users’ social networks as a way to generate improved, tailored search results. Viewed through the lens of Google’s business model, a social network allowed the business to generate greater revenue and profitability by better targeting advertisements and delivering more advertisements through increased usage of its product platform. However, consumers apparently didn’t see the value from combining search and social networking; to the consumer, the jobs are very different and arise in different circumstances in their lives. So while Google maintains its exceptional search business, its social network failed to gain momentum.
Contrast Google’s experience to that of Daimler, which recognized that car2go was a very different business and established it far afield from the home office and existing business. Daimler started car2go as an experiment tested by its employees working in Ulm, Germany. It housed the business in a corporate incubator that does not report to the existing consumer automotive businesses and designed it from the outset to fulfill Daimler’s core job of providing mobility, but without the need to convince consumers to purchase vehicles. Recognizing that the priorities of a business that rents cars by the minute are very different from those involved in selling luxury vehicles, Daimler has kept car2go separate and allowed it to develop a unique business model capable of fulfilling its job profitably. However, car2go benefits from Daimler’s ownership by using corporate resources where appropriate — for example, car2go rents only vehicles in the Daimler portfolio, principally the Smart Fortwo.
To achieve successful business model innovation, focus on creating new business models, rather than changing existing ones. As business model interdependencies arise, the ability to create new businesses within existing business units is lost. The resources and processes that work so perfectly in their original business model do so because they have been honed and optimized for delivering on the priorities of that model. The classic example of this was the movie rental company Blockbuster, which attempted to develop a new DVD-by-mail business in response to the rise of Netflix Inc. by integrating that offering with its existing store network. This “bricks-and-clicks” combination made perfect sense to Blockbuster’s managers, but what became obvious only in hindsight was that the two models would be at war with each other — the asset velocity required to maintain a profitable store network was incompatible with the DVD-by-mail offering. The paradox that managers must confront is that the specialized capabilities that are highly valuable to their current business model will tend to be unsuitable for, or even run counter to, the new business model.
Building a Business Creation Engine
For some time, we’ve argued that companies should build a business creation engine, capable of turning out a steady stream of innovative new business models, but to date no company we know of has built an enduring capability like that. We think that such an engine of sustained growth would quickly prove to be a company’s most valuable asset, providing growth and creating new markets. But unleashing this growth potential requires very different behaviors than those required to successfully exploit existing markets.
The challenge, as the journey metaphor we’ve developed here should make clear, is that what is necessary is to turn an event — the act of creating a new business and a new business model — into a repeatable process at the corporate level. It must be a process because events are discrete activities with definitive start and end points, whereas processes are continuous and dynamic. Learnings from a previous event do not naturally or easily flow to subsequent events, causing the same mistakes to be repeated over and over. In contrast, processes by their nature can be learning opportunities that incorporate in future attempts what was discovered in previous iterations. Enacted as a process, the act of creation will improve over time and refine its ability to discover unfulfilled customer jobs and create new markets; the success rate will improve alongside the process, creating a virtuous cycle of growth.
While we have not discovered a perfect exemplar of this discipline, we have been tracking the efforts of some leading companies that are intent on building such a capability. While it is too early to hold any of them up as success stories, we can nonetheless discern five approaches that we believe have the potential to lead to success. Let’s look at each of these approaches in turn.
Spot future growth gaps by understanding where each of your business units is on the journey. In our course at Harvard Business School, we teach students to use a tool called the aggregate project plan to allocate funding to different types of innovation. 11 Such a plan categorizes innovations by their distance from existing products and markets and specifies a desired allocation of funding to each bucket. We see application for this tool here as well.
The innovation team at Carolinas HealthCare System, a not-for-profit health care organization based in Charlotte, North Carolina, performed this type of analysis and identified a need to field additional innovation efforts that reflected the organization’s belief that hospitals will be less central in the health care system of the future. Armed with this view, Carolinas HealthCare System has been able to plan innovation activity by type, ensuring that the organization invests appropriately across all three categories of the business model journey. As Dr. Jean Wright, chief innovation officer at Carolinas HealthCare System, said, “The strength of the journey framework is that it allowed us to see that our investments in business creation are very different from our investments in our existing businesses. More importantly, it has helped us see that both types are important.”
Run with potential disruptors of your business. Another approach is to create incentives and channels for entrepreneurs to bring new and, in some cases, potentially disruptive business models to you, either as potential customers or as ecosystem partners. ARM Holdings plc, a developer and licenser of system-on-chip semiconductors, headquartered in Cambridge, U.K., has had success viewing itself as the central, coordinating node of a symbiotic ecosystem of independent semiconductor manufacturers and consumer products companies, rather than as a traditional semiconductor company that develops and manufactures proprietary, standard products. Today, nearly every smartphone and mobile device includes at least one ARM design. The company achieved this ubiquity by inviting customers and consumers into its development process so that it will be the first company called by customers seeking to design a new chip. It does this in two ways: first, by incorporating knowledge across its entire ecosystem that allows it to develop optimized end-to-end solutions for customers, and second, by employing a royalty-based revenue model that ensures ARM’s incentives are aligned with those of its customers.
Start new businesses by exploring the job to be done. When identifying new market opportunities, it’s critical that you begin with a focus on the customer’s job to be done, rather than on your company’s capabilities. It’s tempting to look at your capabilities as the starting point for any expansion, but capabilities are of no use without a job for them. For incumbents, this requires staying focused on the job rather than the market or capability. One example of this discipline is Corning Inc., the manufacturer of specialty glass and ceramic materials based in Corning, New York. When it becomes apparent that a Corning business can no longer generate a premium price from its technical superiority — when it reaches the efficiency innovation stage, in our framework — the company divests that business and uses the proceeds to expand businesses in the sustaining stage and to create new ones. For example, when Corning realized that liquid crystal display (LCD) would eventually replace cathode ray tube (CRT) technology to become the future of display, the company focused on the job to be done — display — rather than just on the CRT market, which at the time was important to the company. Corning began inventing products to enable the growth of the LCD industry and eventually decided to exit the CRT market. 12 To Corning, businesses serve needs, not markets, and as technological or market shifts occur, the company continues to grow by remaining focused on the need, which we call the job.
Resist the urge to force new businesses to find homes in existing units. When executives start new businesses, they often look at them and wonder, “Where do I stick this in my organization?” They feel pressure to combine new businesses with existing structures to maximize efficiency and spread overhead costs over the widest base, but this can spell doom for the new business. When a new business is housed within an existing unit, it must adopt the priorities of the existing business to secure funding; in doing so, the new business often survives in name but disappears in effect.
Once a new business is launched, it must remain independent throughout the duration of its journey, but maintaining autonomy requires ongoing leadership attention. The forces of efficiency operate 24/7 inside an organization, rooting out any cost perceived to be superfluous; standing against these forces requires the constant application of a counterforce that only the company’s most senior leaders can provide. In the quest for efficiency, what has been somehow forgotten is the vital leadership role that corporate executives can play in fostering organizational innovation by countenancing the creation of multiple profit formulas and housing these different businesses in a portfolio of business models.
Use M&A to create internal business model disruption and renewal. Lastly, while we’ve focused most of our attention on organic activities, there’s a very valuable role for M&A in a business growth engine. 13 Although at the extreme, this approach can result in a quasi-conglomerate structure that history has proved to be ineffective, there are exceptions. EMC Corp., based in Hopkinton, Massachusetts, adopted this approach with the creation of its federation structure when it floated VMware Inc., a company it had acquired three years earlier, as a publicly traded subsidiary in 2007. Much M&A activity designed to change an existing business model fails because it’s done for the wrong reasons and managed in the wrong way, often resulting in the integration of units that should remain autonomous. In contrast, EMC’s federation structure allows each business to pursue its individual objectives while coordinating the company’s activity as a whole. This embedded capability for exploiting existing markets while identifying and investing in new markets allowed EMC to expand out of its traditional memory business into machine virtualization, agile development, and information security.
The Greatest Innovation Risk
Executives sometimes prefer to invest in their existing businesses because those investments seem less risky than trying to create entirely new businesses. But our understanding of the business model journey allows us to see that, over the long term, the greatest innovation risk a company can take is to decide not to create new businesses that decouple the company’s future from that of its current business units.
We take great hope from the insights about business model innovation and corporate renewal that we have explored in this article — not because we believe that business units can evade or escape the journey that we have described, but because we believe that the corporations that house these units can. There remains much to be learned about corporate renewal and the business model journey, but we hope that insights from the business model road map can help companies learn how to create robust corporate-level business creation engines that will renew their organizations and power growth. The challenge is great — but so are the potential rewards.
About the Authors
Clayton M. Christensen is the Kim B. Clark Professor of Business Administration at Harvard Business School in Boston, Massachusetts. Thomas Bartman is a former senior researcher at the Forum for Growth and Innovation at Harvard Business School. Derek van Bever is a senior lecturer of business administration at Harvard Business School, as well as director of the Forum for Growth and Innovation.
1. PwC, “2015 US CEO Survey: Top Findings — Grow and Create Competitive Advantage,” n.d., www.pwc.com.
2. Z. Lindgardt and M. Ayers, “Driving Growth with Business Model Innovation,” October 8, 2014, www.bcg.perspectives.com.
3. See D.A. Garvin, “The Processes of Organization and Management,” Sloan Management Review 39, no. 4 (summer 1998): 33-50. In discussing processes, we refer to all of the processes that Garvin identified in that article.
4. This business model framework was developed in 2008; see M.W. Johnson, C.M. Christensen, and H. Kagermann, “Reinventing Your Business Model,” Harvard Business Review 86, no. 12 (December 2008): 50-59.
5. For more information about organizational capabilities, see C.M. Christensen and S.P. Kaufman, “Assessing Your Organization’s Capabilities: Resources, Processes, and Priorities,” module note 9-607-014, Harvard Business School, Boston, Massachusetts, August 21, 2008, http://hbr.org.
6. See E.H. Schein, “Organizational Culture and Leadership” (San Francisco, California: Jossey-Bass, 1985).
7. It’s worth noting that startups typically begin with one business unit, which is the company. Then as the organization grows, companies typically create corporate offices and business units that separate responsibility for the administration of the organization from the specific business. Today, managers tend to operate lean corporate offices that often function as thin veneers between the business and investors, but we believe that there is a vital role for the corporate office in leading business creation and developing innovation.
8. P.F. Drucker, “The Practice of Management” (New York: Harper & Row, 1954).
9. For a more complete treatment of jobs to be done, see C.M. Christensen, T. Hall, K. Dillon, and D.S. Duncan, “Competing Against Luck: The Story of Innovation and Customer Choice” (New York: HarperCollins, in press).
10. W. Shih and M. Pierson, “Boeing 737 Industrial Footprint: The Wichita Decision,” Harvard Business School case no. 612-036 (Boston, Massachusetts: Harvard Business School Publishing, 2011, revised 2012).
11. S.C. Wheelwright and K.B. Clark, “Creating Project Plans to Focus Product Development,” Harvard Business Review 70, no. 2 (March-April 1992): 70-82.
12. Authors’ teleconference with David L. Morse, executive vice president and chief technology officer, Corning Inc., March 8, 2016.
13. J. Gans, “The Disruption Dilemma” (Cambridge, Massachusetts: MIT Press, 2016).
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Business Model Innovation: What to do When Plan A Doesn’t Work
par StartupShelter.be | Juin 23, 2014 | Business Model Innovation , Business Models
Business Model Innovation: What to do When Plan A Doesn’t Work ?
All aspiring entrepreneurs have a Plan A and nearly of all them believe that Plan A will succeed. But what happens if it doesn’t?
The sad truth is most of these brilliant hopefuls do not have a solid Plan B or an alternative plan to the initial one. Business model innovation is not under their radar. And this is where experienced entrepreneurs differ from the rookies.
The veteran entrepreneurs know very well that in most cases, the initial blueprint they made didn’t lead them to success. Unexpectedly for beginners, it will always be the second, third, or fourth plan that made it to the roster of fruitful ventures and business model innovation should not just be in the back burner.
Why most initial plans don’t deliver
Most successful business ventures did not succeed as planned. Entrepreneurs had to made calculated and risky modifications with their business models along the way in order to cater to the need of the changing consumer demand and behavior.
Most Plan A’s do not deliver because they were crafted prior to actually experiencing the current and volatile customer needs. Plan A’s are like prototypes that are always in need of revision and refinement based on concrete and tangible experience on the ground.
Creating Plan B, C, D, and possibly more
Entrepreneurs could improve their initial business plans by referring to the experience of other enterprises, learning what has worked and what has not worked for them, and synthesizing it.
In looking for references, entrepreneurs must consider ventures that are comparable to the one they envision of, as well as businesses that are completely different from it. Analyze the success and pitfalls of other enterprises to identify which strategy should be applied in the new business model innovation venture one is currently pursuing. The best way to do that is to meet other entrepreneurs and share your plans.
But creating another plan to address the failure of the first one does not only require lessons from the cases of other business ventures. Remember that there is a limit to what the past could tell us about a present endeavor. When push comes to shove, there are times when entrepreneurs need to make decisions out of instinct and leap of faith.
However, entrepreneurs must be fully aware that decisions made out of a pig in a poke could affect the whole business plan and could actually cause it to break down altogether. This is why entrepreneurs need to devise a metric by which they could gauge the success rate of those leap-of-faith-kind-of decisions in their business model innovation initiative.
By tracking and collecting data using the said metric, entrepreneurs are able to substantiate or invalidate their leaps of faith (we call this hypothesis testing) . This metric should be designed to address one of the nine fundamental blocks of your business model innovation initiative, which include: value proposition, customer segment & relationship, channels, key activites, resources & partners, revenue streams and cost structure. Don’t try to measure all of them ! This is a step by step process. Too much information kill information.
In summary, creating another plan and forming more in the future involves pondering each of the blocks of the business model, applying lessons from the history of other companies, and experimentally challenging assumptions to prove or disprove them. The success of business model innovation depends on whether all of the afore-mentioned processes are integrated synergistically into a sound and solid tactic. The Lean Startup methodology is pretty similar to this approach: Build, Mesure & Learn.
What entrepreneurs must remember is that while it is unlikely for them to attain success with their initial plan, Plan B and beyond could thema better fighting chance.
Extra information: Check out this HBR video on Strategies for Learning from Failure
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Innovation dans les business models : Qu’est-ce que c’est et pourquoi c’est important ?
Amazon a été lancé en 1995 en tant que « plus grande librairie du monde ». Vingt-deux ans plus tard, cette « librairie » est devenue un leader de l’informatique en nuage, peut livrer des produits alimentaires à domicile et produit des séries télévisées récompensées par des Emmy Awards.
L’entreprise, qui pèse un billion de dollars, a atteint cette croissance grâce à sa volonté constante d’innover dans son modèle commercial afin de relever de nouveaux défis et de saisir de nouvelles opportunités.
Amazon est extraordinaire en matière de développement de nouveaux business models, Ils se regardent d’un point de vue défini par le client.
Cette approche a permis à Amazon de se développer car, plutôt que de s’appuyer sur une seule source de revenus ou un seul segment de clientèle, l’entreprise se demande en permanence « quelle sera la prochaine étape ? ». Cela a permis aux dirigeants d’itérer sur son business model en conséquence, en expérimentant à plusieurs reprises un processus connu sous le nom d’innovation de business model.
Comme le démontre le succès d’Amazon, ce processus peut être incroyablement passionnant et avoir un impact considérable lorsque vous en avez le contrôle. Toutefois, lorsque la nécessité d’innover votre modèle d’entreprise vous est imposée par des forces extérieures, elle peut également être considérée comme une perturbation.
Par exemple, aujourd’hui, le nouveau coronavirus provoque des changements considérables dans l’économie nationale et mondiale. De nombreuses entreprises sont contraintes d’innover et d’adapter leurs business models afin de relever ces défis, sous peine d’être victimes de ces changements radicaux.
Lisez ce qui suit pour découvrir ce qu’est l’innovation en matière de business model et pourquoi il est si important pour les entreprises d’être capables de changer.
Qu’est-ce que l’innovation en matière de business model ?
Un business model est un document ou une stratégie qui décrit comment une entreprise ou une organisation apporte de la valeur à ses clients. Dans sa forme la plus simple, un modèle d’entreprise fournit des informations sur le marché cible d’une entreprise, les besoins de ce marché et le rôle que les produits ou services de l’entreprise joueront pour répondre à ces besoins.
L’innovation du business model décrit donc le processus par lequel une organisation ajuste son business model. Souvent, cette innovation reflète un changement fondamental dans la manière dont une entreprise apporte de la valeur à ses clients, que ce soit par le développement de nouvelles sources de revenus ou de nouveaux canaux de distribution.
Exemple d’innovation de business model : L’industrie du jeu vidéo
Amazon n’est pas la seule entreprise connue pour innover en permanence son business model.
L’industrie du jeu vidéo, par exemple, a connu plusieurs périodes d’innovation de son modèle commercial ces dernières années, explique M. Collier, en imaginant de nouvelles façons de gagner de l’argent grâce aux clients.
Lorsque les jeux vidéo ont été créés, les consoles qui les hébergeaient étaient chères et encombrantes, ce qui les mettait hors de portée de la plupart des consommateurs. C’est ainsi qu’ont vu le jour les salles de jeux électroniques, qui faisaient payer les clients pour acheter les crédits nécessaires pour jouer aux jeux.
Les processus de fabrication et les progrès technologiques ont facilité la création d’unités plus petites et plus économiques, mais des sociétés comme Atari ont profité de la demande en vendant des unités directement au client, ce qui constitue un changement radical par rapport à la pratique habituelle.
Plus récemment, les développeurs de jeux ont dû innover rapidement en matière de modèle économique afin de répondre à l’évolution de la demande des clients, dont beaucoup veulent pouvoir jouer à leurs jeux directement sur leurs smartphones.
À l’origine, de nombreuses entreprises ont adapté leurs pratiques afin de proposer leurs jeux dans ce format, en faisant payer les consommateurs sous forme d’abonnement ou en les faisant payer pour débloquer de nouveaux niveaux. Certaines de ces entreprises ont toutefois réussi à innover leurs modèles commerciaux pour rendre le jeu gratuit pour l’utilisateur final en incorporant de la publicité dans l’application ou en vendant des marchandises telles que des T-shirts et des peluches. Cette pratique, ont-ils constaté, a permis d’augmenter considérablement leur portée, tout en rapportant des fonds substantiels des consommateurs.
Les concurrents peuvent facilement changer leur façon de fixer les prix. C’est pourquoi il est crucial pour les entreprises de prendre en compte la manière dont leurs produits sont livrés.
L’importance de l’innovation du business model
L’innovation du business model permet à une entreprise de tirer parti de l’évolution des demandes et des attentes des clients. Si des entreprises comme Amazon et Atari n’avaient pas été capables d’innover et de modifier leurs business model, il est fort possible qu’elles aient été évincées par de nouveaux venus mieux à même de répondre aux besoins des clients.
Exemple d’innovation de modèle d’entreprise : Blockbuster contre Netflix
Prenez Blockbuster, par exemple. La chaîne de location de vidéos a été confrontée à une série de défis, notamment lorsque les DVD ont commencé à supplanter les cassettes VHS. Les DVD prenaient moins de place dans les rayons, offraient une meilleure qualité vidéo et audio, et étaient également assez durables et fins pour être expédiés par la poste – c’est là que les fondateurs de Netflix, Reed Hastings et Marc Randolph, ont repéré une opportunité.
Ils ont lancé Netflix en 1997 en tant qu’entreprise de DVD par courrier, permettant aux clients de louer des films sans avoir à sortir de chez eux. En prime, Netflix pouvait stocker ses produits dans des centres de distribution ; elle n’avait pas besoin de maintenir des stocks dans plus de 9 000 magasins et de payer les mêmes coûts d’exploitation que Blockbuster.
Il a fallu sept ans à Blockbuster pour lancer son propre service de DVD par courrier. À ce moment-là, Netflix avait un avantage concurrentiel et son objectif était de lancer un service de streaming, ce qui obligeait Blockbuster à jouer un jeu de rattrapage constant. Au début de 2014, tous les magasins Blockbuster restants ont fermé leurs portes.
Le problème de Blockbuster était en réalité la distribution, Les DVD ont inspiré Netflix, et le changement technologique a ensuite entraîné un changement de modèle économique. Et ces changements sont beaucoup plus difficiles à copier. Vous éliminez des pièces clés dans la façon dont une entreprise fonctionne. »
Pour cette raison, il est souvent plus difficile pour les marques historiques d’innover. Ces entreprises fournissent déjà un produit ou un service que leurs clients attendent, ce qui rend plus difficile pour les équipes d’élaborer une stratégie sur ce qui va suivre ou de réfléchir à la manière dont le secteur pourrait être perturbé.
Les perturbations sont généralement le fait de nouveaux entrants. Les organisations établies gagnent déjà de l’argent.
Exemple d’innovation de business model : Kodak
En se concentrant uniquement sur les flux de revenus existants, les organisations pourraient toutefois connaître un sort similaire à celui de Kodak. L’entreprise représentait autrefois 90 % des ventes de films et 85 % des ventes d’appareils photo. Bien qu’impressionnant, ce n’était que le problème : Kodak se considérait comme une entreprise de films et de produits chimiques, alors lorsque l’ingénieur de l’entreprise, Steven Sasson, a créé le premier appareil photo numérique, Kodak a ignoré cette opportunité commerciale. Les dirigeants craignaient que le passage au numérique ne rende les produits existants de Kodak inutiles et n’affecte sa principale source de revenus. L’entreprise a perdu son avantage de pionnier et a été contrainte de déposer le bilan.
Exemple d’innovation de modèle d’entreprise : Mars
Mars a commencé comme une entreprise de bonbons, en commercialisant des marques populaires comme Milky Way, M&M’s et Snickers. Au fil du temps, cependant, Mars a commencé à s’étendre aux aliments pour animaux de compagnie et, finalement, à acquérir des hôpitaux pour animaux. Début 2017, Mars a acheté VCA – une société qui possède environ 800 hôpitaux pour animaux – pour 7,7 milliards de dollars, renforçant ainsi son emprise sur le marché des animaux de compagnie.
Mars s’est penchée sur ses capacités fondamentales, ce qui est l’essence même de l’entrepreneuriat d’entreprise. Il s’agit d’envisager vos produits et services sous un angle nouveau. Tirer parti de quelque chose dans lequel vous êtes vraiment bon et l’appliquer de manière nouvelle à de nouveaux produits.
Le rôle de l’innovation agile et Lean
La mise en œuvre de l’innovation agile est avantageuse. L’innovation agile permet aux équipes de développer, de prototyper et de valider de nouveaux modèles commerciaux plus rapidement et avec moins de ressources en recueillant les commentaires des clients tôt et souvent.
Je recommande aux entreprises de commencer par une hypothèse : « J’ai ce nouveau client et voici le problème que je résous pour lui », par exemple. À partir de là, les employés peuvent commencer à tester ces hypothèses clés en utilisant différentes techniques d’idéation et de marketing pour recueillir des informations sur les clients, comme des enquêtes. Ces commentaires des clients peuvent ensuite être exploités pour développer un pilote ou un prototype qui peut être utilisé pour mesurer les hypothèses de l’équipe. Si la première idée ne fonctionne pas, les entreprises peuvent plus facilement pivoter et tester une nouvelle hypothèse
C’est une grande partie que les gens oublient de faire. L’expérimentation nous permet de tester rapidement et perpétuellement jusqu’à ce que nous arrivions à un modèle qui fonctionne.
Poursuivre l’innovation dans l’entreprise
Outre l’innovation en matière de business model, les entreprises pourraient également poursuivre d’autres types d’innovation, notamment :
L’innovation de produit : Il s’agit du développement d’un nouveau produit, ainsi que de l’amélioration des performances ou des caractéristiques d’un produit existant. L’itération continue de l’iPhone d’Apple en est un exemple. Innovation de processus : L’innovation de processus est la mise en œuvre de méthodes de production et de livraison nouvelles ou améliorées dans le but d’augmenter les niveaux de production d’une entreprise et de réduire les coûts. L’un des exemples les plus notables de cette innovation est l’introduction par la Ford Motor Company de la première chaîne de montage mobile, qui a permis de réduire le temps de montage d’un véhicule de 12 heures à environ 90 minutes.
Le choix de l’innovation de produit, de processus ou de modèle d’entreprise dépendra largement du client et du secteur d’activité de l’entreprise. Les dirigeants d’une entreprise de produits, par exemple, doivent constamment réfléchir à la manière dont ils prévoient d’innover leur produit.
Lorsque l’innovation commence à ralentir, c’est à ce moment-là que les entreprises doivent réfléchir et envisager des capacités de nouvelle génération.
Si une entreprise essaie de choisir où concentrer ses efforts, le modèle d’entreprise est toutefois un point de départ recommandé.
L’innovation en matière de business model a souvent plus d’impact sur une entreprise que les innovations en matière de produits. C’est le modèle commercial d’Amazon qui perturbe le marché.
L’innovation n’est pas toujours facile
Si les exemples ci-dessus montrent que l’innovation est un élément important de la gestion d’une entreprise, il est également clair qu’elle n’est pas toujours facile. L’histoire des entreprises regorge d’exemples d’entreprises qui n’ont pas su innover au moment où elles en avaient le plus besoin.
Heureusement, il existe des mesures que les propriétaires d’entreprise, les entrepreneurs et les professionnels peuvent prendre pour être mieux à même de poursuivre l’innovation lorsqu’une opportunité se présente.
Apprendre les principes fondamentaux de l’évolution des entreprises et des secteurs d’activité vous permettra de mener à bien vos propres initiatives. Évaluez et disséquez les réussites et les échecs des entreprises du passé, et apprenez à appliquer ces précieuses leçons à vos propres défis.
Sur le même sujet.
Le marché des produits de grande consommation ( CPG ) regorge de nouveaux produits et le moment n’a jamais été aussi propice à l’innovation.
in " Innovation "
Comment prospérer grâce à l’innovation malgré un leadership faible
Comment l’IOT aide à stimuler l’innovation dans le domaine des énergies renouvelables
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- Original Article
- Open Access
- Published: 28 October 2021
Business Model Innovation Through the Lens of Time: An Empirical Study of Performance Implications Across Venture Life Cycles
- Elena Freisinger 1 ,
- Sven Heidenreich ORCID: orcid.org/0000-0003-2278-0610 2 ,
- Christian Landau 3 &
- Patrick Spieth 4
Schmalenbach Journal of Business Research volume 73 , pages 339–380 ( 2021 ) Cite this article
Current literature suggests that the innovation of a business model is among the most important success factors for organizations and has a positive influence on their performance. What is not yet clear, however, is how this relationship unfolds during an organization’s life cycle. We posit that business model innovation strongly contributes to firm performance in earlier phases, but ultimately gets less important. We therefore collected data on 250 organizations in Germany and used structural equation modeling for analytical purposes. We make the following two main contributions to the literature: (1) We confirm recent findings about the positive impact of business model innovation on performance; (2) we provide first empirical evidence for the important role of life cycle stages as moderator with regard to this relationship. With respect to the latter, our findings show that business model innovation is an important pathway of organizations, especially in their early years of existence, yet somewhat diminishing over time. In conclusion, this study opens new research avenues by extending and incorporating explanations for the life cycle theory and business model innovation.
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Novel business models appear to play an important role in disrupting entire industry dynamics and changing “the way people live, work, consume, and interact with each other” (Demil et al. 2015 , p. 2). Uber, for example, a new venture founded in 2009, bypassed the traditional licensing system of taxi companies by offering a location-based app that allows individuals to hire a private on-demand driver (de Jong and van Dijk 2015 ). Similarly, bitcoin-based business models successfully disrupted the way traditional banking institutes made business for decades (de Jong and van Dijk 2015 ). Anecdotal evidence shows that profitable business models do not necessarily entail a better or more innovative product, but change the game of the industry (Afuah 2014 ). Hence, it is not surprising that design of successful novel business models have turned into a key strategic priority for managers in multiple industries (Chesbrough 2007 ; Johnson et al. 2008 ; Massa et al. 2017 ). Managers of incumbent firms and entrepreneurs are increasingly using the business model concept in order to understand and to rethink novel ways on how to achieve their company’s goals (Laudien and Daxböck 2017 ; Massa et al. 2017 ). Yet, not only in practice but also in academia, business models are a largely discussed topic spanning almost all disciplines of economics, e.g., technology and innovation management (e.g. Tripsas and Gavetti 2000 ; Tucci and Massa 2013 ), strategy (e.g. Casadesus-Masanell and Zhu 2013 ; Suh et al. 2020; Teece 2010 ), and sustainability (e.g. França et al. 2016 ; Klein et al. 2021; Snihur 2016 ). Ever since the concept has firstly been brought to academia, business model innovation (BMI) is considered as a source of competitive advantage (Casadesus-Masanell and Zhu 2013 ; Demil and Lecocq 2010 ; Teece 2010 ) that ultimately leads to financial performance (Foss and Saebi 2017 ). This prominent link is somewhat the crux, but also the cornerstone of business model research.
Up until 2021, research on BMI is still very much on the rise fueled through recent empirical studies showing that BMIs are a source of competitiveness and competitive advantage (Clauss et al. 2019 a; Teece 2010 ; Wirtz et al. 2010 ), with “the potential to improve enterprise performance” (Lambert and Davidson 2013 , p. 676) or even change the market equilibrium (Trabucchi et al. 2019 ). As a result, in the last twenty years, a growing body of literature is showing a strong interest in BMI denoted as a “new subject of innovation, which complements the traditional subjects of process, product, and organizational innovation” (Zott et al. 2011 , p. 1032). However, besides many others, especially the effect-side of BMI has been paid considerable attention to, but a systematic understanding on how BMI contributes to firm success is still lacking (Foss and Saebi 2017 ). So far, only a handful studies were able to describe this widely-stated association but mainly in a correlational way and without considering the dimension of time (Foss and Saebi 2017 , 2018 ). Yet, almost twenty years after the advent of business model research, it is still not clear, whether BMI is beneficial to the firm at all (Foss and Saebi 2017 , 2018 ). What we know so far is largely based upon empirical studies that investigate how different business model designs contribute to performance effects (e.g., Wei et al. 2014 ; Zott and Amit 2007 , 2008 ). Current studies have shown that environmental factors, e.g., environmental dynamism (Pati et al. 2018 ), environmental turbulence (Schrauder et al. 2018 ), and environmental resource munificence (Zott and Amit 2007 ) influence the relationship. Yet, besides a handful studies, effect-side BMI research has failed to examine contextual factors, such as firm age, firm size, firm characteristics as well as a firm’s focal value proposition. First empirical studies acknowledge that performance implications differ across firms in their early or late life cycle stages in case of a more efficiency-centered business model design (Brettel et al. 2012 ), a paucity of studies, however, remains investigating the impact of the innovativeness of the business model on performance implications for new ventures and more established firms. In a similar vein, research has so far lacked to account for different firm-types, i.e., product- or service-oriented firms, and how their engagement in BMI and the resulting performance implications varies for new and more mature ventures.
In order to improve our understanding, this paper explores the prominent relationship between BMI and firm performance by (1) providing a systematic literature review of empirical studies investigating this relationship, (2) presenting further empirical evidence on the beneficial character of BMI, (3) examining the moderating influence of early and late life cycle stages, and (4) comparing the findings for product- and service-oriented BMIs. We therefore collected data on 250 new and more mature ventures in Germany and used structural equation modeling for analytical purposes. We make the following two main contributions to the literature: (1) we add further evidence to the body of knowledge of effect-side research of BMI, and (2) we bring new contingency factors into the discussion. The paper first gives a systematic literature review, followed by hypotheses derivation. The next section emphasizes the study’s research design and methodology, afterwards we present our results. The last section draws these findings together, discusses its implications for theory, as well as for practice, and concludes with limitations and avenues for further research.
2 Systematic Literature Review
2.1 systematic literature review of the effect-side of bmi research.
In order to grasp the amount of current knowledge on the relationship between BMI and firm performance, we conducted a systematic literature review using the procedure suggested by Denyer and Tranfield ( 2009 ). By executing a systematic search in three scientific databases, namely in EBSCO Business Source Complete, Elsevier-Science Direct, and Scopus, we not only focused on the search term “business model innovation”, but also included the expression(s) “business model design”, “business model development”, “business model renewal” or “business model change” which are used interchangeably for the same phenomenon (Foss and Saebi 2017 ). The search terms had to be included either in the title, the abstract, or in the keywords of peer-reviewed articles between 2000 and December 2020 and by that we identified 1676 articles after removing duplicates. In a next step, we applied an objective criterion (Denyer and Tranfield 2009 ) to assess the relevance of each study. More specifically, we excluded articles which were not ranked A+, A, or B in the VHB-JOURQUAL Footnote 1 ranking to ensure quality as well as theory-focused work. However, we included all articles from the Journal of Business Models, a journal devoted to establishing the discipline of business models as a separately recognized core discipline to get a thorough picture of the literature. This resulted in a total of 397 articles. Furthermore, we reviewed and coded the remaining articles using the MAXQDA software and eliminated publications without a primary focus on BMI; 260 articles were eventually deemed as a fit for our research purpose. We again reviewed and assigned these articles into the categories of antecedents, process, construct, and effects. We found a large volume of published studies describing the role of organizational and individual antecedents ( n = 85), research investigating the act of designing and implementing BMIs ( n = 75), and investigations into the construct itself ( n = 75). However, only a small proportion of studies has devoted its attention to the effect-side of BMI ( n = 40), yet with a certain increase in recent years (for an overview see Table 1 ).
What we know about BMI performance relationship is largely based upon four types of empirical studies that investigate how BMI impacts performance. The first type encompasses the activity system view (Zott and Amit 2010 ) and investigates how different design themes (Zott and Amit 2007 ) impact performance variables such as firm performance (Brettel et al. 2012 ; Wei et al. 2017 ), technological innovation performance (Hu 2014 ), start-up’s growth performance (Balboni et al. 2019 ), or small and medium-sized enterprise (SME) performance (Pati et al. 2018 ). Another stream of effect-side research, the element-based view (Clauss et al. 2019 b) connects the innovativeness of the business model with different outcomes, such as strategic flexibility (Spieth and Schneider 2016 ), internal corporate venturing performance (Futterer et al. 2018 ), and again firm performance (Clauss et al. 2019 a). A third type of studies examines the effects of different aspects that come along with BMI, such as different types of revenue models (Konya-Baumbach et al. 2019 ), product- and service-orientation (Visnjic et al. 2016 ), or technology and consumer orientation in BMIs (Guo et al. 2020 ), as well as business model adoption (Karimi and Walter 2016 ) and business model imitation behavior (Frankenberger and Stam 2020 ). While these study entail an inside-firm perspective, the fourth type and more recent research shift to a customer-oriented view and examine the effects of BMI on customer satisfaction (Clauss et al. 2019 b), adoption intention (Futterer et al. 2020 ), and brand loyalty (Spieth et al. 2019 ).
With respect to potential benefits, these studies point to the fact that BMI is a powerful predictor for firm performance (Cucculelli and Bettinelli 2015 ; Karimi and Walter 2016 ; Visnjic et al. 2016 ). However, many questions remain in this young field of study. First, while the majority of the studies connects different business model designs with firm performance, more research is needed examining the impact of the innovativeness of business models within the element-based view. There are relatively few current studies that indeed present first evidence for the beneficial character but replicating these studies in different contexts might shed new light on the most prominent statement in the BMI literature. Second, while few studies have integrated contingency and moderating variables in their research, there are many factors that may influence the strength of that effect. Current studies have shown that environmental factors, e.g., environmental dynamism (Pati et al. 2018 ), environmental turbulence (Schrauder et al. 2018 ), and environmental resource munificence (Zott and Amit 2007 ), influence the relationship. Yet, besides a handful studies, effect-side BMI research has failed to examine contextual factors, such as firm age, firm size, firm characteristics as well as a firm focal value proposition. Yet, in combination with an element-based approach, the exploration of contextual factors holds the potential to deepen our understanding of the BMI performance relationship. Previous studies have indicated that BMI performance relationship is especially contingent on the factor time (Balboni et al. 2019 ; Foss and Saebi 2017 ; Pati et al. 2018 ), but a clear understanding of the impact on the effect strength is still missing. In the following, we will first discuss the core assumptions of BMI research and subsequently develop an understanding on how different life cycle stages affect this relationship and discuss how this relationship might further vary for product- and service-oriented BMIs.
2.2 Business Model and Business Model Innovation
For a long time, business models have mainly been used as a template or narrative device to understand and communicate a firm’s current activities by managers (Massa et al. 2017 ). In 2003, Mitchell and Coles moved the idea of managers having the ability to purposefully change a business model into the spotlight (Foss and Saebi 2017 ). By adding the additional dimension of innovation (Foss and Saebi 2017 ), business models have eventually become a potential unit of innovation that “complements the traditional subjects of process, product, and organizational innovation” (Zott et al. 2011 , p. 1032). A business model is a formal conceptual representation of a company (Massa et al. 2017 ) and thereby reflects the “design or architecture of the value creation, delivery, and capture mechanisms” of a firm (Teece 2010 , p. 172). In terms of conceptualization, two dominant views have emerged (Clauss et al. 2019 b): the activity system perspective (Casadesus-Masanell and Ricart 2010 ; Zott and Amit 2010 ) views business models as holistic systemic structures that encompass all activities of a company as well as how and when these activities are carried out (Zott and Amit 2010 ); the element-based perspective approaches the business model construct as a modular set of elements consisting of three (Bocken et al. 2013 ; Clauss 2017 ; Spieth and Schneider 2016 ) or of four elements (Baden-Fuller and Haefliger 2013 ; Futterer et al. 2018 ; Johnson et al. 2008 ; Osterwalder et al. 2010 ). This understanding is rooted in the dynamic perspective on business models (e.g., Casadesus-Masanell and Ricart 2010 ; Demil and Lecocq 2010 ; Martins et al. 2015 ), which refers to dynamic interactions among various business model elements (Casadesus-Masanell and Ricart 2010 ; Demil and Lecocq 2010 ). In the following, we will draw on latter one as the element-based view is generally considered as the cornerstone for BMI research (Clauss 2017 ; Futterer et al. 2018 ; Spieth and Schneider 2016 ). According to the element-based view, business models consists of four interrelated elements, namely (1) value offering, (2) internal value creation, (3) external value creation, and (4) financial architecture (Futterer et al. 2018 ) that capture a firm’s foundational processes (Foss and Saebi 2017 , 2018 ; Saebi et al. 2017 ). The first element, which reflects the value offering of a company, comprises the products and services offered to the target market (Demil and Lecocq 2010 ; Yunus et al. 2010 ), the internal value creation element integrates the methods, processes, structures, and competencies within the company’s value chain (Demil and Lecocq 2010 ; Dubosson-Torbay et al. 2002 ; Osterwalder et al. 2005 ), the third element—the external value creation—describes the relationships with external partners, stakeholders, and distribution channels (Kindström 2010 ; Yunus et al. 2010 ) and the financial architecture element constitutes the company’s revenue mechanisms and cost structure (Chesbrough 2007 ; Osterwalder et al. 2005 ; Yunus et al. 2010 ).
BMI itself is a transformation process that purposely alters the key elements of a business model (Bucherer et al. 2012 ; Clauss et al. 2019 a; Tucci and Massa 2013 ) and nontrivial changes to these key elements of a firm’s business model eventually result in a BMI (Foss and Saebi 2017 ). Firms can either innovate single elements or introduce a whole new business model (Foss and Saebi, 2017 ). While changing “of at least one core element is the necessary condition for BMI to be given, the sufficient condition is represented by a subsequent change of the BM’s underlying logic” (Futterer et al. 2018 , p. 2). Since even the change of one core element induces (minor) changes in other elements as well (Demil and Lecocq 2010 ; Johnson et al. 2008 ), innovating only one element often requires reconfigurations of the business logic and thus may constitute BMI (Foss and Saebi 2017 ). In case of established firms, BMI is deemed either the change of an established business model (Amit and Zott 2012 ; Zott and Amit 2013 ) or the creation of a new innovative business model that is added to their portfolio (Snihur and Tarzijan 2018 ). For new ventures, BMI is typically the creation of a new innovative business model (Foss and Saebi 2018 , 2017 ). Eventually, the reference point for the innovation is either its newness to the firm or its newness to the industry (Foss and Saebi 2017 ).
3 Conceptual Development
3.1 business model innovation and firm performance.
Innovation means “doing something new”, e.g., developing new products, new processes, new markets (Schumpeter 1934 ), and now new business models (Taran et al. 2015 ). In new product contexts, innovation is considered as the extent a new product differs from already existing ones (e.g., Cillo et al. 2010 ; Cooper and Kleinschmidt 1987 ; Danneels and Kleinschmidtb 2001 ), meaning innovativeness is the difference between old and new (Garcia and Calantone 2002 ). More precisely, innovativeness covers the amount of newness relative to a certain base, such as the world, the industry, the firm, or the perception of the customer (Calantone et al. 2006 ; Garcia and Calantone 2002 ). In case of business models, innovativeness captures the relative amount of newness to the focal firm (e.g., Osterwalder et al. 2005 ; Spieth and Schneider 2016 ) or to the industry (Amit and Zott 2012 ; Snihur and Tarzijan 2018 ) depending on the perspective. Hence, following the interpretation that business models are attributes of real firms, being innovative in doing business means executing value-adding activities such as value creation and/or value capture (Massa et al. 2017 ) in the core elements of a business model, namely value offering, internal value creation, external value creation, and financial architecture.
According to Lepak et al. “value creation depends on the relative amount of value that is subjectively realized by a target user (or buyer) who is the focus of value creation—whether individual, organization, or society—and that this subjective value realization must at least translate into the user’s willingness to exchange a monetary amount for the value received” (Lepak et al. 2007 , p. 182). The value creation is typically described in the most integral part of a business model in the value offering element that comprises the products and services offered to the target market (Futterer et al. 2018 ). Such changes optimize the resources and competencies employed more toward customers’ preferences and are more tailored toward customers’ needs, enhancing customer satisfaction (Futterer et al. 2020 ). By innovating the value creation in a way that it delivers greater value to the target market a company is able to outperform its competitors (Normann and Ramirez 1994 , 1993 ; Porter 1985 ). Furthermore, business models also describe the value capture domain: “value may be captured by the use of resources with attributes that make them difficult to imitate, through the source’s own use of creative destruction before competitors can use the innovation, and through methods of resource management” (Lepak et al. 2007 , p. 189). Value creation in business models is reflected in the internal value chain, relationships with external partners, and the financial architecture of a company; i.e., all activities necessary to monetize the value created (Massa et al. 2017 ). Hence, being more innovative in the respective business models elements, leads to cost reduction, process optimization, accessing new markets, and eventually to financial performance improvements (Foss and Saebi 2017 ). This indicates a positive link between business model innovativeness and financial performance improvements.
Therefore, we assume the following—
BMI has a positive effect on firm performance.
3.2 Business Model Innovation and Life Cycle Stages
While prior research often emphasizes BMI as the holy grail for achieving firm performance, more recent research indicates that innovated business models are not always necessarily better than existing business models, such that positive performance implications often strongly depend on contingency factors (Casadesus-Masanell and Ricart 2010 ; Futterer et al. 2020 ; Kranich and Wald 2018 ). Understanding the contingency mechanisms that unfold BMI into positive firm performance implications is of utmost importance for many firms. Yet, effect-side BMI research neglected to thoroughly discuss contingency factors of this valuable relationship. So far, recent research acknowledges that the performance implications of firms might differ across early and late life cycle stages depending on the business model design, i.e., either novelty- or efficiency-based, they have chosen (Brettel et al. 2012 ). Yet a more in-depth understanding is still missing. Both, young ventures and more established firms possess a unique bundle of resources and capabilities depending on their individual life stage that provide benefits and weaknesses (Carr et al. 2010 ). These benefits and weaknesses have an influence on the ventures capability to create and capture value from its BMI (Pati et al. 2018 ). Organizations grow in a predictable pattern (Hanks et al. 1993 ) and move through different life cycle stages (e.g., Gaibraith 1982 ; Kazanjian 1988 ; Laudien and Daxböck 2017 ; Quinn and Cameron 1983 ; Smith et al. 1985 ). Every venture’s life begins with a startup or birth stage, moves through certain growth stages, and ends with a form of maturity or with the decline of an organization (Hanks et al. 1993 ). Due to conceptual vagueness and a lack of distinctness concerning the individual stages (Hanks et al. 1993 ), scholars typically differentiate the early and late life cycle stages of ventures (e.g., Brettel et al. 2012 ; Dodge et al. 1994 ; Engelen et al. 2010 ).
More established firms have typically gained some form of stability and execute a viable and working business model. These firms typically capture more value from their experiences, well-functioning processes, established routines and long-term partnerships (Kotha et al. 2011 ). In case of more established SMEs—or firms in their later life cycle stages—BMI means either the change of an existing business model (Amit and Zott 2012 ; Zott and Amit 2013 ) or the creation of a new innovative business model that is added to its portfolio (Snihur and Tarzijan 2018 ). This may happen due to several reasons, e.g., new entrants in the market (Dewald and Bowen 2010 ), disrupting power of new technologies (Sabatier et al. 2012 ) or a general emphasis on innovation in a company (Sorescu et al. 2011 ). Firms in their later life cycle stages have already gained a good sense of their environment, such as their market, customers, and partners (Zahra and George 2002 ). However, changing an existing business model, like Xerox did when switching from selling copiers to leasing them (Chesbrough and Rosenbloom 2002 ), comes also with idiosyncratic challenges for the innovating firm, such as path dependencies, organizational inertia, new management processes, and types of organizational learning (Tucci and Massa 2013 ). The performance effects realized through a BMI might get mitigated by the transition process the company undergoes.
In contrast, new ventures, or firms in their early life cycles stages, are typically created to pursue unexploited opportunities (Dahlqvist and Wiklund 2012 ), are characterized by smaller firm size, lower age, a more uncertain environment and a different structure (Brettel et al. 2012 ), and have to take on a long journey before overcoming their liability of newness (Stinchcombe 1965 ). In new ventures, business models are an important device to narrow down the initial entrepreneurial idea into a describable opportunity (George and Bock 2011 ). In case of new ventures, BMI means the deployment of an innovative business model right from their inception (Foss and Saebi 2017 ). The reference point for innovation in this case is the industry. Uber, for example, outperformed established taxi companies, that offered the traditional licensing system, by providing a location-based app and a taxi service via private drivers (de Jong and van Dijk 2015 ). By being more innovative with their business models than their competitors, they are doing better in creating and capturing value, which ultimately leads to greater firm performance. We argue that this effect is stronger for young ventures in their early life stages for several reasons. First, new ventures tend to have a stronger business sense with less complex decision-making mechanisms, less inefficiencies in their processes, and less rigid structures (Thornhill and Amit 2003 ). Furthermore, younger ventures deploy an atmosphere of creativity and have clearer information channels (Zaheer and Bell 2005 ). New ventures have not yet built formalized processes and standardized work procedures (Engelen et al. 2010 ), since they have to constantly adapt to new and unknown situations (Roure and Keeley 1990 ). These characteristics of ventures in their early years of existence suggest that they are in a more favorable position to benefit from innovation-related opportunities (Rosenbusch et al. 2011 ), BMI being one of them. While many new business models fail, before a new one becomes viable, these new ventures with their innovative business models are sources of abnormal returns (Tucci and Massa 2013 ).
Hence, we conclude that early stage firms might create and capture greater value from BMI and transform it into performance.
In early stages, BMI has stronger effects on firm performance than in later stages.
3.3 Business Model Innovation and Product- and Service-oriented Firm Types
Previous studies have already identified that BMI has a different impact on performance implications, depending on whether BMIs are product- or service-oriented (e.g., Visnjic et al. 2016 ; Visnjic Kastalli et al. 2013 ). However, previous studies have not yet determined how these effects unfold in early and late stages of a venture’s life.
Service-oriented firms are characterized by intangible products and focus on a more people-oriented business (Masurel and Van Montfort 2006 ). In their early life cycle stages their diversification of object types, clients, and activities is typically rather small (Masurel and Van Montfort 2006 ) and it is crucially important to implement and market their innovative business model. In the later stages, service-oriented firms have typically gained broader diversification, more stable relationships with their customers, and deal with a larger variety of markets, clients, as well as sectors (Masurel and Van Montfort 2006 ). Hence, BMI becomes less important for service-oriented firms, due to other value drivers with greater impact in later stages. In contrast to service-oriented firms, ventures with a greater focus on more tangible assets engage more in product innovation, which is considered as one of the main drivers of value creation (Visnjic et al. 2016 ). However, sole product innovation is deemed less profitable than product innovation embedded in the appropriate business model (Chesbrough and Rosenbloom 2002 ; Teece 2010 ). Product-oriented firms in their early stages normally focus on prototyping, thereby enhancing the design of products and establishing a first production process (Gaibraith 1982 ). However, the main introduction of the product into a market happens at a later stage of the life cycle where the venture is more mature and established (Lumpkin and Dess 1995 ).
The relationship between BMI and firm performance in early and late life cycle stages differs for product- and service-oriented firm types, namely
In case of product-oriented ventures, the performance effect of BMI is significantly higher in later than in earlier stages
In case of service-oriented ventures, the performance effect of BMI is significantly higher in earlier than in the later stages
The proposed research model is depicted in Fig. 1 .
4 Data and Analysis
4.1 data and sample.
In order to answer our research question, we collected data from ventures in German-speaking countries via a cross-sectional research design. With this research design we respond to a former call of Foss and Saebi ( 2017 ) who have suggested “to collect cross-sectional data on business model changes and regress those data against business or corporate performance” (p. 212). Cross-sectional designs have been proven to be a valid approach when investigating the link between BMI and venture performance (e.g., Futterer et al. 2020 ). Yet, cross-sectional designs always have some limitations with regard to establishing causality. In order to alleviate confounding effects surrounding causality that may arise due to a delay of BMI effects on performance outcomes, we assessed the independent variable of BMI at the time of business formation, and the respective dependent variable “firm performance” at the time of the survey. Our sample needs to consist of the key decision makers within their respective ventures, which are considered to be the top management team or the founder(s) of the venture. This is necessary since the key decision makers are those who shape a firm’s strategic orientation (Talke et al. 2011 ) and, hence, the business model. We, therefore, invited entrepreneurs from the most prominent entrepreneurship directories in Germany (e.g., Bundesverband Deutsche Startups, Gründerszene.de, deutsche-startups.de), Switzerland, Austria, and Lichtenstein (Angellist) to participate in our study in 2017. We collected data via a self-administered survey in the months from April to June, including the first approach and one reminder email. We sent an Email to 3884 individual entrepreneurs containing the link to our online-survey or, when no direct contact information was available, to the venture’s e‑mail address and included the information that had to be forwarded to the key decision maker. We advised the respondents to think about their focal venture when answering the question—bearing in mind that entrepreneurs might have more than one venture. Thereby, 268 questionnaires were returned to us. In sum, eighteen returned questionnaires had significant missing values and straight-liners that we deleted, thereby resulting in 250 respondents and an overall response rate of 6.9%. On average, the 250 ventures were founded in 2014 (3 years old) and conducted mostly business in the IT or service industry, which we assessed by the NACE ( N omenclature statistique des a ctivités économiques dans la C ommunauté e uropéenne) scale. NACE is a four-digit classification of economic activities in the European Community and the participants were asked to self-categorize their venture. Since the service industry has proven to be an adequate research context for studies in the BMI context (Laudien and Pesch 2019 ), we also consider our sample as appropriate for our investigation. 61.60% of all ventures had less than 5 employees, 19.60% had 6–10 employees, 9.60% had 11–15 employees and 9.20% had more than 16 employees. The average founder in our study is thirty-four years old, male (84%), obtained a university degree, has about 5 years of start-up experience, funded about 2.40 prior start-ups of which 0.55 failed. Concerns about survival bias are mitigated by the fact that every company can be listed in the public entrepreneurship database. Consequently, immature and young companies are also included. Table 2 presents descriptive statistics and zero-order correlations among all variables used in the analyses.
4.2 Variables and Method
We drew on established measures (see the Appendix for the main constructs and items) and applied seven-point Likert-type scales except where otherwise stated. We also pre-tested the questionnaire with a group of twelve experts, namely PhD researchers working in the economics department at university, thereby ensuring face validity and clarity (Churchill 1979 ).
Business model innovation Business Model Innovation
is operationalized as a molar third-order hierarchical construct adapted from Futterer et al. ( 2018 ) with four formative second-order elements (Chin 2010 ): (1) value offering, (2) internal value creation, (3) external value creation, and (4) financial architecture, enclosing thirty-two items that Futterer et al. ( 2018 ) derived from established scales. The first element, value offering architecture, builds on the following scales: the novelty-centered business model design by Zott and Amit ( 2007 , 2008 ), product superiority to the customer by Lee and Colarelli O’Connor ( 2003 ), and market newness by Dahlqvist and Wiklund ( 2012 ). The items for the second element, internal value creation architecture, are adapted from Gatignon et al. ( 2002 ), whereas the third item, external value creation architecture, was operationalized with items adapted by the market newness scales of Lee and Colarelli O’Connor ( 2003 ), as well as supplier involvement of Chen and Paulraj ( 2004 ). Finally, the fourth element, financial architecture, mainly builds on items adapted by Spieth and Schneider ( 2016 ), and supplemented by items from Chesbrough ( 2007 ), Dubosson-Torbay et al. ( 2002 ), as well as Yunus et al. ( 2010 ). We asked the founders to think about the moment of the foundation of the company and indicate how innovative their business model was. All items were measured according to a seven-point Likert scale anchored by “strongly disagree” and “strongly agree.”
In general, new ventures do not need to publicize their financial data in financial reports (Wang et al. 2017 ) and surveying the key informants of the new ventures is a common approach (Anderson and Eshima 2013 ; Kraus et al. 2012 ). In accordance with this, we assessed firm performance via the respondents’ subjective assessments; they were taken from a synthesis used by Vorhies and Morgan ( 2005 ) and comprise previous measures regarding their customer satisfaction (Fornell et al. 1996 ), profitability (Morgan et al. 2002 ), and market effectiveness (Vorhies and Morgan 2003 ) and are commonly used in effect-side research of BMI (e.g., Balboni et al. 2019 ; Nunes and Do Val Pereira 2020 ). In studies that are based on the key-informant approach due to the absence of mandatory financial reports this scale entails all components a key informant, such as the founder of the venture, is able to assess. All scales were designed as seven-point scales and we estimated overall firm performance as a reflective second-order construct, comprising the three first-order latent performance factors, thereby building a type I hierarchical component model (Hair et al. 2018 ).
Organizational Life Cycle Stage
The moderating variable in our research model, organizational life cycle stage, was operationalized by using the scale of Brettel et al. ( 2012 ) who adapted a five-stage classification scheme from Lumpkin and Dess ( 1995 ). In accordance with this, we followed the approach of Brettel et al. ( 2012 ) and provided an explanatory sentence for each stage. The five stages included (1) startup/conception and development, (2) commercialization/market entry, (3) growth, (4) consolidation, and (5) maturity/diversification. Similar to Brettel et al. ( 2012 ), as well as Engelen et al. ( 2010 ), we built two groups, namely early and later stages. The first one included the stages (1) startup/conception and development, as well as (2) commercialization/market entry. The latter one incorporated the last three stages (3) growth, (4) consolidation, and (5) maturity/diversification. Table 3 gives an overview of the stage classifications.
The relationship between BMI and performance depends on several variables for which we included control variables: age, sex, and education of the key respondents as well as firm size measured according to the number of employees. Although all the firms included in our study were relatively young ventures, the firm size might still influence the relationship between BMI and firm performance.
Common Method Bias
In order to control for common method bias, procedural and statistical remedies were combined (Podsakoff et al. 2012 ). We applied proximal and psychological separation between our independent and dependent variable to reduce the respondents’ ability to use a similar response pattern (Podsakoff et al. 2003 ). Statistical remedies included Harman’s single factor test (Podsakoff et al. 2003 ), the Lindell-Whitney marker variable test (Lindell and Whitney 2001 ), and Kock’s collinearity test (Kock 2015 ). All the independent and dependent variables were included in an exploratory factor analysis, resulting in a total variance of 35.55%, that is below the common threshold of 50% (Podsakoff et al. 2003 ). Next, we applied the Lindell-Whitney marker variable test by integrating the measurement inventory of team trust (Bansal et al. 2004 ) in the model as a theoretically unrelated latent variable (Lindell and Whitney 2001 ). The highest path coefficient turned out to be 0.15, which is below the common threshold of 0.30. In addition, we applied a full collinearity test and found that all the variance inflation factors (VIFs) of the latent constructs in our model were not higher than 3.30 (Kock 2015 ). This indicates that common method variance should not be a concern in our model.
We used structural equation modeling (SEM) to test our research model as this statistical technique allows assessing complex models with different relationships simultaneously (Reinartz et al. 2009 ). More specifically, we applied partial least squares (PLS) SEM that combines indicators to build composite variables (Lohmöller 1989 ), which are designed to be the proxies for the constructs under investigation (Rigdon 2016 ). We have chosen PLS-SEM over covariance-based techniques for several reasons. First, since our study focuses on prediction rather than exploration, indeterminacy is less suitable in a covariance-based approach and more suitable in a PLS approach (e.g. Dijkstra 2014 ). Second and most important, contrary to CB-SEM approaches, PLS-SEM is capable of modeling type IV higher-order constructs (Chin 2010 ), which are present in our research model. PLS-SEM has recently been applied to entrepreneurship studies (e.g. Radosevic and Yoruk 2013 ), in BMI research (Futterer et al. 2018 ), innovation research (Heidenreich et al. 2016 ), and to other management topics (for an overview, see Hair et al. 2011 ). For statistical analyses, SmartPLS 3 (Ringle et al. 2015 ) was used to estimate the inner and outer model parameters by applying a path weighting scheme (Chin 1998 ). We also employed non-parametric bootstrapping (Chin 1998 ; Tenenhaus et al. 2005 ) with 5000 replications and mean replacement as missing value-algorithm, as well as individual-level change pre-processing, to obtain the standard errors of the estimates.
The higher-order latent variable BMI was set up by using the hierarchical component model approach (Lohmöller 1989 ; Tenenhaus et al. 2005 ). In order to handle the measurement issues of higher-order models in PLS-SEM, researchers can apply the repeated indicators approach, the two-stage approach, or the hybrid approach (Becker et al. 2012 ). In a simulation study, Becker et al. ( 2012 ) found that the repeated indicators approach provides better results when it comes to parameter estimates and lower-order construct scores than the other two techniques. Only in certain cases, the approach is particularly problematic: For example, when assessing reflective-formative and formative-formative hierarchical component models (HCM) or when the higher-order construct (HOC) has one or more antecedent latent variables (Becker et al. 2012 ). Similar to our research model, the reflective-formative-formative BMI construct is exogenous and the dependent variable—firm performance—is a reflective-reflective HCM; we draw in both cases on the repeated indicators approach. It assigns all indicators of the lower-order constructs to the measurement model of the HOC (Lohmöller 1989 ; Wold 1982 ) and can also be applied to third-order HCM (e.g., Wetzels et al. 2009 ). Nevertheless, additional technical considerations need to be considered. First, the indicators at the lower level should not vary strongly when it comes to their number (Becker et al. 2012 ); second, the measurement models of the HOCs needs to be evaluated in terms of the relationship with their lower-order components (LOC); third, this necessitates additional attention to the collinearity, significance, and relevance of the relationships between the HOCs and LOCs (Hair et al. 2018 ). We now proceed to evaluate the structural and the measurement models.
5.1 Evaluation of the Measurement Model
In a first step, we evaluated the hierarchical measurement models of the constructs under investigation, thereby following the criteria and procedure pointed out by Hair et al. ( 2017 ). The eight first-order constructs of the molar higher-order construct BMI, as well as the three first-order constructs of the dependent variable firm performance, all have a reflective nature, which means that internal consistency reliability, convergent validity, and discriminant validity need to be evaluated (Hair et al. 2017 ). In terms of internal consistency and reliability, composite reliability values all exceed the threshold of 0.70 (Henseler et al. 2009 ) and the same applies for the Cronbach’s alpha values, which are all above 0.70. When it comes to convergent validity, all the indicator loadings of the reflective constructs are well above the threshold value of 0.70 and further analysis shows that the indicator loadings squared are above 0.50 (Hair et al. 2017 ). The average variance extracted values are all above the required minimum level of 0.50 (Fornell and Larcker 1981 ). In terms of discriminant validity, the values of the heterotrait-monotrait ratio of correlations (HTMT)—with the highest one turning out to be 0.862—are also below the threshold of 0.9 (Gold et al. 2001 ; Teo et al. 2008 ). As stated above, in terms of HOCs, the measurement models are evaluated according to their relationship with its lower-order components, thereby accounting for the same evaluation criteria and thresholds. Consequently, the HOC firm performance, which is likewise a reflective construct, was assessed and the above stated measurement criteria were all met. However, in reflective-reflective or formative-reflective HCMs conceptual and empirical redundancies are expected and, hence, discriminant validity between HOCs and LOCs is of no relevance (Hair et al. 2018 ). In a next step, the measurement criteria of the second-level constructs—that is, the four business model elements, as well as the first-level construct BMI itself, which are all operationalized as formative constructs—are assessed in terms of their relationships with their corresponding LOCs. Consequently, the measurements models are evaluated with regards to potential collinearity issues, as well as the significance and relevance of formative indicators (Chin 2010 ). In terms of collinearity, the VIFs were assessed (Cassel et al. 1999 ; Diamantopoulos and Winklhofer 2001 ) and found to be uniformly below the threshold value of 5 (Hair et al. 2013 ). We, therefore, conclude that collinearity is not an issue in this model. Next we analyzed the outer weights for their significance and relevance by applying a complete bootstrapping procedure using 5000 bootstraps (Hair et al. 2017 ). In terms of significance levels, we found that all the formative constructs’ relationships with their LOCs are significant at a 1% level. All criteria in terms of formative measurement models are therefore met. Appendices 1–4 and Fig. 2 give an overview of the measurement models and their indicators. Considering the results of all the reflective and formative constructs, we found that they exhibit satisfactory levels of quality. Therefore, we could proceed with the evaluation of the structural model.
Results of PLS-SEM
5.2 Evaluation of the Structural Model
The main research goal of this study was to empirically examine the relationship between BMI and firm performance. We, therefore, collected primary data and used SmartPLS 3 (Ringle et al. 2015 ) to test the hypotheses by examining the path coefficients and significances of the structural model. Fig. 2 illustrates the results of the structural model. Again, we followed the procedure outlined by Hair et al. ( 2017 ). With respect to the inner model, no VIF value exceeded the threshold of 5—in fact, the highest value turned out to be 2.441, thereby indicating that multicollinearity should not be a concern. The R‑squared value in the structural model for the relationship between BMI and firm performance turned out to be 0.247 with an effect size f 2 of 0.159. The blindfolding procedure resulted in Q‑squared values above 0 for all endogenous constructs, thereby indicating predictive relevance. BMI has a positive effect on firm performance ( β = 0.336, p < 0.001), thereby confirming Hypothesis 1. Furthermore, the life cycle stage of a firm negatively moderates the positive relationship of BMI with firm performance ( β = −0.154, p < 0.01), thereby supporting Hypothesis 2. We also studied the moderating relationship by using a separate interaction analysis. Thereby, we used latent variable scores and standardized the predictors prior to the analysis to account for multicollinearity (Aiken and West 1991 ). Table 4 and Fig. 3 show the results of the analysis. The two-way interaction of BMI and life cycle stage is significant and negative ( β = −0.483, p = 0.019).
Illustration of the Moderating Effect of Life Cycle Stages
In a next step, we tested for differences between product- and service-oriented BMIs and we again conducted two separate interaction analyses, one for product-oriented and another for service-oriented firms. The interaction analysis shows that product- and service-oriented ventures exhibit different performance implications across life cycle stages. However, as Table 5 and Fig. 4 indicate, the difference between early and late stages is not statistically significant in product-oriented ventures ( β = −0.435, n. s.) and therefore, Hypotheses 3a is not supported. On the contrary, in the case of service-oriented ventures, the performance effect of BMI is significantly higher in the earlier than in the later stages ( β = −0.529, p = 0.025), thereby providing support for Hypotheses 3b.
Illustration of Moderating Effects of Life Cycle Stages in Different Firm Types. a Product-oriented firms. b Service-oriented firms
5.3 Additional Analysis
In addition to our research framework, we have calculated an additional analysis as we wanted to determine the relative importance of each element of BMI in early and late life cycle stages. It has been noted that the often stated, yet vaguely described relationship between BMI and performance relationship is difficult to study, due to its complexity (Foss and Saebi 2017 ). This complexity stems from the “multiple complex links” (p. 212) between the business model elements and the performance implications that are not only intertwined, but also unfold differently over time. In addition, previous studies have also identified that elements of BMI have a different impact on performance (Schneider et al. 2013 ). In order to determine the innovation contribution of each business model element in each life cycle stage, we conducted four separate interaction analyses. Table 6 and Fig. 5 show the empirical results and graphic illustration of how each BMI element takes effect on performance in different life cycle stages.
Illustration of Moderating Effects of Life Cycle Stages in Elements. a Value Offering Innovation. b Internal Value Creation Innovation. c External Value Creation Innovation. d Financial Architecture Innovation
6.1 theoretical implications.
Academic research has, thus far, claimed that BMI is a strong driver of firm performance (Foss and Saebi 2017 ). However, an important, but largely overlooked research issue is if and to which extent BMI differs in firm performance across different life cycle stages, namely the early and late stages of a venture’s life. Hence, this study strives to add to BMI and life cycle theory by making the following contributions: (1) Our research confirms recent findings on the positive impact of BMI on firm performance, (2) it provides first empirical evidence about the moderating role of life cycle stages on the relationship between positive BMI and performance, and (3) it investigates for the first time how this relationship differs for product- and service-oriented firms.
First, this study found evidence for the hypothesized positive relationship between BMI and firm performance. This finding is in line with previous research in the academic realm (Brettel et al. 2012 ; Cucculelli and Bettinelli 2015 ; Futterer et al. 2018 ; Kim and Min 2015 ; Zott and Amit 2007 ). We contribute to current literature by confirming that more innovation in business models will, indeed, result in higher performance (Foss and Saebi 2017 ).
Second, the life cycle stage’s moderation of a venture brings an important factor into the discussion about the performance advantages of BMI. We thereby extend and challenge extant literature on the outcomes of BMI (Cucculelli and Bettinelli 2015 ; Zott and Amit 2007 ) by providing—for the first time, to the best of our knowledge—empirical evidence for the impact of BMI on firm performance in early and late life cycle stages. More specifically, the more innovative a business model becomes, the higher are the performance implications for ventures in their earlier stages. In accordance with these results, previous studies have demonstrated that BMI leads to firm performance in the earlier stages of entrepreneurial firms (Brettel et al. 2012 ; Cucculelli and Bettinelli 2015 ; Zott and Amit 2007 ). Perhaps the most striking finding is that in the cases of more established ventures; an increase in BMI does not automatically lead to higher rates of performance. This result has not yet been previously described and extends current research on the outcomes of BMI that assumes a positive relationship (Foss and Saebi 2017 ). Although anecdotal evidence shows that established companies like Xerox, Gilette, or Apple successfully innovated their business model and were rewarded with higher performance rates than before. Our findings suggests that the performance implications are not tied to the innovativeness of the business model. An explanation for this phenomenon might be that BMI in firms in their later life cycle phases is a positive trigger in the beginning, but that the value creation and capture mechanisms do stem from their existing assets rather from the innovativeness of the BMI itself. In contrast to more established firms, newly founded ventures often operate in niche markets, serve other customers than incumbents, employ novel resources, and are in a situation where they can play actively with their new business models (Tucci and Massa 2013 ). Further, firms in their early stages are highly centralized in their founder (Chandler and Hanks 1994 ), who is able to monitor and steer the BMI process. A comparison of these results with those of other studies confirms that companies with a high level of control have a higher innovation-input-output ratio (e.g., Duran et al. 2016 ). In similar vein, compared to their later stages, new ventures are less formalized and departmentalized in their earlier stages (Hanks et al. 1993 ) and are, therefore, much more flexible (Jaworski and Kohli 1993 ). After surviving the liability of newness, the business model of firms in their early stages is the central asset for creating and capturing value, and ultimately to generate performance implications. By providing empirical evidence, we extend the life cycle theory with the phenomenon of BMI and conclude that relying only on the innovativeness of the implemented business model in the later stage of a venture’s life, will not enhance organizational performance.
Third, our results deliver first empirical evidence on how the interaction effect of life cycle stages differs in the case of product- and service-oriented firms. We found contradictory results. In the case of service-oriented ventures, a more innovative business model especially pays off in early stages, but performance declines during the later stages like we expected. However, in the case of product-oriented ventures, our results show that BMI is important in both stages with no statistical difference between early and late stages. A possible explanation might be that in the event of market acceptance, a venture’s main goal is to establish itself in the market (Abernathy and Utterback 1982 ; Moore and Tushman 1982 ) and in later stages, ventures aim to maintain their market position by developing a second generation of their product (Kazanjian 1988 ; Moore and Tushman 1982 ). In both cases, an innovative business model designed around their focal products might help leverage their customer adoption. Besides being the first study to investigate how the relationship between BMI and firm performance differs for product- and service-oriented firms, we also extend existing knowledge with regards to the life cycle theory.
Fourth, when it comes to the individual contribution of business model elements in each life cycle, our findings of the additional analysis are mostly in line with the main analysis. More specifically, the innovation of all business model elements pays off more in a venture’s early life than in its later stages; this means that ventures in their early stages need to have greater pressure for BMI, ultimately leading to firm performance. However, in the event of value offering, as well as internal and external value creation, the innovation of the elements in later stages leads to smaller performance implications. A possible explanation might be that firms in their later stages have already gained market acceptance of their offering (Kazanjian 1988 ; Moore and Tushman 1982 ), they have gained a status of formalization with efficient and implemented processes (Churchill and Lewis 1983 ; Gaibraith 1982 ), and they have established stable relationships with their partners and customers (Masurel and Van Montfort 2006 ). After gaining stability and reducing uncertainty for the first time, a change in these offerings, processes, and relationships might lead to confusion and inefficiencies, and ultimately to decreased performance. However, an innovation of the financial architecture element contributes to venture performance in both stages. This is in accordance with current research. In the BMI domain, prior research has shown that efficiency-centered business models, that is, business models designed to reduce transaction costs, enhance firm performance (Zott and Amit 2007 , 2008 ), especially in later stages of organizational life (Brettel et al. 2012 ). By first investigating how business model elements impact on firm performance in different life cycle stages, we extend existing knowledge by adding a more fine-grained analysis, which has only been marginally investigated thus far (Schneider and Spieth 2014 ). Thereby, we laid the groundwork for disentangling the business model construct into its sub-elements with a certain emphasis on the different life cycle stages of ventures.
6.2 Managerial Implications
These findings may help managers and entrepreneurs to understand how to leverage a new business model to success. In line with earlier studies (Cucculelli and Bettinelli 2015 ; Zott and Amit 2007 ), research has found that BMI is an important predictor of performance implications in organizations. Our findings show that a more innovative business model makes a stronger contribution toward organizational performance than a less innovative one. A key policy priority for managers should, therefore, be to design and implement an innovative business model. Second, our results show that especially in the early stages of an organization’s life cycle, an innovative business model entails a unique selling point and is a key asset in a successful growth process. The more a venture grows, the less important an innovative business model becomes as other factors gain in importance. Within this context, this study shows that the individual life cycle stage of an organization has an important impact on the performance outcomes of BMI and should, therefore, be carefully assessed. Third, our results point out that managers of organizations have to take their firm type—either a product-oriented or a service-oriented venture—into account. According to our findings, especially in the earlier stages, a service-oriented venture has, to a certain extent, emphasize the design and development of a rather innovative business model. In later stages, however, a very innovative business model might lead to decreased performance. In case of product-oriented ventures, an innovative business model is highly important in both stages. In sum: We advise managers and entrepreneurs to not only carefully assess the innovativeness of their ventures’ business models, as well as its elements, by, for example, using the measurement inventory of Futterer et al. ( 2018 ), but to also assess, respectively, each life cycle stage the venture is currently passing through by using the framework of Kazanjian ( 1988 ). Furthermore, the venture’s main offering, which is either a service or a product, must be taken into account for the best possible organizational performance outcome.
7 Limitations and Avenues for Future Research
The findings derived from this study make several contributions to the current literature. However, as with any study, this one also has its limitations. First, we conducted a cross-sectional investigation of the relationship between BMI and performance in the new ventures domain to empirically examine the positive implications. Although using cross-sectional data is a common approach in BMI research (Futterer et al. 2018 ), such approach might suffer from several limitations. The most important one for our investigation might be tied to a potential delay of performance effects of BMI. While we did account for potential confounding effects due to such delay within our measurements, future research might replicate our findings employing a longitudinal sample to completely rule out any confounding effect in this regard by establishing true causality. Second, both the independent and dependent variable were assessed by the same instrument, i.e., survey, and respondent. To minimize potential problems due to common method bias, we applied procedural and statistical measures to rule out common method variance as effectively as possible. However, again replicating our findings by a longitudinal study with secondary data might provide additional support for our results. Furthermore, in terms of the moderating role of a firm’s life cycle stage, a longitudinal design might provide additional insights and a more fine-grained analysis of the complex mechanisms of BMI and the growth process of a firm. Third, in similar vein, we split our dataset into two stages of a venture’s life, namely early and late stages. Although it has provided initial insights into the moderating role of lifecycle stages on firm performance during BMI, it also comes with a lack of information. We therefore encourage scholars to examine the growth process of a new venture in each stage to link their individual growth pattern with the relationship between BMI and performance. A more fine-grained analysis might shed more light on the prominent relationship and produces viable insights in the underlying mechanism on how performance effects unfold over time. Forth, our study was not able to account for the amount of structural change brought about by the innovation of a business model in an established company. Although we split our dataset into early and late stages, the latter stage does not resemble established companies, since our dataset entails only young and older new ventures, but not established companies. When it comes to directions for future research, further studies might explore the relationship investigated in established companies with a special emphasis on the stages of maturity, diversification, and decline. This might result in worthwhile contributions to research on the life cycle theory and BMI. Fifth, an arguable weakness of this study is the founders’ self-evaluation of performance as a dependent variable, which makes these findings less generalizable. Although new ventures do not need to publicize their financial data (Wang et al. 2017 ) and surveying the key informants of the new ventures is a common approach (Anderson and Eshima 2013 ; Kraus et al. 2012 ), future research might work with secondary data, such as the amount of investments a venture receives during its growth process as an indicator for third-party’s trust in its potential to validate and strengthen our findings.
The VHB-JOURQUAL Rating is a journal ranking of the German scientific community. The scientific quality of a journal is defined as the extent to which the journal in question advances business administration as a scientific discipline. The categories A and B in this ranking do largely correspond with the categories 4 and 3 in the ABS journal ranking.
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Correspondence to Sven Heidenreich .
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E. Freisinger, S. Heidenreich, P. Spieth and C. Landau declare that they have no competing interests.
This paper was originally submitted and independently peer-reviewed at Business Research , one of SBUR’s predecessor journals. It has been accepted by the same Editor-in-Chief for publication in the successor journal SBUR.
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Freisinger, E., Heidenreich, S., Landau, C. et al. Business Model Innovation Through the Lens of Time: An Empirical Study of Performance Implications Across Venture Life Cycles. Schmalenbach J Bus Res 73 , 339–380 (2021). https://doi.org/10.1007/s41471-021-00116-6
Accepted : 02 September 2021
Published : 28 October 2021
Issue Date : December 2021
DOI : https://doi.org/10.1007/s41471-021-00116-6
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