Yes ... And: Making Lean Startup Work in Large Organizations.
Why is this? In short, it's a problem of context. Steve Blank, one of the founders of the Lean Startup movement, said that his first big "Aha!" was the realization that startups are not just smaller versions of large companies (Blank and Euchner 2018). Before Lean Startup, entrepreneurs and venture capitalists tried to manage startups using the same tools that had worked for established enterprises--principally the business plan, the P&L, and Stage-Gate product development practices. Blank and his collaborators realized that something different was needed to develop products under the conditions of extreme uncertainty that characterize the startup world, including uncertainty about the market, uncertainty about customers' emerging needs, uncertainty about technology, and uncertainty about costs, among others (Ries 2011). Lean Startup was designed to help startups deal with these risks by creating learning organizations that could operate productively under conditions of extreme uncertainty.
Just as a startup is not a smaller version of a large company, however, an internal venture within a large company is not just a startup that happens to be hosted by an existing enterprise. The context of the corporate environment makes all the difference. Identifying the primary differences between startups and new ventures operating inside a corporation can help companies understand how to make Lean Startup work for them. These differences--which can be significant--can be managed, and even leveraged for success, if they are approached consciously.
Lean Startup Practices and Principles
To understand the challenges of implementing Lean Startup in large organizations, it is important to start with a review of its key principles (Blank 2013; Blank and Euchner 2018; Ries 2011, 2017; Ries and Euchner 2013).
The first three principles of Lean Startup--lean learning loops, minimum viable product (MVP), and pivot or persist--address how Lean Startup teams work. The second three principles define the three key hypotheses the team is seeking to validate: the value hypothesis, the business model hypothesis, and the growth hypothesis.
Experimentation is the heart of the Lean Startup approach. That experimentation takes place via lean learning loops (Figure 1), the basic construct of the method. Lean learning loops are designed in essentially the same way as experiments in the laboratory sciences are designed. In a lean learning loop, the team:
* Frames a hypothesis.
* Designs an experiment to test the hypothesis.
* Conducts the experiment.
* Reviews the results to confirm or disconfirm the hypothesis and decides on next steps based on that analysis.
The basis for these experiments is often some form of prototype. The Lean Startup method, which originated in the software industry, originally focused on experiments with the Minimum Viable Product, which is the first product that is useful to and usable by customers. The MVP usually has a very focused feature set and is designed to prove that the product concept is attractive to customers and can succeed in the market. As Lean Startup has been applied to physical products, innovation teams have borrowed other types of prototypes from the design world, many of which are designed to test a concept or feature before a product is marketed. Thus, in the manufacturing world, prototypes may also include:
* Probes--Low-fidelity, nonfunctioning prototypes, such as storyboards or foam-core models, designed to provoke a response to an idea and validate or invalidate a need.
* Technical prototypes--Prototypes designed to demonstrate specific functional capabilities.
* Concept prototypes--Nonfunctioning or "Wizard of Oz" prototypes to assess whether the proposed solution would work in the customer's world.
* Business prototypes--Small-scale tests of an element of the business model, designed to take risk out of the business.
After each experiment, the team has to make a decision: to pivot or persist. To persist means to continue learning along the lines of the current plan; to pivot means to rethink a major element of the plan, such as the channel or an important aspect of the product. This discipline--to let data drive the pivot or persist decision--is at the heart of the Lean Startup method.
The pivot-or-persist principle is closely related to another Lean Startup principle, innovation accounting. Innovation accounting is a way of tracking progress--not against defined milestones, but against the learning and risk reduction needed to make a venture viable. In essence, in Lean Startup, the assumptions that need to be true for the product to be successful are tested, one at a time, via lean learning loops and prototyping, and the results of the experiments are tracked over time, via tools that allow the necessary innovation accounting. A Kanban board is one good way to track the status of the assumptions. Whatever method is used, it is important to clearly associate the evidence gathered from an experiment with the hypothesis (or hypotheses) that it validates or invalidates.
The Lean Startup learning process is designed to develop and test three key hypotheses for a proposed product or service: the value hypothesis, the business model hypothesis, and the growth hypothesis (Figure 2).
1. The value hypothesis captures the fit between your product or service concept and the market. The process of testing the value hypothesis goes by several names: Steve Blank calls the process customer development (Blank 2013); the Lean Product community talks about product-market fit (Olson 2015); Eric Ries uses value hypothesis (Ries 2011); and in the design community, the term of art is customer value proposition (Lanning 1998). Whatever it is called, testing the value hypothesis or identifying product-market fit is very customer-intensive. It begins with a hypothesis about a customer need or a definition of what Clay Christensen and Michael Raynor (2003) call the Job-to-be-Done, which is tested with a series of prototypes. The initial prototype is usually very simple--a storyboard, for example. Later versions are more complex and complete, at least from the customer's perspective; a "Wizard of Oz" prototype, for example, seems to the user to work but is actually manipulated from behind the scenes. This process eventually leads to a prototype the user can actually use, the MVP. This testing and iteration with prototypes provides assurance that there is a customer need and that the product does meet it--that is, that the product provides value.
2. The business model hypothesis is focused on identifying the business model needed for the venture to capture value from the concept (the customer value of which was validated in the testing of the value hypothesis). For a startup, this means developing the company's initial business model. For established companies, the considerations can be more complex. A truly new idea often will not fit nicely into an existing business model; trying to force-fit a new concept into the company's dominant business model is a common reason for failure--either failure to create a new business or failure to capture a fair share of the value created. Thus, even in existing organizations, new ventures need to develop and test new business models.
Business model experiments should begin with a coherent definition of the proposed business model. In developing this definition, product developers can look to business model archetypes and to models that have worked in other industries (see, for instance, Slywotzky 2002). The process of testing a business model is similar to that for testing the value hypothesis--design a prototype to test a hypothesis, do an experiment, interpret the results, and decide how to proceed. Ganguly and Euchner (2018) offer a blueprint for effective business experiments. The elements of the model should be tested separately. You may want to test channel effectiveness, for example, or the costs of supporting the product in the field; each of these should be the subject of a separate experiment, if possible.
3. The growth hypothesis posits a model for scaling the business. In startups, scale often happens organically: as sales increase, the startup configures to manage them and seeks investment to accelerate growth. In established corporations, on the other hand, the growth hypothesis is often developed and validated in a distinct step: small-scale incubation. Incubation has the advantage of testing the whole proposition at low risk. It validates that customers will buy the offering at a price sufficient to sustain the business and therefore that the business as a whole can be made profitable. Once profitability has been demonstrated, there are many options for achieving scale. In a large company, the options may include acquisitions, reorganization of parts of the business, or substantial organic investment in a new division.
Growth hypotheses can be threatening to the core business. The fear, generally, is a loss of control: that the new venture will run off in some uncontrolled direction, hurt the core business in some way, and sap resources along the way. The growth hypothesis can be a primary source of tension between the new venture and the core business.
The principles and practices of Lean Startup have been tested in thousands of startups (Blank and Euchner 2018). Although their application in established businesses has been problematic, they do not need to be abandoned in those settings. In fact, they are very effective in reducing the conditions of extreme uncertainty in which internal ventures operate. But they need to be complemented by additional practices that address the specific challenges of the corporate setting. Those practices are best approached with conscious consideration of the specific challenges presented by the intersection of Lean Startup principles and the large organization context.
Yes, And ...
Both startups and new ventures inside corporations must manage similar conditions of extreme uncertainty: Will the market for the new offering develop? How quickly? Can the product be delivered at an attractive cost? Will people be willing to pay for it? Will the new technology work? What new competitors might disrupt the business? These are market uncertainties, and they are the province of entrepreneurs. The Lean Startup methodology is designed to reduce these risks systematically, quickly, and at low cost.
A venture inside a corporation must deal not only with market risks but also with internal risks that startups do not face. These risks come in three general categories: personal risks, risks to the performance engine, and risks to the corporation itself.
* Personal risks are the career risks taken by innovators who associate themselves with, champion, or spend time on a venture that may not succeed--one that may even make enemies in the core business. Most corporate environments are far less tolerant of a good failure than a robust startup ecosystem is, whatever the declarations of executives to the contrary. For an individual, the career risk also includes the opportunity cost of working on a new venture rather than in a mainstream career role.
* Risks to the performance engine are risks that core functions confront in their support of innovation. These functions include sales, intellectual property law, liability law, procurement, IT, engineering, and contracts. Support of the new venture may distract people in these functions from their core objectives. It may also result in errors as the functions struggle to deal with issues very different from those they confront in their support of the core business.
* Risks to the corporation operate at a higher level. They are the (perceived) risks that the new venture will cannibalize the existing business and sap resources, both financial and human, that the core business needs. There is also a risk with any new venture that it will drag the business away from its successful core.
To succeed, internal ventures that seek to use the practices of the Lean Startup movement must complement those practices with others peculiar to the corporate context. The differences between the startup world and the corporate context need to be managed in addition to and in coordination with the Lean Startup method. The issues themselves are not new--in many cases, they have been studied in isolation by academicians and other thought leaders who have focused on corporate innovation--but they can be exacerbated by the practices that make up the Lean Startup method.
Complementary Practices for Lean Startup in Large Organizations
Lean Startup practices solve a major problem (taking the risks out of a new venture), but they do so at a cost. Implementing these practices within a corporate setting can provoke corporate antibodies. The pressures of organizational life can cause people to act in a way that inhibits progress of the innovation team. These natural tendencies need to be identified and managed.
One useful way to approach this dilemma is to look at the sources of resistance through the lens of the Lean Startup practices themselves. Although the relationship between Lean Startup approaches and internal resistance is not one-to-one, each practice does induce specific kinds of resistance and internal challenges (Table 1). The first three practices of the Lean Startup, which relate to the daily work of the innovation team, create concerns for the day-to-day operations of the business. The next three deal with a more fundamental issue--the compatibility of the venture with its host corporation. Conscious implementation of specific practices can help resolve the dilemma.
1. Innovation Stage-Gates: Reconciling Lean Learning Loops with the Need to Demonstrate Discipline
The Lean Startup methodology is somewhat chaotic. It works, when it works well, because the chaos is managed through a learning agenda. Over the course of a monthly sprint, many things can change: the feature set of an MVP, the target customer, the channel to market, the revenue model. To executives used to evaluating whether or not a project is on plan and on budget, this constant change can be unsettling, even with frequent reviews and good documentation of the decisions made. Executive leadership teams often want a more linear assessment of progress.
The use of an innovation Stage-Gate process with clear intermediate deliverables and a reasonable estimate of timeframes for creating them can provide the necessary framework (Figure 3). In an innovation Stage-Gate system, the process within the stages is agile, dynamic, and a bit chaotic; at the level of the gate deliverable, however, it is more defined and more predictable. An innovation Stage-Gate is analogous to the hybrid Stage-Gates now emerging in new product development (see, for instance, Cooper and Sommer 2018).
Introducing an innovation Stage-Gate process requires separating in time some of the activities that might be undertaken simultaneously in the Lean Startup approach (Ganguly and Euchner 2018). Customer insight, and the development of the customer value proposition, can be usefully separated from creation of the business model, for example. Similarly, business model development can be separated from in-market incubation of the concept, reducing the risks of entering the market. Finally, the decision to scale the venture can be separated from the decision to incubate it.
A stage-and-gate process may strike some as antithetical to the Lean Startup approach--and even to innovation itself. It is, however, a critical element in matching the Lean Startup to other business processes in large organizations. The stage-and-gate structure provides a clear sense of progress, clear points at which investment decisions can be made, and a space where executives can learn, over time, about a new market and its risks and promise.
2. Graduated Engagement: Developing MVPs in the Context of the Performance Engine
Every established company has what Vijay Govindarajan and Chris Trimble call the "performance engine" (Govindarajan and Trimble 2010)--the collection of functions, processes, and resources that have been optimized over time to support the profitability of the core business. The people who manage the performance engine have objectives, internal client expectations, and methods of operating that can be disrupted by an innovation team--especially one focused on breakthrough innovation. Nevertheless, the internal venture needs to leverage the skills, resources, and imprimatur of the internal functions.
How can an organization resolve this paradox to allow the performance engine and the venture to coexist and even support each other? Some companies create an entirely independent innovation entity, with its own HR, IT, procurement, legal, and engineering functions. This approach is expensive and, in many cases, impractical. Others attempt to use the existing functions, together with pressure from the top, to get things done. This works well until it wears thin, and then it tends to collapse.
There is a third way, one that engages the performance engine throughout the innovation process in a transparent but graduated way. In essence, core functions provide basic support during the exploratory parts of the process and only become more engaged in as the concept advances. Decision rights are explicitly negotiated for each stage in the Innovation Stage-Gate process. The various functions provide the support needed, using budgeted funds allocated to that purpose and provided by the innovation team. The innovation function also assumes the risk of doing things differently and more quickly; it is the responsibility of the functions simply to highlight issues they anticipate and to make their risk explicit. When the venture moves into incubation (Figure 4), the functions become more active in assuring (appropriate) compliance with established practices.
Graduated engagement assures that existing standards and ways of working, which often seem very constraining for those doing something new, will not slow down the innovation team as the business is being developed. It also assures that the venture will comply with corporate standards once it is launched. Implementing this kind of ramped engagement takes time, planning, open communication, and compromise, but it enables an internal venture to move quickly and still leverage corporate knowledge and resources--one of the primary advantages corporate ventures have over startups.
3. Stochastic Models: Reconciling Pivot Decisions with the Need to Demonstrate Progress
Lean Startup is an evidence-based practice. The goal is to learn about the viability and desirability of your business concept from the real world. Experiments provide evidence to support or invalidate a range of hypotheses about a concept's viability. Difficult decisions must often be made based on the evidence. Some of these decisions may cause a team to take a big step backwards. These moments can be challenging in the corporate context, where the expectation is often that a team will make a plan and then make steady progress in executing it.
In Lean Startup, results from business experiments drive revisions to the plan; those revisions may call for a step backward. The learning--the motivation for evolving the plan--must be made visible or the entire process can seem chaotic and quixotic. One tool for achieving that visibility is a stochastic model of the business's pro forma, which can be represented as a simple P&L statement with a range of values for the key line items. The range reflects the uncertainty around that line item at that point in time. Running the overall stochastic model gives the distribution of expected profit based on what is known at that time. The goal of business experiments is to narrow this distribution and to develop a high likelihood of a profitable business.
The pro forma P&L and the stochastic model based on it clarify the current state of the business. Creating the model forces clarity about the critical elements of the business and the sources of uncertainty. Using it makes clear the progress of the concept over time. Business experiments can then be targeted to the areas of most uncertainty, which may not be those of most interest to the innovation team. With such a model, a pivot does not seem like an undisciplined change of direction; rather, it reflects a disciplined change in direction driven by data that show that such a move is required to achieve profitability.
4. Opportunity Spaces: The Value Hypothesis and the Need to Create Strategic Alignment
Ongoing corporations have strategies, whether they are explicitly stated or implicitly enacted. Any new venture must align with these strategies or with an explicitly espoused growth strategy--even if the CEO says that there should be no bounds on the innovation team, that he or she will invest in any truly good new venture. If executives cannot see the connection to a larger objective, if they do not invest the time to understand the new domain in sufficient depth to make decisions with confidence, if the new venture is seen as diverting resources from the existing corporate strategy rather than moving it forward, then investment will not flow.
One way of achieving this alignment is by creating sanctioned opportunity spaces. The opportunity spaces defined will likely build on trends that are creating new possibilities combined with innovative use of the corporation's assets--including its customer base, brand, service networks, and core technologies. Corporate assets can often be combined with market opportunities in a way that provides unique advantage.
Shaping the opportunity space within which a corporation will play and making it explicit is difficult work. It requires thinking through alternative spaces, understanding their potential for the company, and being realistic about corporate assets. This is not something that senior leaders can delegate. But once the opportunity space is sanctioned, it reduces the concern that the innovation initiative is going off in irrelevant or even destructive directions. Startups must also define their opportunity space, but they do not have to align it with an external strategy, as internal ventures must.
5. The Business Model Pyramid: The Business Model Hypothesis and the Need to Manage Internal Risks
A business model is a configuration of resources, assets, and processes designed to deliver a customer value proposition profitably. A good business model creates differentiation in the marketplace and has economic leverage--it gets stronger with scale. Over time, a company's business model is optimized; when it reaches this stage, the work of the functions is highly aligned with the core business model. Introducing a new business model is both costly and risky. It means going back to square one and learning anew how to drive profitability. A new business model can also present a threat to the performance engine, since it competes with the core business for resources, talent, and managerial attention.
When established businesses launch new business models, they confront two conflicting objectives. On the one hand, they seek to create a durable competitive advantage by leveraging the assets of the core business in the new venture; on the other hand, in order to minimize disruption of (and by) the core, they often organize to keep the new venture at arm's length from the operating units. Startups do not face this dilemma. They are discovering their business model; they do not have a dominant model to constrain (or support) them.
Business models that leverage assets and are compatible with a corporation's strategy can be systematically developed. Euchner and Ganguly (2014) have described a process that successively identifies and addresses risk, based on what they call the business model pyramid. Use of this model is helpful in managing internal resistance by making the risks (as well as the opportunity) explicit, and by creating clarity about the impact of the new venture on the core business.
6. Organizing for Growth: The Growth Hypothesis and the Need to Protect the New Venture
Organizational issues do not loom large when a venture inside a large company is small. Everyone involved does whatever is necessary for success. Resources are begged, borrowed, stolen, and cajoled into being. This is true for startups as well, although the sources of resources are different. As the venture matures, both startups and internal ventures need to manage a new set of challenges. In both cases, for example, the leadership may need to change as the venture enters the growth stage. The team must often be reshaped to take full advantage of the opportunity the venture has created.
An internal venture has an additional set of issues to address. When it was small, it could fly under the radar. As long as it was able to muster the resources it needed and the permissions required to operate, it was not challenged. But growth changes this balance. Suddenly, the new venture challenges the status quo in ways that were not visible when it was small. It may attract scarce budget, draw on scarce internal talent, and demand managerial time from the core business. The core often fights back (if it feels it has the political permission to do so). Moving the venture from incubation to scale must therefore be done carefully, especially if the business intends to leverage the assets of the core business.
Internal ventures fail when the balance is poor--when integration is too tight to accommodate differences in business models or when the separation is so complete that the parent venture confers no competitive advantage. Too tight an integration can mean that the new business is force-fit into the existing business model. The functions and routines and policies of the core are grafted onto the new venture, whether they support it or not. Too tight an integration can also lead to investment that is governed by normal corporate allocation processes, not by the opportunity the venture presents.
Full separation of the new venture and the core business brings other risks. The primary danger of full separation is that the assets of the core will not be available to help the venture create competitive advantage. Without these advantages, the new venture might as well be a startup.
Govindarajan and Trimble's (2010) model for achieving the needed balance between the core business and the new venture calls for structural separation together with explicit, negotiated relationships between the new venture and the core business functions. Applying Govindarajan and Trimble's model requires open discussion that is often difficult in a corporate context, as the organizational issue inevitably impinges on issues of power and budgets. It is helpful--perhaps essential--to have funds to incubate the business sequestered so that the question of organization is not fraught with budget issues.
There is another risk that must be balanced differently inside a corporation--the risk associated with the "bet to win." Once a venture has been brought to the point where it has proven to be attractive to customers, profitable, and scalable, a venture capitalist will often go all-in to win in the marketplace. The corporate investor, confronted with alternate investment paths, will often choose the path that minimizes the downside risk rather than the one that maximizes the venture's potential. This is understandable. It can be hard for a public company to explain to Wall Street a dip in earnings due to significant investment in a new and very different business. Executives may be emboldened and invest more aggressively in a new venture if the innovation team has implemented some of the practices recommended here to help the leadership team understand the opportunity and its risks.
The Lean Startup method has been demonstrated to work well, especially for startups and software companies. Successfully applying the method within established companies--especially industrial companies--has been problematic. This is due, in part, to the natural response of the organization to the elements of the Lean Startup method.
A number of practices have been effective in overcoming internal resistance to Lean Startup approaches and that have proven successful in the launch of new ventures within established companies. These practices, or similar practices that address the same underlying issues, need to be implemented to complement the deployment of Lean Startup. Both are necessary for the success of new ventures within large organizations.
Jim Euchner is editor-in-chief of Research-Technology Management and Honorary Professor at Aston University (UK). He previously held senior management positions in innovation leadership at Goodyear Tire and Rubber Company, Pitney Bowes, and Bell Atlantic. He holds BS and MS degrees in mechanical and aerospace engineering from Cornell and Princeton Universities, respectively, and an MBA from Southern Methodist University. He is author of a forthcoming book, Lean Startup in Large Organizations, to be published by Productivity Press. This paper is based on his talk at IRI's 2019 Annual Conference in Pittsburgh, PA. email@example.com
Published by Taylor & Francis. All rights reserved.
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Caption: FIGURE 1. Lean Startup's lean learning loop
Caption: FIGURE 2. The three key hypotheses of Lean Startup
Caption: FIGURE 3. An innovation Stage-Gate process
Caption: FIGURE 4. Graduated engagement
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