Take the Fuzzy Out of Innovation—The AVID Methodology Part 2

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This post is PART 2/2 of a paper entitled The AVID Methodology. Summary—A new contemporary approach is discussed that systematically resolves the risks associated with the fuzzy front-end of innovation. Startups and companies can create NEW products/services in less time with less risk at a significantly lower cost than conventional product development methods.

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A Better Way to Create New Products & Services

The AVID Methodology

The Agile Value Innovation Discovery (AVID)  methodology is a contemporary best practice for structuring the discovery phase for NEW product and service development (aka: the fuzzy front-end of innovation). The AVID methodology–

  • Is fast and flexible under conditions of uncertainty
  • Surfaces critical outputs via spiral iteration

Ideas and assumptions are empirically tested as they cycle through the discovery process.  Assumptions are systematically substituted with actual knowledge via discovery learning (i.e., de-risking).

Assumptions that fail the reality test generate new learning loops that are immediately cycled back into the next iteration of ideation and testing. Failed assumptions are viewed as “off target,” which becomes the impetus for continued discovery learning. The AVID methodology ensures that the critical outputs of the discovery phase define a profitable growth opportunity (that is, a best value solution).

Knowledge drives the discovery process (the spiral progression), not assumptions. When companies effectively resolve the risks associated with the discovery phase, the execution phase for new product development moves quickly and efficiently. Cost and time-to-market is drastically reduced.

Conventional methods like the phase/stage gate methodology have come under fire for being too rigid and planning-oriented for the front-end of innovation. Specifically, the phase/stage gate methodology is criticized for stifling creativity with too much structure, inhibiting learning, killing nascent innovation ideas that do not meet myopic financial criteria, and generally slowing things down to a crawl during the innovation process. I would suggest, however, that the problem is not the phase/stage methodology, per se. Rather, the problem is that the phase/stage gate methodology does not work well when uncertainty is high (the fuzzy front-end).

The phase/stage gate methodology emerged in the late 1980s as the best practice for structuring the development of new products/services in a business environment where uncertainty was low. That is, the phase/stage gate methodology was designed for incremental value enhancement projects where the critical outputs are line of sight.

The problem is that over the last few decades, uncertainty has increased dramatically. This uncertainty manifests itself in the discovery phase which exploits the weakness of the phase/stage gate methodology—namely, its inability to generate critical outputs under conditions of high uncertainty.

That said, there is no need to discount the part of the phase/stage gate methodology that is useful. Once a lucrative growth opportunity has been identified and innovation risks have been resolved in the discovery phase, the phase/stage methodology is the best practice for managing the development and launch (execution phase) of a new product/service.

When it comes to value innovation projects (new product/service development) where the critical outputs are obscured by uncertainty, the best way to increase the odds of success is to use a methodology better suited for the purpose. The Agile Value Innovation Discovery (AVID) methodology effectively structures the discovery phase for value innovation projects where uncertainty obscures the critical outputs.

Since the focus of AVID is solely on the discovery phase, AVID can be used on the front-end of a phase/stage gate methodology. AVID helps teams to identify the best growth opportunities and to resolve innovation risks prior to the development phase. Further, using the AVID methodology significantly decreases the time to market for a new product/service by compressing both the discovery and execution phases.

This is possible for two reasons. First, the agility of the AVID methodology enables teams to move through the discovery phase much faster and with much more precision than the conventional phase/stage gate methodology. Second, the testing and validation steps of the phase/stage gate methodology along with the subsequent decision gate (gate 5) can be eliminated because a solution design has already been empirically validated by the AVID methodology in the discovery phase. Removing these steps significantly compresses the execution phase (see figures below), thereby reducing the costs associated with this phase.

Execution goes much faster and more smoothly because execution teams can work in parallel with one another — each receives execution hand-offs from the discovery phase that make the critical outputs actionable for them. That is, various management/administrative functions, product development/engineering, sales and marketing, and operational departments can all be working on their part of the execution plan at the same time. Thus, AVID and a streamlined phase/stage gate component decrease the time to market for new products/services by compressing the total lead time of the process.

In summary, using AVID on the front-end of a traditional phase/stage gate methodology eliminates many of the steps and decision gates in the execution phase, dramatically reducing the risks, costs, and time-to-market for developing new products/services.

A great many companies do not use a rigorous and comprehensive methodology for systematically structuring the discovery phase of innovation. Instead, they use piecemeal methods and tools that fail to address all the critical aspects of the discovery phase. The result of such an ad hoc approach is the selection of fictitious or marginal growth opportunities where innovation risks go unresolved as the project moves into the execution phase.

Alternatively, the AVID methodology offers companies an orderly and repeatable best practice for managing the discovery process. The effective use of the AVID methodology will dramatically increase the chances that a new product/service innovation will succeed. Ultimately, AVID enables companies to systematically create profitable growth engines in less time and with less risk.

AVID is ideal for companies of all sizes that want to develop innovative products and services that will help the company achieve its strategic growth objective. The input into the AVID methodology is a growth target for a yet-to-be identified new product/service. The growth target specifies the desired amount of net profit that a new product/service needs to generate over some time period to support the company’s strategic growth plan.

The AVID methodology is the best practice for identifying a new product/service that is capable of achieving this growth target. Specifically, the AVID methodology delivers:

  • A new product/service capable of achieving a desired growth target
  • A business model that is capable of creating and delivering a compelling value proposition to customers while generating the required net profit for the company
  • An optimal product/service design that is capable of fulfilling the customer value proposition via the business model.

All assumptions associated with the critical outputs are validated via empirical testing. The validation of assumptions resolves all innovation risks prior to the execution phase. The final deliverable of the AVID methodology includes execution strategies for implementing the critical outputs in the execution phase.

AVID is Informed by Other Innovation Technologies

Over the years, a variety of innovation theories, concepts, principles, methods, tools, and techniques have been introduced that can be very helpful in the discovery phase. Collectively, I call these the core innovation technologies (see table below). Each of these innovation technologies focuses on a certain aspect of innovation discovery or enables a specific approach to innovation. While some of the core innovation technologies cover more ground than others, all of them are limited to specific contexts, domains, or circumstances of innovation.

The problem is that even though the core innovation technologies are very helpful in the innovation process, using one or a combination of these technologies is generally not sufficient to produce a successful innovation. Innovation projects can fail because teams miss or neglect critical aspects of the discovery phase. By doing so, they unknowingly increase the risk of their value innovation projects, which is not realized until it’s too late.

For example, Blue Ocean Strategy offers effective concepts, methods, and tools to help companies identify lucrative growth opportunities in new markets. However, Blue Ocean Strategy does not address the specifics of how to design a good product/service, business model structure and dynamics, assumption testing procedures, operational execution, ecosystem risks, and other things.

Disruptive Innovation offers powerful strategies for driving new products/services into markets without eliciting incumbent response. Yet disruptive Innovation suffers from the same gaps as Blue Ocean Strategy.

The Customer Development Model and the Lean Startup methodologies are great for startups, but are less useful for established companies. Open Services Innovation focuses on the flexible sourcing of the raw ingredients of innovation but does not deal with other important aspects of the innovation process. Design Thinking offers a great creative process for innovating via rapid prototyping, but it ignores many other aspects of creating customer demand.

Discovery-driven Innovation provides powerful innovation management methods, but it has little to do with the actual innovation process itself. In short, every innovation technology has its strengths within a certain area/context of innovation, but none of them address all the critical aspects of the discovery phase. Critical aspects of the discovery phase that are not effectively dealt with will significantly increase the risk of innovation failure.

The Agile Value Innovation Discovery (AVID) methodology is not a new innovation technology, per se. Rather, it is a composite of all the aforementioned core innovation technologies. This enables companies to leverage any and all the innovation technologies that are useful during the discovery phase. In fact, the innovation technologies provide the means of executing steps in the AVID methodology. Going forward, I refer to an innovation technology as a “lens” and/or a tool. A lens provides a conceptual/theoretical view of a particular aspect of innovation. A tool structures the activity associated with executing steps.

The AVID methodology resolves three important issues. First, it enables teams to more effectively leverage more innovation technologies across a wide spectrum of innovation contexts, circumstances, and conditions. Second, it addresses all critical aspects of the discovery phase of innovation, significantly decreasing the risk of innovation failure. Third, it provides a common language around which teams can ideate, collaborate, and work to maximize knowledge creation and workflow productivity during the innovation discovery process.

Why AVID is Called “Agile”

The AVID methodology is called “agile” because it incorporates some of the general principles of Agile Methodology, an iterative (non-linear) approach to software development that has been evolving since the 1980s. The agile approach uses empirical evidence captured throughout the discovery phase to generate customer value insights rather than a fixed execution plan that assumes knowledge of customer needs. Because of this, customer needs do not need to be known ahead of time.

Assumptions regarding value creation, delivery, and capture are tested along the way to determine their validity before they are accepted. Agile methodology is a more effective way to work when the project requirements cannot be known in advance due to uncertainties. An Agile approach provides opportunities to assess the direction of a value innovation project throughout the discovery phase as new knowledge is acquired.

The agile approach is “iterative” because teams are required to cycle back to previous steps to challenge flawed assumptions when they fail the reality test. The agile approach is also “incremental” because stages and/or steps provide the structure that moves a project steadily towards completion. By contrast, teams using a conventional linear-sequential product development model have only one chance to get each aspect of a project right. With a linear approach, the efficacy of the project is not known until the project is complete. In the agile paradigm, every aspect of development—customer needs, product/service design, business model, risks, and assumptions—is continually revisited throughout development.

A Systems Perspective of Innovation

Many believe that the discovery phase for product/service innovation cannot be structured because it is too amorphous and dynamic. They say that there are just too many scenarios, approaches, contexts, and that no one methodology can take all of these possibilities into account. They assert that structuring the discovery phase will stifle creativity and will slow down the process with bureaucracy and controls; that innovation is a serendipitous phenomenon that depends on having just the right people and conditions to make it happen.

The fact is that innovation is a very complex phenomenon — it is the ultimate multi-disciplinary sport. Innovation involves all aspects of business — competitive strategy, operations, marketing, finance, supply chain, leadership, culture, organizational capabilities, ecosystems, and other things. Who is comfortable claiming that they are competent in all of these business disciplines? Not many. Quite simply, innovation is overwhelming for most of us mortals.

Then there are the core innovation technologies like Blue Ocean Theory, Design Thinking, etc. Although each of these technologies is very useful, none of them individually encompasses all the aspects and contexts of the discovery phase. It’s like having bits and pieces of a large map with lots of chunks missing. Companies do their best with what they have. They gather a few pieces of the map and proceed through an ad hoc innovation process. Sometimes they develop a winner.

However, all indications are that only one out of five product/service innovations succeed. These are terrible odds! What most people do not appreciate is just how many ways a product/service innovation can fail. The truth is that no amount of creativity, bravado, or wishful thinking will surmount these pitfalls. The only way to increase the odds of success is to use a best practice for the discovery phase that enables a company to consistently develop successful innovations via an orderly and repeatable process.

A best practice provides the foundation for continual learning and the development of organizational capabilities. It is through a best practice that all employees rise to the occasion to contribute to the innovation efforts, not just the few gifted or the most influential.

The dynamics inside the discovery phase include interactions between various aspects of the business, interactions with customers, interactions between people, interactions between a company and its business ecosystem, and interactions with competitors and the market. The discovery phase is too complex to comprehend from a linear perspective, which conceptualizes a phenomenon as a collection of discrete causes and effects. The discovery phase is too complex to be reduced in this way.

However, the dynamics of the discovery phase can be understood from a systems thinking perspective. When viewed through the lens of systems thinking, it becomes clear that certain patterns of interactions produce certain outcomes. Because the various aspects of a system are interdependent, interactions are subject to trade-offs and constraints. In the world of systems, interactions produce feedbacks. These feedbacks then inform more interactions.

In the discovery phase, interactions and feedbacks iterate to produce knowledge which then informs decisions. These decisions determine the success or failure of outcomes. This is why conventional linear methods like phase/stage gate do not manage the discovery phase well when uncertainty is high. As the name suggests, “discovery” is the result of multiple iterations of interactions, feedbacks, and learning over the course of time.

The best growth opportunities cannot be ascertained by conventional analysis methods like SWOT, which assumes everything there is to know is already out there. Instead, the best opportunities are discovered through interactions. As these opportunities are developed into business models and product/service designs, no assumption can be taken for granted. The discovery phase requires empirical validation rather than analytical verification.

The Big Picture

The AVID methodology is a systems approach for managing the discovery phase of product/service innovation. The structure of AVID facilitates rapid learning and knowledge creation through cycles of interactions and feedback which systematically reveal critical outputs for lucrative growth opportunities. The AVID methodology enables teams to quickly refine critical outputs and resolve associated innovation risks through empirical procedures.

The AVID methodology is a hybrid framework that incorporates certain structural features, functions, and logic from other development methodologies — Agile Methodology, Phase/Stage Gate methodology, the Spiral Lifecycle Model, Kline’s Chain-Linked Model, and the New Concept Development Model. The AVID methodology is both incremental and iterative.

It incorporates theories, concepts, strategies, principles, techniques, methods, and tools from many of the core innovation technologies — Theory of Disruptive Innovation, Customer Jobs Theory, Blue Ocean Theory, the Customer Development Model, Lean Startup, Discovery-driven Growth, the Business Model Canvas, the Value Proposition Canvas, Open Services Innovation, Innovation Ecosystems, Design Thinking, and TRIZ. The AVID methodology is a contemporary best practice for structuring the discovery phase of value innovation projects.

External Inputs and Outputs

The AVID process begins with a high potential opportunity that is identified via the Entrepreneurial Insight Generator (indicated by the inward pointing arrow labeled “Hi Potential Opportunity”). The final outputs of the AVID methodology are execution strategies for a validated opportunity that is capable of achieving certain profit-revenue targets over time (indicated by the outward pointing arrow labeled “Execution Phase”).

AVID Stages, Action Steps, and Critical Stage Outputs

AVID structures the value innovation discovery phase into four incremental stages of development: (Stage 1) verify opportunity, (Stage 2) design job solution, (Stage 3) validate opportunity, and (Stage 4) develop execution strategies. Each stage consists of a number of action steps that are required to complete that stage in the discovery process. This results in a total of 11 action steps through four stages of development. The 11 action steps are iterative while the four stages are incremental.

A team will need to cycle back to previous steps when: 1) assumptions fail the reality test, 2) new knowledge is acquired in later steps that impacts earlier assumptions, and/or 3) it becomes clear that the pieces or logics of the formative critical outputs do not fit together into a coherent whole. The four stages represent the incremental development of the critical outputs and systematic resolution of innovation risks.

Each stage involves a critical output which serves as the input into the subsequent stage. The critical output from Stage 1 is a viable business model; the critical output from Stage 2 and part of Stage 3 (test differential value) is the best job solution fit possible for the target customers relative to competing solutions; the critical output from Stage 3 is evidence that the job solution prototype is the best value for the target customers relative to competitive solutions; and the critical output from Stage 4 are execution strategies (as articulated in a demand creation plan), which are passed to the execution phase of the project.

Critical outputs are expected to change when new knowledge is acquired as a result of iterations between action steps. The changing of these four critical outputs through iteration is represented by the four large, red, circular arrows positioned between each of the four stages. The text inside each iteration arrow is the critical output that is passed on from the proceeding stage to the subsequent stage. The circular arrows move backwards indicating that a team will need to cycle back to the preceding stage if that critical output is not achieved.

AVID Decision Gates

Decision gate 1 requires a “go forward” or “go back” decision on critical output 1 (viable business model) from Stage 1 before proceeding to Stage 2. This decision involves evaluating the business model to determine its viability and whether it is capable of meeting the profit-revenue target for the product/service based on what is known at that point (traditionally called a “proof of concept”).

Decision gate 2 requires a go forward or go back decision on critical output 2 (job solution fit) from Stage 2 and part of stage 3 (test differential value) before proceeding to validating the business model in Stage 3.

Decision gate 3 requires a go forward or go back decision on critical output 3 (best value) from Stage 3 before proceeding to stage 4.

Decision gate 4 requires a go forward or go back decision on critical output 4 (effectual plan) from Stage 4 before proceeding to the execution phase of a value innovation project.

Again, multiple iterations between action steps will be required to evolve the critical outputs to the point where they are capable of passing through the decision gates. That is, a team should know before presenting to decision makers if a critical output will meet the decision criteria for its respective gate.

With a go back decision on any gate, a team will need to iterate through the previous action steps until the gate criteria can be met. If the gate criteria cannot be met, the value innovation opportunity is abandoned, preventing the company from developing a new product/service that will likely disappoint. However, even when an innovation opportunity is abandoned, the learning acquired from the effort is cumulative and benefits future innovation efforts.

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