Fail fast, fail often?!

“Success is the ability to go from failure to failure without losing your enthusiasm.”       

attributed to Winston Churchill.

Is the 'fail fast' culture creating irresponsible entrepreneurs? "Fail fast, fail often" is the mantra that echoes everywhere in the startup universe. Startup gurus, investors, and aspiring entrepreneurs are trying to embrace failure as part of the learning process and building resilience in early-stage ventures.
But, how genuine is this? Does the entrepreneurial community really accept failure? Or is it just hype?
asks Anastasia Haralabidou.

The blog article "Fail Fast! Creating A Culture of Failure?" by Larry Boyer contrasts the context of the startup culture where the "Fail Fast, Fail Often" mantra originated with the context of the established corporate world to argue that both cultures are sufficiently different to not allow a straight adoption of that mantra.

The Fail Fast! philosophy seems to work well in the startup culture of Silicon Valley [, but] there is a context in a Silicon Valley start up that simply doesn’t apply in the corporate world. [...] There are 3 key subcontexts to the concept of Fail Fast! paradigm that are missed in the typical corporate discussion and execution:

• Avoiding Analysis Paralysis -  Experimentation & agile development

• Startup Darwinism - Risk-reward trade-off

• Counterculture Reactionism- Backlash against punishing failure
  

Avoiding Analysis Paralysis

[...] The need to think through the potential solution from beginning to end, uncover and address any likely issues, present your plan, make revisions and get approval to move forward. [...] By the time you’re through that process the need for your product has probably passed and your competition has made its money and moved on. [...]Sometimes it costs less and takes less time to just try it than it does to develop a formal design and testing plan. [...] A similar [iterative learning process] process can be found in in software development. Agile development also involves the rapid iteration and evolution of the software through short term goals, learning and moving on. It is a process of continuous learning and improvement along the way. Setback are expected and addressed rapidly to move the product forward.

Start-up Darwinism
Startup Darwinism refers to venture capitalists and entrepreneurs rapid exploration of business ideas and either quickly grow the business or shut it down. It’s a strategy where you can win big or cut your losses quickly and move on to the next big idea. There are parallels between the roles of VCs with corporate shareholders or executives as well as entrepreneurs and employees or, as is now vogue, intra-preneurs. [...]There are, however, important differences and perhaps none as important as the mindset. For the entrepreneur and founding employees the success or failure of the project is personal. [...] In the corporate world where such investments are made there are frequently many layers insulating the investors and those doing the work.

Even so, venture capitalists don’t just through money at projects with the expectation of failure. The expectation is success.

Counterculture Reactionism
Entrepreneurs enjoy taking risks, taking ownership of a project and the results. [...] The fail fast concept provides an acceptance of risk taking, learning and accountability if your ideas and direction don’t work out.

Values and Watching Your Language
Values define the way we make decisions, approach problems and go about our daily business. [...]Corporate values will often include: Excellence, Innovation, Creativity, Curiosity, Respect, Teamwork and the like. Have you ever seen a corporate value of Failure, Fail Fast or Fail Often? 

PwC suggests both cultures can be bridged and elaborates on "How to bring a fail-fast culture to a slow-move company".

In "Failure is the Mother of Innovation" Baba Shiv argues that 

Experimentation and failure are essential to innovation because, by its nature, an innovation is an unknown that can only be discovered through trial and error. Still, for all the startups that follow the mantra of “fail fast,” there are many corporate leaders who see failure as something to be avoided, not embraced. [...]
In corporate hierarchies there is a tendency to give greater weight to the opinions of leaders rather than their subordinates. However, those opinions are usually based on instinct rather than information. The one thing that can trump a higher-up’s opinion is data, and repeated experimentation and failure lead to a lot of it. [...]
Data can also win over the opposition. Those with a risk-averse mindset generally oppose innovating through experimentation, like rapid prototyping or continual iteration. [...]
Organizations also tend to reward big breakthrough successes rather than smaller ones, but those game-changing innovations generally happen after, or in tandem with, the incremental ones. [...] This two-pronged approach relies on exploitation and exploration.
Exploitation [...] means honing competencies [a company] already has to reduce costs and improve the value for customers — incremental innovations. At the same time [a company] invests in exploration, which enables breakthrough innovations.

Technology first. User needs last?

“If I had asked people what they wanted, they would have said faster horses.” — attributed to Henry Ford

“It's really hard to design products by focus groups. A lot of times, people don't know what they want until you show it to them.”
— Steve Jobs

In his 2010 article "Technology first, needs last" renowned design professor Don Norman came to a disconcerting conclusion:

Design research is great when it comes to improving existing product categories but essentially useless when it comes to new, innovative breakthroughs.

[...] Although we would prefer to believe that conceptual breakthroughs occur because of a detailed consideration of human needs, especially fundamental but unspoken hidden needs so beloved by the design research community, the fact is that it simply doesn't happen.

New conceptual breakthroughs are invariably driven by the development of new technologies.

The new technologies, in turn, inspire technologists to invent things, not sometimes because they themselves dream of having their capabilities, but many times simply because they can build them. In other words, grand conceptual inventions happen because technology has finally made them possible.

Do people need them? That question is answered over the next several decades as the technology moves from technical demonstration, to product, to failure, or perhaps to slow acceptance in the commercial world where slowly, after considerable time, the products and applications are jointly evolve, and slowly the need develops.

[...] But if you examine the business impact of innovation, you will soon discover that the most frequent gains come from the small, incremental innovations, changes that lower costs, add some simple features, and smooth out the rough edges of a product. Most innovations are small, relatively simple, and fit comfortably into the established rhythm and competencies of the existing product delivery cycle.

Successful revolutionary innovation is rare. In any given arena, it happens only a few times per decade. Why? In part because it is difficult to invent a new concept that truly fits people's lives and needs. In part, it is because existing products already satisfy most people and when the new concepts appear, the older, existing technologies have a remarkable way of rising to the challenge and sustaining themselves for years - decades even - long after people thought they would disappear. [...]

Major innovation comes from technologists who have little understanding of all this [design] research stuff: they invent because they are inventors. They create for the same reason that people climb mountains: to demonstrate that they can do so. Most of these inventions fail, but the ones that succeed change our lives.

Build it and they might come? 

If you disagree with Don Norman's view - that he subsequently refined in a presentation on "Incremental and Radical Innovation: Design Research versus Technology and Meaning Change" together with Roberto Verganti - you may want to consult Bruce Neumann's objections documented in "Technology Vs. Design - What is the Source of Innovation?". Then again, Mr. Neumann has meanwhile distanced himself somewhat from the "Design Thinking" movement.

Norman has a model of innovation that is top-down, one-way and very old. It goes this way. Engineers invent. Marketeers construct products around the new technology. Designers put on a pretty face. And then the stuff is thrown at the consumer marketplace, with the hope that it finds a need or a want. In the past, sometimes it did. Often it didn’t.
[...]
Thanks to design thinking and new tools and methods in ethnographic research, we now have a new model of innovation that is flat, open-source and dynamic. It pulls people into an engagement with technologists early and perhaps more productively, rather than have them wait for technologies that may evolve into innovations they can actually use. Ethnographic research is especially important in an era of co-creation and social media, where consumers demand a say in creating the products and services they use.

I take note of Neumann's quote, though:

Invention has to have socio-economic value to become innovation. It has to be socialized or else it sits in the lab.

Technology-Push or Marketing-Pull?

See the "Typology of Innovation" blog entry for further categorization of innovation types.

Innovation Metrics

It should not come as a surprise since there is no single definition of the term "innovation" to start with: 

There is no established measurement framework in the software industry to measure innovation yet – according to this 2013 study*

Edison, H., Ali, N.B., & Torkar, R. (2013). Towards innovation measurement in the software industry. Journal of Systems and Software 86(5), 1390-1407. Available at: http://www.torkar.se/resources/jss-edisonNT13.pdf 

The article lists some metrics, though, that we can consider in this context (see Table 5 on pg. 1397) if we find a simple and reliable way to track them – highlighting is mine:

Category     Example 
Determinants The existence of a project champion, knowledge sharing, government regulation              effect
Inputs       R&D expenditure, R&D intensity (ratio of R&D expenditure to total assets),
             percentage of workforce time that is currently dedicated to innovation                      projects
Outputs      Patent density, new organisational programs, number of new processes              and significant enhancement per year

Performance  Percentage of sales that is generated by new products, citation ratio, impact              of brand
Activities   Percentage of ideas funded, quality of adaptation, managers survey

*Excerpt from 8. Conclusions on pg. 1405

The purpose of this study was to establish the current practices, mechanisms and challenges of innovation measurement in the software industry. […] The study found that among major challenges is a lack of a consistent perspective of innovation. This difference in views affects how innovation measurement initiatives are conceived (what is considered key aspect of innovation) and executed (which metrics are required to capture a particular aspect). […]

[…] there are several shortcomings in the state of practice. In the software industry, there is a lack of defined innovation process and measurement programs. Similarly, none of the well-known measurement frameworks are used to measure innovation. […]

The outcome of this review contributed to the existing body of knowledge in the form of an innovation measurement model, enumeration of metrics and their classification based on what aspect of innovation they are used to measure. […]

The metrics listed above are in line with the traditional innovation metrics documented in " The Complete Guide to Innovation Metrics – How to Measure Innovation for Business Growth" by Soren Kaplan, but he goes on to define more modern metrics that better reflect today's "Open Innovation" methods.

How do you measure innovation? One of the reasons that only about 1/3 of all Fortune 1000 companies have formal innovation metrics is because this simple question does not have a simple answer. [...]

The heart of the problem is that today’s competitive environment is radically different from the industrial environment in which traditional innovation metrics were born. Because most metrics programs begin with benchmarks of established companies that have been successful with new products (like 3M or Google), metrics tend to revert back to traditional measures of R&D or technology investment and effectiveness. Across the Fortune 1000 that do possess innovation metrics, for example, the most prevalent metrics include:

• Annual R&D budget as a percentage of annual sales
• Number of patents filed in the past year 
• Total R&D headcount or budget as a percentage of sales
• Number of active projects 
• Number of ideas submitted by employees
• Percentage of sales from products introduced in the past X year(s)

While some of these metrics are valuable for driving investment in innovation and evaluating results, they provide a limited view. In today’s environment in which “open innovation” (sourcing ideas and technology from outside the company) can create differentiation and competitive advantage, for example, some of these metrics actually inhibit strategic innovation. And in an environment in which disruptive innovation and cannibalization must be wholeheartedly embraced as a core strategy, fundamentally new types of behaviors are required, and subsequently new structures and related metrics to drive these behaviors. [...]

A Framework for Innovation Metrics

The best solutions create simplicity from complexity. Assuming that successful innovation results from the synergies between complementary success factors, it is important to address these by:

• Creating a “family of metrics” for ensuring a well-rounded portfolio of measures
• Including both “input metrics” and “output metrics” to ensure measures that drive resource allocation and capability building, as well as return on investment

A “family of metrics” ensures a portfolio of measures that cover the most important innovation drivers.  The following are the three categories to consider for any metrics portfolio:

Return on Investment Metrics
ROI metrics address two measures: resource investments and financial returns.
ROI metrics give innovation management fiscal discipline and help justify and recognize the value of strategic initiatives, programs and the overall investment in innovation.

Organizational Capability Metrics
Organizational capability metrics focus on the infrastructure and process of innovation.
Capability measures provide focus for initiatives geared toward building repeatable and sustainable approaches to invention and re-invention.

Leadership Metrics
Leadership metrics address the behaviors that senior managers and leaders must exhibit to support a culture of innovation within the organization, including the support of specific growth initiatives.

[...]

Please consult “Soren Kaplan’s article” for the details of the proposed metrics.

Open Innovation

Companies are shifting from the traditional closed model of innovation to embrace a more practical and smarter way of innovation – "Open Innovation", a term originally coined by then Harvard Business School Professor Henry W. Chesbrough.

Aditya Purohit has summarized the approach in his blog "What is an Open Innovation approach" as follows.

Moving from the "Closed Innovation" thinking that all R&D needed to be in-house and use only internal resources to develop intellectual property (IP) for new products or services, "Open Innovation" defines the antithesis of the traditional approach. "Open Innovation" (OI) helps companies look beyond their boundaries to seek and utilize inflows & outflows of knowledge, to accelerate innovation.

The concept of OI entails a series of activities that help with the integration and interaction with external sources of knowledge. This could include everyone in the ecosystem right from suppliers, clients, and customers to competitors, research institutes, and non-customers from completely different industries. The objective boils down to stimulating innovation by creating strategic alliances and networks. This process is characterized as the “Outside-In” processes.

The other way in which OI is approached is the “Inside-Out” process. The idea is for companies to appropriate value by bringing ideas to the market, trade their IP, and undertake technology transfer to the external market for further development of the technology/idea being transferred.

The primary aim here is to exploit their intellectual property developed beyond the firm’s boundaries. This is done either by licensing / joint ventures / spin-off’s the technology / ideas to other companies / industries. The value generated isn’t restricted to financial gain only. It’s about collectively engaging a larger audience to support an idea and thereby have a new business model for innovation in new markets.

Both aspects, the outside-in approach to secure new knowledge, and the inside-out process to bring ideas to the market, can be combined in a hybrid OI process which leads to co-creation between complementary partners via network alliances, joint ventures, and other vehicles of cooperation. This is where digital platforms and social media for idea exchange and community building, and advanced analytics come into play to bring together problem-solvers and those demanding an innovative solution.

Innovating Innovation

When I was reading Henry W. Chesbrough's book on "Open Innovation", the foreword by John Seely Brown, former Director of Xerox PARC, about "Innovating Innovation"  grabbed my attention.

Here's an excerpt:

[...] Some more definitions: by innovation I mean something quite different from invention. Innovation to me means invention implemented and taken to market. And beyond innovation lies “disruptive innovation.” By this I mean something that actually changes social practices — the way we live, work and learn. Really substantive innovation — the telephone, the copier, the automobile, the personal computer or the Internet — is quite disruptive, drastically altering social practices.

Disruptive innovation presents some major challenges. First, although it may be relatively easy to predict the potential capabilities of a technological breakthrough in terms of the products it enables, it is nearly impossible to predict the way that these products or offerings will shape social practices. The surprising rise of email is but one example. It is not technology per se that matters, but technology-in-use, and that is what is so hard to predict ahead of time. Nevertheless, technological breakthroughs that do end up shaping our social practices can produce huge payoffs, both to the innovator and to society.

A second major challenge is that a successful innovation often demands an innovative business model at least as much as it involves an innovative product offering. This is a hard lesson for research departments of large corporations to learn. It is why so many great sounding innovations in the research lab fail to see the light of day. In the lab, we have devised many ways to rapid prototype an idea, explore its capabilities and even test lead customers' reactions to it. But innovations that intrigue the customer don’t necessarily support serious business models — as the dot.com boom and bust showed again and again — and even those that do may support a model that threatens to cannibalize the sponsoring corporation's existing business models. So, as one aspect of innovating innovation, we need to find ways to experiment not only with the product innovation itself, but also with novel business models. Rapid business model prototyping is thus of critical importance to the future of technological innovation, [...]

There are additional reasons to innovate innovation. Most prior models turned on the creativity within the firm. In today’s world we are faced with two new realities. The first is that there are now powerful ways to reach beyond the conventional boundaries of the firm and tap the ideas of customers and users. Indeed, the networked world allows us essentially to bring customers into the lab as co-producers. [...]

The second reality has to do with the fact that today most of the world’s really smart people aren’t members of any single team but are distributed all over the place in multiple institutions. Similarly, we are now looking for innovations in the interstices between different disciplines — between, for example, biotech and nano technologies. Any new model of innovation must find ways to leverage the disparate knowledge assets of people who see the world quite differently and use tools and methods foreign to ourselves. Such people are likely to work both in different disciplines and in different institutions. Finding successful ways to work with them will lie at the heart of innovating innovation.

New technology offers us new tools to help in this meta type of innovation. ...

[...] 

The open innovation model that Chesbrough describes in this book shows the necessity of both letting ideas flow out of the corporation in order to find better sites for their monetization and also to flow into the corporation as new offerings and new business models. [...] An open innovation model diminishes both the error of squelching a winner (a false negative) and of backing a loser (a false positive). [...] Let us, instead, all engage in the process of innovating innovation. [...] "

Typology of Innovation

There seems to be a common view that only "disruptive" innovation counts, i.e. technological innovation that radically disrupts business practice, when in essence this is only one - extreme - type of innovation which is certainly not the most frequent but, of course, potentially the most impactful if successful.

To quote from Applying Innovation, D. O'Sullivan, L. Dooley, 2008:

Every now and again a radical innovation is introduced that transforms business practice and rewrites the rules of engagement. In other words, business practice across an entire industrial sector changes radically.

[In "Innovator's Dilemma"] Christensen (1997) defines these types of innovations as disruptive innovations. Disruptive innovation often occurs because new sciences and technology are introduced or applied to a new market that offers the potential to exceed the existing limits of technology.

Note that Gary P. Pisano (see "You Need an Innovation Strategy" below) only emphasizes the business model change but not a radical shift in technology:

Disruptive innovation [...] requires a new business model but not necessarily a technological breakthrough. For that reason, it also challenges, or disrupts, the business models of other companies.

The maybe confusing usage of the term "disruptive" has been acknowledged by Clayton Christensen himself in this recent noteworthy Google Talk (@1:05:47):

BTW, Christensen does not consider Uber a disruptive innovation despite it's profound impact on the established taxi market as explained in the 2015 "What is Disruptive Innovation?" HBR article nor does Tesla qualify but Airbnb does per explanation given in a 2015 Forbes interview.

Most ideas, however, will rather lead to incremental sustaining or routine innovation; that is often incremental, evolutionary improvements of existing products.

The concepts of "novelty", "impact", and "fields" of innovation listed below are taken from "Towards innovation measurement in the software industry".

Novelty or Reach of Innovations

Note that only a very small fraction of innovations are new to the world, some are new to a market, or new to an industry, and most are (only) new to a particular organization or company.

Impact of Innovation

• Incremental innovation -
  These are relatively minor changes in technology based on existing platforms that deliver relatively low incremental customer benefits.
• Market breakthrough -
  These are based on core technology that is similar to existing products but provides substantially higher customer benefits per dollar.
• Technological breakthrough -
  These innovations adopt a substantially different technology than existing products but do not provide superior customer benefits per dollar.
• Radical innovation -
  They are referred to as disruptive innovations which introduce first time features or exceptional performance. They use a substantially different technology at a cost that transforms existing or creates new markets and deliver a novel utility experience to customer.

Fields of Innovation

• Product innovation
• Process innovation
• Market innovation
• Organisation innovation

Dimensions of Innovation

• Extent of change (radical—incremental)
• Modality of change (product—process)
• Complexity of change (component—architecture)
• Materiality of change (physical—intangible)
• Capabilities and change (enhances or destroys market/technological capabilties)
• Relatedness of change (replaces a firm’s existing product or extends it)
• Appropriability/Imitability (difficult or hard to hang on to)
• Cycle of innovation (time between discontinuities)

Types and Extent of Innovation (as cited by Andrew Davies in "Innovation contexts" except for the entries after 2003)

• Radical or incremental (Freeman 1974)
• Product life cycle – product or process innovation (Abernathy and Utterback 1978)
• Continuous or discontinuous (Tushman and Anderson 1986)
• Modular or architectural (Henderson and Clark 1990)
• Sustaining or disruptive (Christensen 1997)
• Open or closed innovation strategies (Chesbrough 2003)
• Market-pull, technology-push, meaning-driven innovation or technology epiphanies (Norman & Verganti 2012)
• Performance-improving or Efficiency or Market-creating (Christensen 2016)
• More recent concepts:
• Service innovation
• Business model innovation
• Management innovation

In his June 2015 Harvard Business Review (HBR) article "You Need an Innovation Strategy" Gary P. Pisano provides the following Innovation Landscape Map that list examples for four dimensions (routine, radical, disruptive, architectural):

Routine innovation builds on a company’s existing technological competences and fits with its existing business model—and hence its customer base.

Disruptive innovation requires a new business model but not necessarily a technological breakthrough. For that reason, it also challenges, or disrupts, the business models of other companies.

Radical innovation is the polar opposite of disruptive innovation. The challenge here is purely technological.

Architectural innovation combines technological and business model disruptions.  As one might imagine, architectural innovations are the most challenging for incumbents to pursue.

A company’s innovation strategy should specify how the different types of innovation fit into the business strategy and the resources that should be allocated to each. In much of the writing on innovation today, radical, disruptive, and architectural innovations are viewed as the keys to growth, and routine innovation is denigrated as myopic at best and suicidal at worst.

That line of thinking is simplistic.

In fact, the vast majority of profits are created through routine innovation.