Systemic Innovation Failure
Running an innovation initiative, be it within a small startup or a team within a larger organization, frequently results in failure.
The challenge that any innovation initiative faces are substantial. There are a kaleidoscope opportunities, challenges, and obstacles overcome. This includes understanding the exact proposition customers will find value in; working to build a team that unifies around a consistent and shared vision; working with constrained resources; and, otherwise climbing barriers and perseverance in the face of countervailing forces. As a new offer, be it a service or product, is shaped from a rough idea to a concrete concept, proof of concept through prototype, to minimum viable product, there are a huge number of “unknown unknowns” in addition to the “known unknowns,” to borrow the Rumsfeldian phrase, to contend with.
A core challenge innovators face is how to move from an idea in the mind’s eye, through to a product that has broad appeal and traction. Given the rates of failure that seem to be acceptable, which may be as high as 80 percent by many estimates, it is a high risk proposition to engage in an effort like this.
There are ways to reduce the risk associated with innovative experimentation: the Lean Startup, argues for quick rapid tests of business-hypothesis, iteration, and verification. While the Business Model Canvas forces the entrepreneur to think through the details of an offering and construct the business case around a core value proposition. But through this, failure rates seem largely unchanged. Instead, we’ve moved to venerate rapid failure as evidence that risk has been embraced.
In the innovative entrepreneur’s wake lie efforts characterized by failure, missteps, and repeatedly attempting to crack a challenging problem against all odds. At the coal face of innovation, a dynamic, invigorating, and complex world of forces emerges. Failure rates are largely accepted as the cost of doing business, where the spark of innovation might create incredible value. But it’s mostly about value destruction, with resulting challenges to the mental fortitude of founders, early employees, and their relationships and support networks.
Early examples of airplane travel frequently include stories of death and destruction, missing airplanes, piles of destroyed airframes, and loss. Over time, supporting the pilots, clarifying procedures, preventing accidents, and managing risks in a highly complex aerospace environment become the norm.
The result was the creation of procedures, testing and verification, efforts to train and rehearse, and force high levels of professionalism onto air crews. Certifications need to be maintained and upgraded. The costs of failure are high, with every failure and near-failure an opportunity to examine the causes closely to mitigate against a recurrence and learn.
Over time, air travel has become one of the safest ways to travel. Checklists and tests became commonplace. The interactions between pilots and air traffic control became standardized. Radar and weather tracking tools were enhanced. And tolerances and limits understood and respected.
In medicine, mortality conferences are regularly scheduled and structured meetings to review the decisions and intervention steps that resulted in negative outcomes: the death of a patient. In surgery, checklists are an increasingly core component of how surgeons conduct their work. This doesn’t assure success, but it does insure against easy to avoid causes of complications (i.e., forgetting a surgical tool inside a patient after an operation).
The use of mental models has become something of a cultural phenomenon. Sites like Farnam Street discuss ways to structure thinking, make decisions, and approach problem solving. Social psychologists and behavioural economists have won Nobel Prizes for discoveries of cognitive biases, idiosyncratic patterns of illogical thought, and an inability to think probabilistically. This has become almost common knowledge, and used to achieve success in any number of fields (such as poker), as well as redefine how to generate accurate forecasts in politics. Concepts such as base-rates or the role of chance in good as well as bad outcomes has become part and parcel of how to manage major decisions for organizations, individuals, and society at large.
In line with this, McKinsey recently had two of its senior partners write a book on the art of problem solving. With details on how to master problem-solving processes. Their approach holds off the actual “solving” of the problem until the middle steps. An initial effort is focused on understanding the scope and scale of the problem at hand, defining it, nearly ad nauseum, to hammer out the specific core issue rather than becoming distracted by peripheral fragments. Throughout the focus is on clarity of focus, what are the uncertainties, and iterate through the process. Only once the problem is clearly defined and scoped, broken apart and understood, does the act of problem solving occur.
Across these examples — airplane travel, medicine, problem solving for business or personal decisions — a commonality appears: they were all revolutionized with structured decision-making processes. Constraints defined and articulated, operating tolerances and assumptions listed and tracked, and decision rubrics to reduce the role of chance, increase the probability of positive outcomes, and insulate against uncertainty adopted and used.
The foundational effort in innovation is to find a better solution to meet requirements, coupled with a willingness to pay the costs involved. Building tools to solve the wrong problem, to solve a need a customer doesn’t actually have, is a regular root-cause of innovation failure. The problem entrepreneurial innovations stumble on is rarely one of technology being inoperative for the innovation. The challenge of marketing and branding can be overcome. Accounting and finances are well understood and systematized. Legal supports can be brought to bear in a measured manner. Successful instances of high value innovation focus on clearly, systematically, and exhaustively understanding the needs customers have.
A revised approach to innovation must embrace the same type of tools, methods, and procedures that have reduced the risk of airplane crashes, increases the confidence that we’ve thought through critical decisions to be made, and the same tools that enable highly complex surgeries to occur.
Innovation efforts need to fully embrace tools that enable an understanding of the core foundational elements of value creation, of what specifically the problem being solved is, and a way to track and articulate this.
It’s not obvious that this exists in a widely adopted form today; the result is a systematic failure of innovation.
