**1.2 e-**

…in parallel with the product-to-service evolution trend there is a pattern of evolution that sees 'mechanical' technologies evolving towards electronic and digital solutions. The mechanical keypads found on the first mobile phones have evolved to become digital touch-screens; the 35 mm film used to record photographic images has become digital; the physical money traditionally carried in people's pockets, is increasingly becoming 'e-cash'. People used to visit shops and now increasingly shop online. There are literally thousands of examples of such physical-to-virtual transitions [2]. The common factor – that it is easier to move electrons rather than atoms – again delivers inherent environmental benefits as well as being better able to serve customer needs. As such digitalisation looks set to be a trend that will also continue for the foreseeable future.

#### **1.3 Innovation**

The rise in the importance of innovation offers up another highly visible evolution trend. This trend is driven by the convergence of a host of other societal trend patterns. Globalisation, the transparency emerging through social media, rising populations, climate change, finite natural resources combine to create, firstly, an imperative to find better ways of doing things, and, secondly, an increasing likelihood that if incumbent organisations fail to meet shifting customer needs, someone else will step in.

'Innovate or die' has been a commonly used aphorism for close to two decades now. More often than not, however, it becomes 'innovate *and* die'. 98% of all innovation attempts end in failure [3]. The world of innovation, in other words, is one that is largely dysfunctional. There are many reasons for this, but two stand above the others. One, is the growing recognition that innovation is not the same as the 'continuous improvement'/'operational excellence' management philosophy that has been dominant since the quality revolution of the 1970s. Rather it is the opposite. Methodologies like Lean and Six Sigma, while extremely potent ways of driving improvement, turn out to drive problem solvers in precisely the wrong directions when it comes to innovation. In Operational Excellence world, for example, 'variation' is bad and therefore needs to be eliminated, but in Innovation World, variation is in many ways the prime enabler of identifying step-change opportunities and solutions.

Second is the definition of the word innovation. Over 90% of authors using the word use or imply a definition that equates innovation to either 'new ideas' or, more commonly, 'new ideas that are launched onto the market'. Neither of these definitions, however, makes any kind of sense from the perspective of enabling better understanding of how to innovate. By either measure, e-service providers like Uber count as innovation, but, at this point in time, the Company has lost and continues to lose vast amounts of money. To the point, many investors are beginning to believe that they will never become cash positive. Any prospective innovator taking organisations like Uber as models for their own projects is only likely to

#### *Systematic e-Service Innovation DOI: http://dx.doi.org/10.5772/intechopen.96463*

fall into the same financial black-hole. The only innovation definition that makes sense is one that includes a success metric. For most enterprises this metric will be financial in nature – achieving a net positive ROI for example, or customer value, or profit – while for others it will be measured in other ways – patient life expectancy or quality of life. Whatever the chosen success metrics are, a new idea only becomes an innovation once they are met. The primary importance of using this definition is that it is the only one that enables a possibility of acquiring and sharing repeatable best practice…

## **1.4 Systematic**

…much of the 98% failure rate found in Innovation World comes from the fact that innovating is difficult. It demands that innovators embrace the innate complexities of the world. It demands they are willing to venture into the unknown. And that they are willing to persevere through the many false-starts, insurmountable obstacles and dead-ends, through the maze of mis-information, mis-interpretation, confusion, stress, and sleepless nights. In many ways, the 2% were first and foremost lucky. They prevailed predominantly by trial and error. Perhaps ironically, the digital world has been lucky enough to stumble upon 'methodologies' like Agile and Scrum, and has evolved the concept of the hackathon in order to increase the speed trial-and-error iterations are able to be performed. The irony being that, even though consistent with working in complex environments, the rapid-trial-and-error strategies of many in the digital world have had little or no impact on the overall innovation statistics. 98% of all innovation attempts fail; 98% of e-service innovation attempts fail.

The big idea underpinning 'systematic' centres around the removal of the trialand-error randomness from the e-service innovation process. In effect it becomes, like its TRIZ forerunner [4], a programme of research to decode and reveal the 'DNA' of the 2% of successful attempts. When dealing with complex systems, as we inevitably are when it comes to innovation, such a task is fraught with difficulties. Not least of the reasons being that it is never possible to 'step in the same river twice'. Just because an innovation team replicates all of the steps of a previously successful innovation project does not guarantee their success. In fact, given the general speed of change in the world, the surrounding context and environment of any previously successful project is inevitably different in today's project. Many prospective innovators, unfortunately, have been taught that 'doing the same tomorrow as you did yesterday and expecting a different outcome' is one of the first signs of madness. Such an aphorism might have made sense in simpler times, but it carries little if any relevance in a complex world. To the extent that the 423 Fortune 500 companies from the original 1950s list that no longer exist could all be said to have fallen precisely into the trap of continuing to do what they'd always done and expecting to get the same money-making results.

'Systematic' and 'complex', in other words, do not traditionally make for good companions. 'For every complex problem there is an answer that is clear, simple and wrong', says another dangerous aphorism. It is an aphorism that might today be extended to say that every complex problem has *thousands* of clear, simple wrong answers. But in making that extension, now that the appropriate research has been conducted, it also becomes possible to say that every complex problem has at least the possibility of a clear, simple right answer. Provided that the first principles of innovation have been incorporated into the simplicity. This, then, has been the basis of the Systematic Innovation research programme [5] over the course of the last two decades: to understand complex systems from a first principles perspective. Which, in the first instance, means examining millions of case studies and looking for

patterns. There being vastly more examples of failed innovation attempts than successful ones, this in turn means looking at failed projects and looking for repeated failure mechanisms.

The results of this analysis – which to date has incorporated over 11 million case studies – is that when innovation attempts go wrong, they go wrong for a very small number of reasons. When it comes to e-service attempt failures, that number, as shown in **Figure 1**, is effectively three:

Which can be elaborated upon as follows:


**Figure 1.** *Three primary sources of e-service innovation attempt failure.*

#### *Systematic e-Service Innovation DOI: http://dx.doi.org/10.5772/intechopen.96463*

and design iterations, should in theory eventually stumble upon contradictionsolving solutions. In practice, however, because almost no designers have been taught that contradictions can be solved, what happens is that Agile and Scrum devolve into trade-off merry-go-rounds which simply transfer the trade-offs from one design parameter to another, until eventually the team ends up, whack-a-mole like back where they began.

3.Failing to find the Road Back. The third problem concerns execution of the innovation project and what might be seen as a failure of perseverance. This is the part of a project where using the wrong definition of 'innovation' comes into play. It is one thing to find 'the solution' to a customer need, it is quite another to turn it into money. A big part of the innovator's challenge here is that large parts of the digital investor world has become too enamoured of so-called 'unicorns'. The digital world has become quite adept at creating companies that are able to attract billion dollar valuations. But attracting a billion dollar valuation and generating more than a billion dollars of new revenue are most definitely not the same thing. The investor ethos seems to hold the irrational belief that what happened with digital Goliaths like Amazon, Facebook, Baidu, Tencent, Alibaba and Google, will also happen to them. And that the game is merely about keeping the enterprise going long enough that the profits will begin to appear. Time, alas, is not the only factor at play, start-up enterprises, need 'innovation DNA' to find the right customer problems and solutions, but they then need to be able to integrate that way of thinking with Operational Excellence World thinking in order to work out how to make money from those solutions. Innovation and Operational Excellence, per earlier comments, may be polar opposites of one another, but any successful enterprise needs to be able to master both sets of skills and bring the requisite ones together at the right places and times. Very few digital start-ups get to master this integration challenge before the last in the chain of investors decide to call time.
