After all, most CMOs are constantly concerned that digitalization and all the changes that go along with it will disrupt their industry. By implementing analytics solutions, they manage to put data front-and-centre in strategy development, product innovation and overall decision-making – alleviating their concerns. In a sense data gets ascribed the role of a contemporary oracle, which should provide them with an answer to the famous Innovation’s Dilemma proposed by Clayton Christensen. The secret hope being that by implementing the right BI tool, one will always know in advance when and how to optimize the existing assets to get the most out of them, and when to venture into new territories to stay ahead of the disruption curve. The reality is that currently evangelised analytic systems are very good at the first task and less so in the second one. Hence, when it comes to data empowered innovation it has to be distinguished between data-informed innovation and data-inspired innovation.
Analytic tools and BI systems used by most companies heavily rely on internal data which measure only existing or past circumstances. The metrics measured are purely a projection of the marketing strategy in place and therefore limited to activities that have already been employed. Meaning that they measure only current consumer behaviour and product performance. Innovating based on data-informed decisions means acknowledging the fact that one has only a small subset of information that derives only from one’s own assets and their performance. In this regard data-informed innovation concerns itself with new solutions that optimize currently employed customer journeys, services and products. Using descriptive and diagnostic analysis problem areas, unserved needs or unexploited potentials within the current offerings portfolio can be identified.
This, of course, provides more than enough fruitful ground for innovation, but one also has to be aware of the pitfalls such an approach harbours. For one, the whole innovation process is based on data that is systematically biased. As stressed, most data analysed with BI tools is based on existing metrics and heavily relies on already employed processes and products. But an even bigger danger is the false sense of security data-informed innovation provides decision makers with. After all, it is in human nature to focus only on the known and avoid new paths.
Not everything is an optimization problem. Data-informed innovation is important, and too often under-utilised in most businesses, however there is a limit to the gains that one can derive from optimisation. Even more, focusing largely on data-informed innovation de-priories the potential bigger picture and disruptions that may affect an industry. And this is where data-inspired innovation comes into play.
There is a saying among NBA players: “You miss 100 percent of the shots you never take.” This is exactly what data-inspired innovation is about: not missing out. It is about making informed decisions about the development of new kind of offerings that will ensure future success. In contrast to data-informed innovation, data-inspired innovation is often seen by managers as a leap of faith, since it bares low relevance for immediate business performance. Investing in, and even more acting on insights that derive largely from limited external secondary data sources and first changes in consumer behaviour takes managerial fortitude and vision. Organisations perusing data-inspired innovation make informed decisions, based on predictive analysis methods, while at the same time consider their own experiences and know-how. Nevertheless, despite their best efforts to shape the future, it remains uncertain and encountering dead ends is unavoidable. The difference to companies focusing largely on optimization being, that companies who pursue data-inspired innovation widely embrace errors. In a Jiu-Jitsu like move they use their prediction failures to improve their data-inspired innovations. Doing so, they are much better able to anticipate and adapt to changing market conditions, as well as quickly operationalize the insights they developed.
It is not an either-or decision
As Alan Kay, the pioneering computer scientists, said: “The best way to predict the future is to invent it.” With the ever more prominent role digitalisation plays in business, his quote wins only on importance throughout the years. While currently most companies are concerned with installing cloud based BI solutions and data visualisation tools, which certainly will provide insights into unexploded potential, this will not make organisations immune to being disrupted. To prosper in the current digital business world and at the same time avoid unpredicted market changes, data will have to be employed for both business improvement and business advancement. In this regard both data-informed, as well as data-inspired innovation should be pursued at the same time. However, for organisations to be able to realise such efforts, following factors have to apply:
- There must be a clear vision in place about what the company wants to accomplish (besides making profit). The vision acts as a compass, guiding the way for data exploration.
- Data-driven culture has to be actively encouraged. This applies to the notion that the understanding of data and its results is not just a task of a certain department, but rather that an open access to tools and databases throughout the organisation is provided and its usage encouraged.
- There is a lean strategy process in place, which awards informed risk-taking and an agile iterative approach to innovation.
- In the yearly forecast, there is space and budget put aside for “Moon shots projects” that allows data-inspired innovation to unfold.
We acknowledge that implementing data-informed and data-inspired innovation at the same time is somewhat daunting and can’t be done overnight. Nevertheless, taking baby-steps with data empowered innovation often leads to big leaps, since the direction for innovating is based on thorough calculations.