The essential component for innovation of any kind is an insight, a singular spark that inspires an idea, which in turn can be developed into a concept for a new product or service. Despite the emergence of better data collection and better data analysis, people are consistently the source of these insights, not data.
Data is rightly regarded as the currency of the digital economy. Every smart organisation invests in it and many have proclaimed that it is the foundation upon which all key decisions will be made. Certainly, when combined with enough computational power and, increasingly, machine intelligence, data provides critical information about historic behaviour (whether counted in microseconds or years) and can predict some future patterns effectively, if processed by the right algorithms.
Of course, not all algorithms are equal and few organisations have access to the type of data-crunching capabilities that an Amazon or a Google can bring to bear. Even they recognise that you can’t rely on them for everything.
Jeff Wilke, an Amazon SVP, told Bloomberg recently: “It’s one of the contradictions of life inside Amazon. The company relies on metrics to make almost every important decision, such as what features to introduce or kill, or whether a new process will root out an inefficiency in its fulfillment centres. Yet random customer anecdotes, the opposite of cold, hard data, can also alter Amazon’s course.”
It’s a remarkable insight into an organisation that is famous for its automated recommendations. Data, collected and interpreted well can provide unparalleled intelligence to fuel operational optimisation. For the bigger leaps, we need human insights. At least for the foreseeable future.
Currently, and I stress currently, even the best algorithms can only provide intelligence based on what they are fed and that data is always operational. In fact, it’s critical that it is operational, as that’s where optimisation kicks in – real- time analysis of behavioural patterns that can be used to reflect patterns back at people, or inform internal teams about what’s working and what’s not, down to an incredibly fine-grained level. It’s something most humans find incredibly hard to do.
On the other hand, data remains a crude tool for fuelling the bigger leaps. Read the origin scripts of any of the world’s digital success stories (and pretty much every other startup) and you’ll be hard-pressed to find a single one that was borne out of data.
Instead, you’ll find thousands of insights and moments of inspiration. Whether identification of an opportunity that hadn’t been pursued, recognition of a problem that no-one had solved, or even the desire to create something to compete with an existing service, all are human insights.
The message here is simple: data is invaluable for operational optimisation, but don’t expect it to produce your next big idea. The limitations of data are as important to appreciate as its strengths and relying on it for too much can be as dangerous as not using it at all.