Big Data and Big Data analytics are very topical at present in business writing. Start-up companies and multi-national corporates alike, try to exploit the data they generate to :

  • gain customer insight,
  • support a plan for blockbuster innovation,
  • study history,
  • run forecasting simulations,
  • do virtual prototyping.

In government, senior policy makers talk about developing evidence-based policy, (to excuse inaction?), while waiting for the perfect set of evidence (data) to come along.

It may be that Big Data analytics gets somewhat over-hyped as the engine of progress, but that design, (for product innovation, or to design novel solutions to new business problems for which history doesn’t show us the answer) is at least as important for progress. Some examples of history not showing us the answer? Evolution generally (biological species, synthetic biology, business strategy) and the emergence of artificial intelligence in systems.

Design of course relies on a group of human techniques including; discussion, brainstorming, imagination, intuition, reverse-engineering, provocations, thought leadership and lateral thinking. In the main, they don’t sound very business-like, but try and deliver significant business innovation without them!

In conclusion, exploiting Big Data is necessary. Encouraging great design, aided by Big Data, is sufficient.