Once upon a time, not so very long ago, commissioning an insight project typically meant embarking on a long and often pretty expensive journey.  Projects routinely ran for 8+ weeks and while you might get some results more quickly, the really meaty insight wouldn’t be delivered until the final debrief, usually many weeks or even months from the start of a project.

Luckily, the nature of insights delivery is changing, and insight projects are both faster and less expensive, largely due to a shift in approach.  Insights have taken their lead from UX and are increasingly adopting a ‘just enough’ iterative approach to insight and development.

While some sectors have been resistant, continuing to throw the world and everything in it at one, annual, post-experience survey – regardless of whether it fits their needs, others are adapting to this more agile approach and reaping the benefits.

So why is an iterative approach better than a one-hit wonder?  Because it’s a fluid, continual process of exploration, development, testing and reviewing.

Given the pace of change in today’s world; social, economic, behavioural, legislative, environmental and political, what’s appropriate now, might not be next week, month or year, so the drive for more continuous and iterative insight to drive business decision-making is more appropriate than ever.

Many organisations have historically been nervous of taking decisions based on ‘a little insight’ – it’s true, many poor decisions have been taken as a result of inadequate (too small) or biased samples.  However, that doesn’t rule out the iterative approach, we just need to be more mindful of sampling (who we speak to), objectives (what we want to know) and rationale (why we want to know it) and design the right approach accordingly.

A small sample of the right people delivering their views on a particular product, service or experience (inductive not deductive) can often generate far greater insight than a large, untargeted, potentially biased online survey sample, which can also often mask the small, but essentially important stuff.

We’ve all spent the last 5 years or so talking big data –  is it time to start sweating the small stuff?

Posted by: Lisa Holt