Just because data is big, and getting bigger, does it mean we should hang up our measure design and data sense-making skills to let technology do it for us? Or is big data a big risk for KPIs?

In his book, Big Data, Big Dupe, Stephen Few uses the yellow brick road to the Wizard of Oz as the metaphor for the journey to Big Data. It’s perfect.

Like the Wizard of Oz, Big Data doesn’t seem to be real. There isn’t a clear and broadly accepted definition of it. The entire first chapter of Big Data, Big Dupe clearly points this out. The myriad definitions of big data are weasely and wide-ranging. About the only common thread is that big data has to do with the explosion in data available today.

Sure, there is more data available now than ever before. And it’s collected faster than ever before. We can know much more than ever before.

But how exactly does the quantity and speed of data coming at us have anything to do with what we need to know? Can the new technologies that promise to reveal insights galore from our big data really decide what we need to know?

And this is one of Stephen Few’s fundamental points: we must do the thinking to decide which data will serve us. In performance measurement, and probably most situations we require data, we must do the thinking to decide how it will serve us in:

• choosing which goals are worthy to pursue
• answering the questions we have about achieving them
• being convinced that we are making progress toward them
• making the best choices to achieve those goals
• without overwhelming us or misleading us

The big data circus reminds me a lot of the mistakes many companies are still making with dashboard technologies: we keep making the mistake that the technology provides the answer. It doesn’t. Technology only provides facilitation:

• We must decide what measures or KPIs are useful to us; technology will facilitate how we define them, implement them, and report them.
• We must decide what signals our measures or KPIs are showing us; technology will facilitate the visual presentation to highlight these signals.
• We must decide what questions we have about the causes of the signals in our measures and KPIs; technology will facilitate how we can dive deeper into the data to answer those questions.

Dorothy wanted the Wizard of Oz to send her back home. But he couldn’t. He could, however, facilitate Dorothy’s realisation that getting back home was entirely up to her. She had the power to do it herself, all along.

I hope that we don’t give up our power to make sense of data, to direct how it helps us measure, analyse and explore our way toward our goals. No matter how much data we have, or what speed it comes at us, it’s only ever going to be as useful as we are skilled in using it.

It doesn’t matter how big your data is. What matters is that you don’t assume it can think for you.
[tweet this]

DISCUSSION:

Is big data raising its head in your organisation? Have you had success with it, or hassle?