Today we are creating 10 million blu ray discs worth of data every day or enough to stack as high as four Eiffel towers! However, as 90% of all human data was produced in the last two years we’re still just learning what to do with it. I think it’s time to stop talking about “big data” and instead to be clear what data you are collecting, why you’re collecting it and what decisions you will take based on it.

(Thanks to Vouchercloud for the infographic)

When meeting a company the management reporting is often a key source of insight. In the best cases the most important business metrics are on a live dashboard (often DN portfolio company Geckoboard) or sent in a daily email. Each team/function has their own view with the data they need and aggregated reports are the basis for management decisions in weekly/monthly/board meetings.

The best performing businesses work back from business objectives to identify the Key Performance Indicators (KPIs) that show they are on track or let them decide to change course. For our portfolio companies we agree KPIs at the point of investment that together with a simple P&L give us a proper overview. For example, in e-commerce we track Customer Acquisition Cost, the return rate and average order value.

What does this have to do with big data? Calculating CAC properly requires marketing spend by channel, web funnel analytics, mobile funnel analytics, CRM data, marketing attribution models, order analytics, customer service and logistics costs as well as payment data. This is a big data problem re-framed as a simple way to make better decisions. To my mind, we are now past the stage where the technical “big data” element is worth talking about and into the mature use of better data for better decision making. I can’t resist adding that enterprises wanting hosted BI should talk to GoodData (another portfolio company).

I’m a big believer that this revolution in the use of data can change business performance dramatically for the better and there is no doubt you make better decisions with better data. By focusing on delivering each incremental item of relevant data to the right decision maker (even manually at first) you’ll be making data driven decisions much faster than by chasing “big data” in the abstract.