The role of data in customer experience, digital optimisation and driving growth is expanding in mid to large Australian businesses.

The government recently acknowledged this via a $162 million investment in the Data Integration Partnership, which will deliver data driven insights to guide commonwealth programs and policies in Australia.

However, it is critical to recognise that data is not objective; it requires analysis and interpretation to generate meaningful insights. The challenge is making this subjective interpretation of data as objective as possible.

March GDP

Let’s take the March GDP figures as a case in point. Seasonally adjusted GDP growth in the March 2017 quarter was 0.3%, marginally ahead of contractionary territory. You could interpret this result in many different ways – and indeed, people did.

On the one hand, you could make a case for Australia’s resilience. An economy that records 103 quarters without a recession (not consecutive quarters of growth), is surely a resilient one – that’s no mean feat. Further to this, you could acknowledge two periods of rebounding growth, and contrast this with the shock decline in seasonally adjusted GDP of 0.5% in September 2016.

On the contrary, you would be equally correct in stating that Australia’s GDP is the lowest it’s been since September 2009 when, at the time, concerns remained over whether Australia could absorb the shocks of the global financial crisis. Additionally, you could mention GDP per capita declined by 0.1% in the March 2017 quarter, a figure that more accurately explains the wellbeing of a country’s citizens.

So is the glass half empty, or half full? It depends who you’re asking.

Bottom line for business

Regardless, it would be naïve to think we should all reach a consensus on what March’s GDP growth rate means for the future.

What we should do is be unrelenting in our efforts to accurately and effectively interpret the data available to us, and ensure we are focused on measuring the things that add value and really make a difference to customers, rather than vanity metrics.

For business, it is critical when generating a data framework to guide decision making that we ask the right questions from the outset. Data is not valuable in itself, its value comes from how we collect, handle and extract it. It’s hard work and it doesn’t always give us the answers we’re looking for, however this approach promises much more to a company’s bottom line.