by Andrew White | September 29, 2016 | Comments Off on In Search of Meaningful Metrics – Part II
The alternative title for this blog is, “The Difference between Data and Analytic -and it makes a big difference.”
In the US print edition of today’s Financial Times there is an article titled, “Japan rethinks GDP data on accuracy fears.” This important article highlights an issue that the Bank of Japan (BOJ) is wrestling with the countries 2014 stated GDP data. It was originally reported as a contraction of 0.9%, and due to some issues, GDP might actually be under-reported and the real figure might be nearer a growth number of 2.4%. This is a frightening development. But let’s first understand the issue.
Like most countries GDP is not a detailed analytic. It is developed through several different systems and processes. Let of the data is systematic in that product and sales data are recorded from tax receipts and trade data. But this data is not up to date not does it cover the whole economy. Much of the insight comes from surveys sent to private business seeking input into what is going on. It turns out that the response rate for these surveys in Japan has been falling and so the BOJ authorities have to make assumptions. It seems that upon looking back at more and more data that trends to accrue over time suggests that those assumptions might have been wrong.
I have written about GDP before (see Secrets and Lies: The Fed and our GDP analytic, April 2016), both its history and its usefulness to the US authorities in measuring our own economy. In that previous analysis I called out the way in which GDP is used. Japan is no different. What is worse is that Japan’s economy and its use (and exploration) with negative interest rates and quantitative easing is seen as a bellwether for other central banks.
Many economists have assumed that the extreme monetary polices in Japan have most their fervor and that economic growth has not returned. This may not be the case. It seems we just don’t know. More importantly for other economies central banks have started to wonder if their policies have really lost their strength in driving growth. Such a re-statement by Japan may force economists to again rethink what is going on around us.
So the challenge here is that data powers analytics, and if that data is bad or at risk, so the analytics is at risk. The result is that decisions taken may be incorrect or ineffective if the insight driving them is of poor quality. The distinction between data versus analytic is critical in digital business, especially since so many folks confuse:
- Data and analytics
- Analytics and decision making
- Decision making and execution
We tend all to jump toward silver bullets and the first part of each of the three pair listed above. As a result our ‘solutions’ tend to be incomplete.
- Data needs to be governed effectively for all uses, not just in analytics
- Analytics provide insight to guide a decision and its alternative pathways; they are not the same thing
- Taking a decision is not enough; success is measured in the outcome (i.e. execution) and feedback from it to inform (e.g. new data)
Our new Data and Analytics Platform (see Mastering Data and Analytics: ‘Table Stakes’ for Digital Business) seeks to address this comprehensive viewpoint.
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