Data analytics is now so ubiquitous that it is a requirement for success in a fiercely competitive global economy. Unfortunately, there is so much hype around analytics that people often expect that analytics are the answer, that it can somehow turn iron into gold. But analytics are not the answer. In fact, good analytics is all about raising questions and testing theories. Perhaps an example would be best…
But first let’s go on a little journey. Think back 50 years, small local businesses were thriving, salesmen spent their time on golf courses or smokey bars. Back then, business was very personal and all about building relationships.
Somewhere along the way (perhaps in the early 90s with the growth of the internet and economy of global travel) things changed and the global corporate model became the key to success. Many local businesses collapsed in a cut-throat, economy of scale. New styles of management sprung up to control the corporate beast, HR had entered its best years, there were more middle managers than school children and we recorded everything! Every transaction, every meeting, email, how we spent our time and it was all recorded and compared against our performance.
Post-Y2K saw the birth of business intelligence (BI). Companies poured all their data into data warehouses and locked it down. Specialist data teams emerged to wrangle all this data and to produce informative KPI and operational dashboards. It didn’t matter that these BI solutions cost just as much to produce as they actually generated in revenue – business was now big business and to be successful you had to embrace the information age.
The problem with traditional BI, is that in the end it really only manages to tell you what you already know. There are some very clever ways to visualise data these days, but still it boils down to tracking sales or deliveries or customer churn. And let’s be honest if it takes some glossy chart to tell a manager that sales are down this quarter or customer churn is up, then that manager should probably be fired.
Traditional BI is about observing and describing what is happening within our business. Here is a very simple example, using customer and sales data:
What can we observe in this chart?
- In general, women are spending more than men.
- Purchase amount peaks at around 40 years of age and then slowly declines for both genders.
- There is less variation in the amount spent by men compared to women.
- Based solely on this chart, the under thirties population is our least profitable market.
Now if our fictional company was a great company that wouldn’t be the end of their analysis. But unfortunately, it all too often is. There are far too many examples of companies for whom BI is simply another form of reporting and not what it really should be, which is the stimulus for strategic change.
So why is advanced analytics different?
At a simple level, analytics is about questioning the data. There are great companies out there using analytics to challenge their operational performance, be pro-active about risk management and innovative with strategic direction. At the heart of innovation is a central theory or hypothesis which is then tested, modeled and explored through analytics.
Again looking at our example, there are some obvious questions to be explored:
- Given that there is a relationship between purchase amount and age, is there a similar relationship between products and age? (Amazon springs to mind)
- What could we do to reduce the decline in purchase amount after age 40?
- Given that men appear to be more specific in their purchasing choice, could we be more specific with our advertising to target them more directly?
- Should we invest in improving our customer loyalty model to ensure that those under-thirties are converted to big spending 30 – 40 year olds?
I will be honest, I love analytics. And perhaps I wouldn’t be so passionate about it if the rest of the world was less enthusiastic, who knows? But let’s move beyond the hype and focus on the real gold. In some ways our information-enlightened society is returning to a more traditional business model where our people, our critical thinkers, our scientists and our dreamers are the ones truly driving innovation. And in some way analytics has re-opened that door to explore and dream on a scale never seen before.