5 February 2018
In the field of data analysis, changes come and go at an increasing pace. It is becoming increasingly difficult to identify which changes are worth paying attention to. Is it just fleeting hype that will soon blow over, or is it something that is going to last some time and you need to buy into? We previously introduced you to the trends and now we are giving you another helping hand with a series of four blogs on privacy, accountability, strategy (including data strategy) and the changing role of analysts. In this blog: accountability; power is information.
The digital transition has made it possible to measure more and more: and this is something that most companies have started to do with gusto. After all, who doesn’t know how many unique visitors their website has and how people on Twitter are feeling about their brand? Thanks to all these opportunities for measurement, there is also increasing demand for hard figures. No longer can you get away with saying: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”
After all, information is power, right? So if we just try and measure as much as we can, we’ll end up knowing more and more… well, there is a catch. To turn information into power – or rather, insight – it is essential to be able to link data together. Which is something you are often not able, or sometimes even allowed, to do. So although we do measure a lot more, we don’t actually know that much more at all.
What’s more, there is also the hidden danger of pseudo-insights from all this fanatical data collection. An extreme and amusing example of this was cited by Tyler Vigen, who has built a website with a whole host of “spurious correlations”. Of course, we are all convinced we would never make such mistakes ourselves. But when we find a correlation that makes sense to us, or perfectly suits our plans, we all do tend to conveniently treat it as “the truth”.
In short, the trend of measuring more information unfortunately doesn’t always produce the power of more knowledge. If our aim is to know more, we shouldn’t necessarily be measuring more, but measuring more specific. Rather than starting from measuring, we should start from knowing. It starts with what you want to know, followed by what you need to measure and finally how you can measure it. The underlying principle is that you first need to know what the drivers of your business are so that you can ask the question: how can you measure it.
We see many organisations struggling with problems such as these. This produces an explosion of reports and dashboards which are intended to improve direction but merely result in more chaos and less accountability. For this we often deploy our Target-To-Data model, which shows the correlation between goals, drivers and data in a comprehensible way.
Do you want to know more about this subject? Please contact Jeanine Schoonemann using the details below
21 February 2022
Plan your calendar free and make sure you have plenty of party clothes in your closet,... read more
30 May 2018
On Monday 7 May, we were at the “Analytics in Sports” conference at the Johan Cruijff... read more