The Idol of Data

We worship data, use it to make life-changing decisions, settle arguments, form opinions and justify actions. Data is great because it is perceived as definitive; in a complex world we gravitate towards the certainty that data provides, be it articulated in a long-form article or displayed in a professional looking infographic. The danger of making data into an idol is that, much like idols past, our objectivity becomes clouded with a certainty that undermines our ability to make good decisions.

An example comes from the world of impact and ethical investing. Last week saw a report by Fortune, ranking the top 50 companies that Change the World. It put JP Morgan ahead of Leapfrog Investments, Jo-Gek and bKash. There is no doubt that this data is accurate, based on the methodology used, however this data provides a misleading picture of what it means to be a world-changing company. The Fortune 50 list makes some fatal errors when presenting data that should be avoided at all costs.

  1. It’s light on methodology

Not everyone wants to get into the detail, however we should all have the ability to do so if we choose. I discard any data that does not come either from a very legitimate source (think World Bank) or is not supported by a coherent methodology. There is, of course, a happy balance to be struck. At Util, we provide lots of detail relating to our methodology — not everything, but certainly enough for the uninitiated to understand to the extent that value can be gained from our data.

2. It’s deficient in composition

I want to be able to break headline data down into the ‘sum of its parts’. Although headline data often tells a coherent story, without knowledge of, or access to the composition of the data, I cannot make reasoned decisions based on this headline data. We see the Legatum Institute’s Profitability Index, the Footprint Network’s Open Data Platform and Global Perspectives’ Indigo Score as leaders in the presentation of ‘sum of the parts’ data presentation — all of which feature in Util’s methodology.

3. We don’t know who the intended audience is

Data presentation and visualisation is very difficult if you don’t have an intended audience. Data is only powerful when integrated with context and direction. If you don’t spend time thinking about a target audience, your data, however interesting will fail to land and will, in some cases, end up in the wrong hands, resulting in divergent audience actions.

4. The output is linear

A rank is a simple and effective way of presenting data and it often tells a useful story. However, without access to the underlying data we are left none the wiser as to whether the difference between company number 1 and 2 is the same as the difference between company number 49 and 50. The key, once again, is to provide access to the data that lies behind the list, acknowledging the limitations of a rank to your intended audience.

We are puritanical about all stages of data gathering and believe that our industry will move from the sidelines to the mainstream only when decision makers can rely upon data to make effective decisions. When lists like the Fortune 50 gain publicity at the expense of robust ESG and impact analysis, our industry is undermined and the idol of data becomes discredited.