Andreas works with socioeconomic evaluation, analysis, and impact. We talked to Andreas about quantification and conclusions made on a valid data foundation.
Can you quantify everything?
Yes. If you have the right data that is. The quality of a quantification hinges on the quality of the underlying data. A quantification can rely on good sources of data such as a companie’s financial accounts, and controlled experiments in research, or it can build on rather unreliable data sources such as personal stories and cases found in a few interviews. Both of the aforementioned and everything in between can serve as a foundation for a quantification of some kind, but the quality will vary depending on this foundation.
Should you try to quantify everything?
No. The ability to put a number or a measure on a problem is a strong communicative tool, and is therefore widely used in politics, public debate and infirm decision-making. Often the information to support a quantification is not good enough, hence the outcome of the quantification will be of poor quality.
Today’s issues with “fake news” and “alternative truths” is often based either on poor data foundation or on deliberately leaving out possible explanations to the outcome of the analysis. When performing quantifications you should always evaluate your data in order to decide whether it can sustain the calculations and conclusions, or if one should refrain from performing the quantification in the first place.
How should you as a consultant work with this?
The good consultant should be the first to underline possible uncertainties and alternative explanations to the information and learnings provided by the data and quantification. Churchill once said, “I only believe in statistics that I doctored myself”. If Churchill had hired a good consultant this quote wouldn’t be necessary, because Churchill would then have been told all the possible learnings from the statistics, and hadn’t have to doubt the statistics presented for him. It may sound like a cliché, but the consultant should focus on the role of the advisor and present all the facts, learnings, and outcomes, and leave the decision to the decision-makers. In today’s world, where the amount of data and statistics is immense and growing at incredible speed, this seems ever more important.