Why You Should Be Data Driven

Data Driven Consulting

Why am we data driven?

We wanted to give you a brief background of our methods of consulting. In particular, data driven consulting. There are two people who have played a role in developing that mindset in our team. Both John Snow(and no, we don’t mean the Game Of Thrones John Snow), and Dr. Arthur Conan Doyle were great influencers in our thinking. They both used data to build their conclusions. Now, we use that mindset to help companies drive their strategy and decision making.

It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts. 

-Sherlock

Data Driven Thinking is Not New

Relying on data is not as easy as it sounds. Sometimes, data states an opinion that does not match a company’s current strategy or bias, and other times it may ruffle feathers of specific teams who may be left behind if certain actions are taken. However, we are starting to see that in order for companies to maintain competitive advantage, they must make data driven decisions in order to succeed and stay ahead of the curve.

The concept of data driven decisions is not new. Yes, the usage of the term has been overstated by every public speaker over the last 5 years. Yet, we are not the first generation to rely on data to drive decisions and conclusions.

Soho London 1854 – Black bars represent cases of deaths. Notice the high concentration in the center of the map.

I recall taking my first epidemiology course and learning about John Snow. This man’s story is often one of the first anecdotes taught in an epidemiology course. In 1854 John Snow analyzed a Cholera outbreak that occurred in Soho, London. All the other experts at the time assumed it was the Miasma(bad air). John did not agree. Instead, he went around and gathered data on who got sick. Then, as you can see in the picture above. He graphed how many people got sick in what area. This lead him to the conclusion that the water from a specific pipe had gotten people sick not the miasma. He was my first exposure to data storytelling, and really, data science. John Snow wanted to make sure he had the data to support his assumption. He went and dug deeper and got actual data to support the correct answer rather than allow bias to blind the truth. This is similar to modern times when some decisions made in large companies are more made on biased opinions and politics vs. hard data driven facts. It does not allow for new ideas and theories to be pushed to the top and tested.

It is not easy to make decisions off data all the time. Especially when all the other experts, or managers believe in a complete different route. However, at the end of the day, data should always drive decisions. Not just because of big data, analytics or data science. Those are just tools, like deductive reasoning or mathematical thinking. They are used to build support for new strategic avenues, pivots and plans. If we start with a biased hypothesis and build up the facts to meet that hypothesis, then we end up like the doctors and physicians during the cholera outbreak and we end up being incorrect.

Another great data mind that came far before the invention of the first digital computer and also inspires my need for facts and data was and is Sherlock Holmes (well, we guess you could say Dr. Arthur Conan Doyle). Throughout Sherlock’s adventures he has many “data” focused one liners. For instance, “Data! Data! Data!’ he cried impatiently. ‘I can’t make bricks without clay”. This line alone inspires a lot of what drives me. It states that you can’t even start to build a strategy or conclusion without first having data. Otherwise, you are just trying to build a building without materials. You can’t even start.

Data driven decisions like data science is not just a fad word, it is a disciplined mentality. It requires turning off natural human bias, ignoring the noise, and focusing on the true cause of a situation. This is not always easy, both Sherlock and John Snow faced opposition on occasions as their deductions may have not made sense to everyone else around them. Yet, they persevered and were able to use their conclusions to actually make accurate decisions.