Is Analytics more an art or is it more a science? 1 of 3

PrintRecently, a friend of mine replied to a post asking me for more details about how I would analyze and mitigate risk in a business…. “the details are a little thin. As a former professor of business decision science, I would like to read more about the model building tools and techniques of how you do it.”

My reply was “That’s a great question Chris. As a blogger I try to not go into too much detail in these posts as most of my audience is relatively unfamiliar with concepts like Big Data, Business Intelligence Applications and Predictive Analytics. That said, I can think of a couple of ways to reply to your comment. I often say that Analytics is as much an art as it is a science. So, I will craft two blog response one for the artists and one for the scientists.” And then I will conclude with my own unique approach to analytics.

So let’s tackle the science angle first. In corporate and academic circles, analytics is looked at primarily as a science. You have millions of pieces of data, you take that data and you analyze it and then you use the analysis in your decision-making. There is a lot of science in this approach.

I often say that in the past two days we have created more data than we created in the entire history of human existence up to the past few years. This is big data… it’s mostly unstructured and its challenging to manage. It takes an understanding of how data is collected, stored, accessed and disseminated. This is why analytics usually starts with the IT team. They manage the databases that do all these things. SO as a scientist, you need to have a lab… in most cases this is a database or data warehouse. How easy is it to identify, inventory and integrate data in your business? Does you lab contain all the raw materials you need for your experiments?

Once you have your data, you need tools to analyze it, to look for patterns and discover new opportunities or to identify risks. There are many instruments you can use like a scientist uses a microscope. Excel is the most common, but there is an ever-growing number of analytics tools that you can use to glean more intelligence from your business. Some of the tools are very complicated and require a lot of training, other are free and can be learned in a matter of hours. SO as a scientist, you need to use the right tool at the right time to get just the analysis you need. What kind of tools are you using for analysis? What kind of tools are you using for reporting and sharing information? If you are using excel to design Powerpoint Decks to share via email, then I have news for you…. you are headed towards joining the dinosaurs. 🙂

And the final part that to me is the most scientific… applying the tools. There many methodologies out there about decision-making. You are starting to see a lot more college and post-graduate course work in decision-making… this is what my friend Chris is talking about in his comment. Having the materials and the tools are no good if you don’t have tried and tested ways of using them so you can trust the results of your analysis. If you want to get into predictive analytics to try to guess right about sales trends or market direction, you need to have a lot of science on your side.

Most businesses struggle having the analytics in place to fully understand where they have been and where they are now. Getting into a science driven way to predict the future requires data, tools and methodologies that you traditionally only find in big companies that invest in well-trained and/or educated professionals. When you have that then you can really benefit from the science side of analytics.

However, are you just as well versed on the art side of the equation? And what if your business doesn’t have the capability of investing in the same things the big boys use? How can you maximize the art side of things? Let’s talk about that in our next blog!


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