Data Scientist communities have their own complex jargon; multivariate regression models, Big data engineering, Hadoop, Map Reduce, Deep Learning etc. But, unfortunately businesses do not seem to care about how complex the term is or how impressive the math is! They want the results explained in non-tech terms.
While working on Big Data & planning to implement it for the benefit of business, it is very important to explain the insights & valuable knowledge in a way that non-technical business user can actually understand.
Here is my recent experience while working on a project for one of the largest food retailers. The goal of this project was how incentivisation would help improve their overall profits.
After an extensive and impressive study, our team came up with a collection of (what they thought) elegantly done slides. They discussed deeply about variance inflation factors, Akaike information criterion that would scare even seasoned practitioners of the art.
Now the client did not have a clue of what was going on during the presentation and rushed and escalated to me. I had to work several days De-technifying the slides! And make them business friendly
More often than not, I notice that I spend 50% of the time processing and cleaning the data and 20-25% of the time De-technifying the results and tell stories. Interestingly, while I find enough doers, the story tellers who understand the subject and business at appropriate depth are rare.
Unfortunately, this skill is missing in traditional MBAs & Managers as this is not a peripheral exercise of language. A fairly deep understanding of Data Science must be coupled with a even deeper research of the client organization.
Need to rush now. But, I shall talk about my thoughts on how to solve this problem on a later post.
Article idea & guidance by - Dr Dakshina Murthy Kolluru
Script, Design & Edited by - Suman Malekani