I’ve been asked to share my thoughts about ‘translator’ roles, so I thought I’d share with the broader world! Most of my professional life I’ve been in one type of translator role or another. I began my career as a business analyst in the pharmaceutical / medical devices industry. At the time, I was ‘translating’ technology concepts between very technical IT organizations and our business areas (sales, support, manufacturing, etc.). Always, the goal was to support the business through the use of technology and to try to have all parties involved understanding some of the details.

Fast forward to today, I still have been in similar roles, but now translate between advanced analytics / data science and the business. I’ve held these translator roles in multiple industries: pharmaceuticals / medical devices, financial services, Big 4 consulting, and healthcare / health insurance.

A translator role is important for many reasons. I’d say it’s most important for true consultants, or those working in large, fortune 500 companies. The reason? Analytics and data science involve multiple parts and functions. For example, you may have someone analyze the data (see my post on ‘insights’), you then have your data scientists, and finally you have your software / data engineers that productionalize the models. Do you want your business partners talking to each of these teams separately? Do you think they would understand the nitty gritty vernacular of each of these groups? No they won’t! I learned this a bit of the hard way. Prior to my current roles, I worked in the financial services industry. I was supporting the sales and marketing function. I had a new business partner to work with that was asking a variety of somewhat detailed questions and asking for updates. Naively, I said ‘Oh for that, you have to talk to so and so. For that other thing, you have to talk to this other so and so.’ Needless to say this did not go over well.

My point? In large, complex organizations (this fits the bill for fortune 500 companies and Big 4 consulting companies), the end customer should not need to see the complexity of the org it takes to deliver a capability. That is one of the true values of an analytics translator… tell me what you need and we will make it happen. Don’t worry, that 5 teams are involved, we’ll take care of it.

I’d be remiss if I did not mention an even more important role of an analytic translator. Let’s be honest, with the advance of big data, cheap(er) compute power, the cloud and data science (AI / machine learning) truly taking off…. we are in a whole new paradigm. Not all of our business areas and partners have PhD’s in a technical discipline…. and they shouldn’t have to. To me, the most valuable role that an analytic translator can have is that of ‘guide’ or ultimately the trusted advisor. Tell me what you want to do, and we’ll tell you the options and best options to get there.

A specific and very recent example of this was when my business partner needed to reduce analytic output quite significantly to provide operators with a chance to catch up. The initial thought was turn everything off for a month. However, with the analytics team supporting the business having stormed, normed, and formed over the past year, a member of the data science team took a second look and felt comfortable speaking up. We devised a way to lessen the burden over the course of two months, instead of a one-month big bang approach, giving the business an opportunity to save ~$30M. That is real money. With the trust of incremental, small victories and straight, no BS talk, the business warmed to the idea and ultimately decided to follow our approach.

Have questions? Want to learn more? Give me a shout.