Previewing the Mining Your Own Business Podcast

Elder Research is launching a new podcast in early April 2022 where Director of Analytics Strategy, Evan Wimpey, will be interviewing commercial data and analytic leaders.
Author:

Evan Wimpey

Date Published:
March 28, 2022

Not Evan’s actual Gameboy, but it could have been.

Not to date myself, but Pokémon debuted on GameBoy when I was in the 7th grade. I had a GameBoy, but I had no interest in Pokémon. There were a few kids that played in school, but I was interested in other fun games, like Donkey Kong and Dr. Mario.

As the months went on, I began to notice that while fun was often the means, the end for these games was social capital: on the playground, in the lunchroom, but most importantly, on the bus.

The bus was where we talked about games and being good at the popular games was a powerful tool. When Pokémon’s popularity began to skyrocket, anybody who was anybody begged their parents to buy them the Pokémon game, and subsequently lots of AA batteries for their GameBoy.

For anyone who wanted to sit nearer the back of the bus, the solution was clear: get the game and spend time playing it. That gave you more Pokémon, stronger Pokémon, and more clout with the “cool kids” on the bus.

But what about when the solution isn’t so clear?

What if there are so many ways that you could fail?

 

Even with the game, some people wasted time and money on it and still fell farther from the inner circle.

How Does This Relate to Analytics?

This incredible stretch of an analogy is how I see analytics in the corporate world today. Analytics can provide incredible insight, leading to more and more firms spending escalating resources on the capability. So, if you want to remain competitive as a firm, the solution is simple, right? Just “do” analytics. Just spend the time and money. But it isn’t that easy.

In fact, you might conduct bad analytics that are detrimental to your firm’s goals. Most common of all, one puts time and resources into building analytics that never actually impart any change in the way decisions are made.

Just as there were popular kids that figured out the “secret” of Pokémon sitting in the back of the bus, there are companies that have benefited greatly from analytics.

Hiring data scientists and building a machine learning model is only one step in a very complex process. Even the best models need to drive change to be useful, and no model can do that in a vacuum.  As one of my colleagues says, “Deploying [analytics] is more than just a technical process—it’s an organizational process”.

To realize the potential of data analytics requires more than throwing data scientists at your company’s problems. It requires embracing the change that analytics brings.

It all comes back to...

In 2016 Jeff Deal and Gerhard Pilcher wrote Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics.

The book highlights the fact that for analytics to be successful in an organization there must be a “durable bridge across the quant/business culture gap”.

The book is a great overview and a useful reference for teams that aim to drive value from their data. Organizations across many industries have used it to help shape their analytics efforts. While there are several example stories of success and failure in the book, wouldn’t it be great to hear directly from the people that are on this great journey to implement analytic solutions? What are they doing now in their organization?

See in the New “Mining Your Own Business” Podcast

That’s what we’ll see in the new “Mining Your Own Business” podcast. The host (yours truly) will be introducing you to an array of commercial data and analytic leaders.

I’ll have conversations with innovative data scientists, engineers, team leaders, managers, directors, and executives that we are excited to learn from. 

These are the people that are responsible for building an elegant technical solution and getting it implemented to drive real change. Some guests will have highly technical backgrounds, some will be more focused on change management, but they will all be working to transform data into decisions.

I hope you listen in as leaders talk about how analytics are tested and used at their company:

What types of challenges are they tackling?

How are they building solutions?

How are they implementing analytic insight?

These are the important questions leaders face as they “mine” their own business. This podcast will provide an inside look at how mining operations can succeed…

And if there’s time, we’ll have Pokemon battles.