When building a data science team, pay close attention to the legends that informally rule your company. Also, learn how to write legendary stories into your strategy.
Catalog the company's legends
I suggest you and your change leads intentionally catalog your company's legends. This exercise will not only serve you in your current strategy, but it will continue to pay dividends for a long time to come. The informal system that runs your company is inconspicuous, so you must be alert and assiduous in this exercise.
First, note the informal leadership structure by paying close attention to whom people follow, regardless of title or position. Then, ask these informal leaders about the stories that have been handed down through the years. It may take some time because this isn't something people consciously think about, but it's important to make a record of and then analyze these stories. You're looking for morals, heroes, and why these stories are important.
When I first started consulting for Sun Microsystems in 2004, I was excited to learn the company had a Six Sigma Center of Excellence and a lot of Black Belts. However, I found that not all departments embraced the idea of Six Sigma. As the story goes, Six Sigma rolled into Sun like a bulldozer, and senior leadership required every manager to become a Black Belt. This engendered an epidemic of frivolous projects whose sole purpose was to get their leaders certified (it's a requirement for Black Belt certification to run at least two Six Sigma projects). This left a bad taste in many mouths, and these stories formed a culture of Six Sigma resistance in many departments. If Sun was around today, and I was a leader trying to launch a strategy that incorporated sophisticated analytics, I would be remiss if I didn't take this Six Sigma history and the stories that go along with it into consideration.
Write your future's history
Making adjustments based on the legendary stories of the past isn't the only way to leverage the power of stories -- you can write the legendary stories of your future by crafting them today. Your strategy has a horizon in the future. And although two years is the new 10 when it comes to strategy, as a leader you must continually keep your focus at the future endpoint.
This is what it means to write your future's history: consider what your legendary stories should be when your strategy is in full swing, and start putting those stories in motion. When your strategy unfolds, you'll need your culture to support analytics and the data science team that's delivering these analytics -- to the organization, the marketplace, or both.You'll craft policy and procedures to formally support your efforts; however, they won't be effective unless you engage the informal system, which is supported by informal leaders and the legends they share with their followers.
To do this, write these stories into your strategic execution and choose your heroes, your maxims, and the outcomes that will make these stories significant. You can start with an easy target and take a small win, and then leverage the momentum into bigger wins. With each win, make sure the story is known and recorded, especially with the organization's informal leaders. This is a technique I call analytic magniloquence, which is a fancy way of saying brag about your analytic successes and make sure your heroes take credit for the wins.
For example, imagine you're the leader of an auto manufacturer that wants to create an analytic service where its cars send diagnostics to the cloud, and customers get real-time maintenance feedback sent back to their console. As a small win, you target a risk-based maintenance monitor that records driving habits and some basic diagnostics from the car, and alerts customers when they should come in for maintenance. Before attacking this small win, write the story of how the analytic team (under the guidance of your analytics manager) brought the company into the future with a cloud-based maintenance program that nobody's ever seen before. Then, when the strategy takes its first small success, make sure key informal leaders like the Director of Service, share it with their people and give your data science team their due credit.