Last month, I talked about some of the lessons I’ve learned over the years and how they apply to my company’s analytics journey. You’ll see a theme continue as I wrap it up this month. None of my lessons are about technology. As I said, technology is easy; it is people that are complicated.
Lesson Five: When it Comes to Governance and Architecture, “Just Enough” is Better than More
I touched on governance last month. We need our analysts and data scientists to utilize quality integrated data. To get a handle on how we might manage that, we piloted a data governance process with our Human Resources department. It’s surprising to learn how many definitions existed for something as simple as Full Time Equivalent staff count. It’s not rocket science, but it’s not easy either. Together, we worked through the issues and definitions we needed to clarify HR data. We think the approach we took will work for other parts of our business by substituting the appropriate subject matter experts to work with IT to define and cleanse the data to be analyzed.
"We want our data scientist(s) to be able to use tools they are familiar with. Their expertise is more important than what tool they use"
We defined our enterprise data warehouse as the “single source of the truth” and we standardized on a set of tools for report writing and analysis. However, when it comes to advanced analytics, I feel data scientists trump standards. We want our data scientist(s), whether on staff or contracted, to be able to use whatever tools they are familiar with. Their expertise is more important than what tool they use.
My philosophy has always been ‘just enough’ when it comes to architecture, governance or controls. We’re applying that philosophy to analytics. The trick is hitting the sweet spot. Whether we have or not remains to be seen. But if we don’t, we’ll adjust and move on.
Lesson Six: It’s Amazing What can be Accomplished if Nobody Cares Who Gets the Credit
I’m fortunate to work for a company filled with folks who believe this. Our CEO says it often and lives by it. And while it’s human to feel pretty good when you’re recognized for a job well done, individuals or teams who allow recognition to become their primary motivation will likely experience frustration and limited success.
So who is leading our analytics effort? You might argue that it’s me. The CIO should be doing that right? But as I said earlier, I’m not alone. IT certainly has a key role to play. We’ve established a platform and we consider ourselves to be the primary data custodians. Today we have a dedicated analytics support team in IT but we partner with our Strategic Management and Continuous Improvement team. Our data scientist is helping us all learn the amazing potential analytics has to improve our business. Our Transmission and Distribution manager is a self-described data geek. Our ultimate goal is to not build an analytics organization in IT, or anywhere else for that matter. What we want is for analytics best practices to happen in every business unit. We want analytics to become part of who we are.
Lesson Seven: Relationships Matter
Here’s another strength of my company’s culture. While we may still have some silos, there are no barriers to working across organizational boundaries. Perceived barriers are probably self-imposed. I know our executives. I know our department heads. I know many of our subject matter experts. We know each other and we respect each other. Analytics, like every other initiative works better if relationships like this exist. If you’re going to go talk to someone about analytics it’s probably better if it’s not the first thing you’ve talked about. And if some of those conversations were about their home brewing hobby, or guitar recording, even better. While not productive in the moment, getting to know one another, makes lots of things easier.
Lesson Eight: There’s no such Thing as too much Communication
While I consider this to be one of my most valuable lessons learned, I repeatedly fail to live up to it. At this point, our analytics effort is significantly under-promoted. Somehow, and I expect I’m not alone, I manage to operate as if other priorities are more important even when they’re not. So the team is helping me remedy that this year. We’re making the rounds presenting and demonstrating our analytics platform. We’re training folks in the use of standard tools and our Data Scientist is training select individuals in the use of more advanced tools. Rest assured, no matter the effort, it won’t feel like enough.
I’m sure you can tell that the lessons learned I’ve referenced aren’t really about analytics. But I have some good ones left over that are worth mentioning so I’ll close with them. I think they’re good for CIOs but apply to everyone.
A career is a marathon, not a sprint. Make sure you’re heading in the right direction, and if so, keep moving and never give up. Focus on your strengths instead of your weaknesses. You can spend a lot of time on weaknesses and maybe make some incremental improvements. But sometimes weaknesses are part of who you are. Better to spend time capitalizing on your strengths while always acknowledging your weaknesses. Don’t take yourself too seriously. Learn to laugh and when you’ve made a mistake, understand you just gained some wisdom. Our analytics program is by no means advanced. We’re probably no further than midway on the analytics maturity curve. But it’s headed in the right direction. We’re better than we were last year and I believe we’ll be better next year. I hope that’s true for me as well.