Hi folks, I’m Lisa. I want to share some tips on building a data-driven culture. So imagine you get a text in your neighborhood group chat, and it tells you that the carpool is now going to be data driven. It sounds fancy, but what does it really mean? Does it mean that that guy from Star Trek is going to be behind the wheel?
Does it mean that you’re going to have a fancy app to work with? A data-driven culture is so much more than an announcement, and the same is true in your corporation. So we’ve found there are five kind of sectors that really help make this transformation to a data-driven culture successful. The first is understanding where you’re starting from.
There’s going to be a lot of communication that needs to happen. You’re going to need to need to do some change management. And in order to help those things be successful, it’s good to understand if your company is centralized or federated. That is where does the information flow through? How are decisions made?
Where does the money come from? That’s a great place to start. And then of course, it’s always important to know your strategy. I get so excited when our clients tell us they have a data strategy. What happens sometimes is that data strategy is built separate from the overall corporate strategy, and so it’s not a holistic view of it.
So you really want that strategy to be integrated with your corporate strategy. With that shared vision of a strategy towards a data-driven culture, you can then take a look at your processes.
Investments are going to need to be made. There’s going to be huge impacts across the organization anytime you change a culture.
And so you really want to understand what that decision process is to make sure that the people making those decisions have the information they need to make good decisions. Priorities are so tough because everything’s important. But we put our best people on the front lines, and we know that they’re getting inundated from all directions all the time.
And we want to make sure that as they’re tackling things and prioritizing day to day, their priorities match yours at the corporate level. We can empower them by giving them these guidelines to help them make better decisions along the way.
Infrastructure is another piece to take a look at. Data is foundational to good decision. That’s why we want to be data-driven cultures, right? And so we need to take a look at that data and understand where it’s coming from. Make sure it’s clean data. It’s not missing. We’re not using bad data to inform bad decisions.
There’s a way to store your data in something called a data lake, and if it helps you remember, data lakes are always better than data swamps. Try to avoid those data swamps. Similarly, you want to take some inventory on the tools and technology that you have in place. How are you going to store the data? How are you going to move the data from one place to another?
Are there ways you can alert your staff when when things start to look a little goofy in the data? You want to make sure you understand where there’s overlaps and gaps in those tools and technologies so that you can make informed decisions about where to fill that out. It’s really easy to get tempted by good marketing when it comes to technology. And you want to make sure that you’re making those decisions aside from the the splash that comes with good marketers.
So once you have good data, in order to be able to derive insights from that data that you can take action on, you need to do some sort of analysis. And every organization is going to have a different level of analytic maturity.
Not every organization needs to do all the things for all the data. So it can be good to take a good look within your own organization and understand what education and experience is already there. So that is you understand what questions you want to be answering with your data. You can better partner with your internal groups. You can bring in third parties to help outsource some of that work. Or you might find ways to combine the two and have a third party work with your internal team and upskill along the way.
I think it’s really important to note here too that with analytics, you also want to right size. There are all kinds of flashy analytic tools that you hear about. It doesn’t mean they’re going to be the best solution for your particular problem.
So that brings us to the foundation of any culture. Whether data-driven or not, culture comes down to the people. You want to make sure that you’re preparing your team to be a part of this data-driven culture instead of just subject to it. So you want to build that data competence and data confidence so that when someone looks at a graph, they understand what that information is trying to tell them, and they can make critical, informed assumptions about what they’re seeing and take action on that.
You also want to make sure that when you are recruiting folks to your growing organization—because it’s going to grow if you’re a data-driven culture—you want to make sure that you’re getting the right people in the right places at the right time. So often we hear someone has a need for a data person. So they might hire a data scientist because the word data’s in that title, right? A data scientist is trained to do the analysis.
They don’t have good data; they’re not going to have their best analysis. You might need to hire a data engineer to get that data clean before you think about bringing a data scientist in. So there’s a lot of nuance in here. You want your people to be happy—you want to keep them on board. Turnover is expensive. Hire the right people in the right place at the right time.
And then you want to keep that energy going with people after this transformation to a data-driven culture. Make sure that you’re making it a part of your onboarding and really instilling in every new corporate family member that you care about data, and you’re going to drive good insights and make good decisions that are in alignment with your strategy.
So to kind of summarize, you want to have the right people following this integrated strategy. You want to make really good insights from that strategy, using excellent data to make good decisions so that your customers and team members are happy. So if we go back to the carpool example, imagine that you’re on call that that morning. You pour your cup of coffee.
You know the game plan. You know the houses you need to go to, how many kiddos you’re going to pick up so that you can plan your route. Figure out how many miles you’re going to put on the car that day so you can make sure you fill up and you have the right technology. Don’t take the small car—don’t take the Miata—take the minivan if you’ve got six kiddos.
You can make really good decisions about dropping the kids off in the right places at the right time so that it all can come back to you so you can have a cup of coffee. Celebrate your successful morning before you go on to make some really good decisions in your data-driven culture.
Thanks for listening.