In an ideal world, when you create an amazing plan to build a world-class data stack, your coworkers' minds would be blown, your company's CEO would thank you for your brilliance, and you'd start on your new datafantastic adventure.
In the real world, that's not how it works. Once you've gotten sign off for your data stack proposal, you've got to get buy-in from your Higher Ups before you start building.
In this article, we'll walk you through everything you need to consider to secure the kind of support you need to help your company’s data warehouse succeed.
If you've never had to sell a big project, it may not be obvious to you why winning upper management support is so crucial to the success of a data warehouse project.
Think of it this way: winning high-level buy-in is like taking out insurance.
Building a data warehouse is a fairly complicated project. Along the way, you're inevitably going to run into bumps in the road. Some of these problems you'll be able to handle yourself. But some of them will require having the backing of the Higher Ups.
For example:
If you hadn't spent time locking down high-level support, these problems could derail your data warehouse project. So protect yourself by investing a little time upfront to gain the support you may need down the road.
There are three types of commitments you should obtain from your Top Brass: a commitment to a shared vision, the resources to execute it, and a willingness to negotiate in good faith.
One of the most important parts of the commitment you need to get from the Higher Ups is a rough consensus on how your data platform will serve your company's needs.
For example, is your goal to make virtually all analytics work self-service? Or will much of the work be handled by your team?
You will have figured out some of that while analyzing your business needs, but whatever the right balance is, you need to secure a commitment to it from the key players. If not, when the going gets rough, the wheels on your data cart are going to spin off in radically different directions.
You'll also need a shared commitment for resources.
That includes rough agreement on how much money you can spend, how much time the project will take, and how much staff time you can count on.
Let's say the Higher Ups want you to create a system that's mostly self-service. Self-service won't work if the departments you’re supporting won't invest time in getting trained up. And if Marketing intends to do more intensive analytics work, they'll need to commit to making their staff available for even more training upfront as well at least a little ongoing training every year.
A shared vision and a commitment to resources are pretty obvious places where you need Higher Up buy-in. But there's another commitment that's less tangible but no less critical: a willingness to negotiate and compromise.
For example:
One of the trickier aspects of building a data warehouse is ensuring that both your peers and the Higher Ups have reasonable expectations about the project. The key to successfully managing expectations: make sure that from the beginning everybody is on the same page.
Setting expectations at the beginning won't be very helpful six months from now if you don't write them up. For that matter, if you don't document major decisions about your project, you can't be sure that all of the Higher Ups had the same understanding.
Large companies try to address this problem by creating lengthy "project charters." You don't need to do anything so formal. All you need to do is briefly, clearly document any critical decisions.
However you document expectations that the Higher Ups agreed to, you're probably best off if you can use an approach that fits with your corporate culture.
For example, if your CEO tends to enshrine key decisions using something simple—e.g., "our five values" or "our three commitments to our customers”—use the same format and language.
Why? Because your goal isn't just to document expectations, it’s to make sure that everyone is crystal clear about what they've signed up for. The more your document mirrors how senior staff are used to making commitments in writing, the greater the odds it'll help you gain some traction if you have to push back against unreasonable expectations down the line.
Getting high-level buy-in can be tricky, but it’s essential. Thankfully, you can make the process easier by using these simple tips as guides for your own consensus building efforts.
While it's ideal to get all of the Higher Ups to sign on, not everyone is critical to your data warehouse's success—at least not at the beginning of the project.
So before you start trying to win high-level buy-in, work with your boss and other people who understand how your company really works to figure out whose buy-in is most important from the get-go and who you can bring on board once your data warehouse has racked up some early successes.
As you identify key players, it can be helpful to find out what goals are tied to their bonuses in the next year and what keeps them up at night. The better you understand where they're coming from and what their pain points are, the more likely you can tailor your pitch in a way that will win them over. And just by asking them these questions, you're starting the process of building the trust that can make the difference in obtaining their sign-off.
If you're trying to gain high-level buy-in, you're going to have to spend some time juggling the perspectives and priorities of multiple Higher Up stakeholders. Figuring out how to build relationships and negotiate compromises is a critical part of this work.
But no matter how good you are at diplomacy, at some point you may run up against the limits of what someone in your position can accomplish.
For example, if two VPs turn everything into a contest to see who can smack the other in the face the hardest, it can easily derail the consensus you need. But if you're like a lot of analysts, you may keep trying to work the problem even if it's become clear that you're trapped in Sisyphus-R-Us. At that point, it's time to have someone near or at the top of the food chain to intervene.
When I was first getting started, I hated having to bring in the big guns. I felt like I had personally failed if I had to ask for help. And I was worried that I would end up burning relationships.
What I learned the hard way is that if people are acting like unruly bear cubs, sometimes you need Mama Bear to give them a timeout.
Because a data warehouse can seem like a bright, shiny object, occasionally some Higher Ups will get sidetracked. Everyone will start from a position of asking how your proposed solution will help the business succeed. But because they aren't used to having gobs of data available at their fingertips, it's easy for people who aren’t data analysts to inadvertently nudge expectations towards "nice to have" data sets and analysis.
That scope creep is one reason why it's not uncommon for companies to invest a lot of time and money in building the data warehouse only to see little or no impact on their bottom line.
So make sure that you routinely take a step back and ask yourself, are we focused on providing access to data and analysis that will directly help the company thrive? If it feels like the process is starting to slip away from that focus, steer it back.
For any nontrivial data warehouse, you need to secure high-level buy-in from the jump if you want to increase the odds that you will succeed. But obtaining buy-in isn't something you do just once.
Data warehouses can be large, complex beasts, and what a company needs to get out of its data warehouse can shift dramatically as the business evolves. So not surprisingly, buy-in from the Higher Ups can wane over time—especially if, like most complex projects, you hit some bumps along the road.
So while the most important buy-in you get is at the beginning, odds are you'll need to do a little ongoing work to ensure you maintain your Top Brass' support. Pairing that support with an understanding that data is your product will go a long way toward creating goodwill with the Powers That Be.
Nobody becomes a data analyst because they love handling corporate politics. But with a little care and a modest amount of effort, you can ensure your data warehouse project has the support it needs to overcome obstacles and produce a powerful analytics solution that will help your company thrive.