#232 It’s About the Value, Not the Data – Effectively Partnering With the Business – Interview w/ Aaron Wilkerson

Sign up for Data Mesh Understanding’s free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here

Episode list and links to all available episode transcripts here.

Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.

Aaron’s LinkedIn: https://www.linkedin.com/in/aaron-wilkerson-81bb21a/

In this episode, Scott interviewed Aaron Wilkerson, Senior Manager of Data Strategy and Governance at Carhartt. To be clear, he was only representing his own views on the episode. Apologies for the lawn work sounds around the middle of the episode 🙂

Before we jump in, this episode contains a lot of really good framing on how data leaders can actually partner with business people to drive to what matters for them. How do you extract what matters to the organization and to each specific business partner? And then how do you tie the data work to that? So while this episode is not heavy on data mesh specifics, it’s really important to really considering the business partner’s point of view and how to work with them to drive value for the organization.

Some key takeaways/thoughts from Aaron’s point of view:

  1. ?Controversial?: Aaron (and Scott) laid out a challenge for data leaders: have a conversation this week with a stakeholder and never mention data. We get too wrapped up in the data instead of listening and understanding stakeholder business challenges.
  2. When thinking data strategy, you should first think business strategy. At the end of the day, it all comes down to how data can support the business in its objectives, not about doing data work for the sake of data work. What are the key business goals and target outcomes?
  3. Business people very rarely care about the how of data, the sausage making. Don’t try to communicate to them about the how, focus on the what and the why. Really drive towards what are they trying to accomplish and work backwards towards what data work you can do to support them.
  4. When working with business partners, yes you can try to teach them to be more data driven. But most of the conversation should still be in the language of the business. Data work itself doesn’t drive value, how it supports business partner value creation is crucial. Make sure you understand what matters and then communicate how you will help them.
  5. Dig into what business people are measured on, their KPIs, to best figure out how to support them with data work. How others are measuring their success is a very important indicator.
  6. ?Controversial?: Data leaders really need to understand and take to heart that data just doesn’t play that big a role in the day-to-day machinations for most business people. It can play a big role in supporting their work, it’s just never going to be a top-of-mind focus for most.
  7. ?Controversial?: Coming to business people with the data first instead of starting from their business challenges and goals first – you are essentially asking them to do the work of figuring out if you’ve brought them something of value. Start from asking them what they’d value and work towards creating that.
  8. Focus on the data work supporting your business partners where they’re at – not where you wish they were – to move forward. Speak with them and _listen_ to their challenges. Then find ways to bring data in to support and improve their work-streams.
  9. When tying data work to the business strategy, while many people might have the same target outcomes, they all have different responsibilities. Really dig into what aspect the person you are working with needs to happen to best support them. Scott note: really important nuance to consider.
  10. When talking to an exec, be concise. “… here’s the challenge we’re facing, here’s the outcome we want to get to, and here’s next steps. And then are you all aligned to us?”
  11. Try to focus your data work on taking away work from your stakeholders instead of adding more things to their plate.
  12. Just because data might drive incremental benefit, it might not be worth it. Think return on investment, not just return. Data people have to work with business people to ask the question of what would actually get them to act. A 10% improvement on one aspect of their work probably won’t get buy in. Find what would get them excited to move forward and focus on supporting those initiatives with data work.
  13. By starting from the problems people have, their pain points, your business partners will be bought in that any insights you find are likely valuable. Otherwise, if it is an incremental opportunity they hadn’t considered, you need to read them in much more on the details of why the problem matters before even getting to the insight. That’s again more work for them.
  14. You will probably have to build a track record of quick wins before business partners look to rely on you for bigger and bigger projects. And that’s okay, you can get to know their general problem areas well through the quick wins.
  15. While data people often want to share everything they find, it can be a double-edged sword. Just letting people know about something can be okay but if you identify a new challenge or opportunity that isn’t closely aligned with their current focus areas, you are asking them to do more work to identify if it should be a new focus. Think carefully about whether and how to bring those up.
  16. To be able to partner well with people down the road, first make sure you “stabilize, build the trust, and get everyone kind of on the same page around … what we need to do to fix [any] leaks.” Lay that groundwork and start to build off a good foundation before trying to do large data projects.
  17. Learn to say no and to prioritize. Don’t stretch yourself too thin or you won’t deliver as well as you could and you will likely not build the trust necessary to really drive the value you want.
  18. Communicating what you’re doing – really marketing your work and success stories – is crucial in data leadership. If all you are focused on is doing the work, you won’t build the momentum and have people coming to you to partner on work.
  19. Focus on learning the language of the business. Yes, it would be great if everyone were data fluent but the main value drivers for most companies happen at the business level.
  20. RACI matrices are a very useful and important tool. Scott note: this comes up A LOT – get specific on responsibilities and ownership. Overcommunicate on both aspects.
  21. It’s amazing how important making your business partners feel seen and heard is, not even ‘fixing’ their pain points. People are far more likely to work with people that take the time to understand them. It sounds simple – and it kind of is – but it’s crucial to laying the groundwork for a good partnership.
  22. ?Controversial?: When focusing on being a data leader, when you aren’t in a conversation with a fellow data person, you need to lean in to talking in the language of the business. Too many data leaders are still entrenched in the ways of doing data instead of supporting the business via data work.

Aaron started with a bit about his background and how he’s been upping his game around better partnering with the business and focusing more on the strategy aspects – data and non-data strategy. He was hitting a career ceiling from focusing so much on the data work itself and communicating by showing people the data. Since he started digging deeper into data strategy, everything points to the business strategy, so the last few years have been about getting smarter on aligning the data strategy to the business strategy and doing data work to support key business objectives. What are the target business outcomes and how can data / data work support those?

For Aaron, when he looks at companies’ business strategies, it’s pretty rare to even see the word data featured. Maybe it’s to become data-driven but it’s certainly not ‘build a data warehouse’ or anything at the tactical level. It’s drive revenue, reduce costs, etc. So a key approach is doing the logic gap work – what do they care about and then think how data might support that. At the end of the day, they care that they get help on their key initiatives, not whether you built a data warehouse or leveraged some new paradigm or tool to drive that help.

To best partner with business people, Aaron recommends digging into their incentivization. Not just their goals but what are the measures of their success, their KPIs? How can you support them in doing a better job at what is most important to their role? Understanding what drives them will help you best understand how data work can support them, which in turn should support the business strategy. And it’s crucial to really take to heart the fact that data just isn’t that big of a part of the day-to-day work of most people inside the business. We want data to make that work more impactful but trying to get everyone to be a citizen data scientist or whatever is just not going to work or drive good business value.

Aaron talked about two different ways of bringing data to business people – starting from a data first approach or starting from the business pain points and working to the data. If you come with the data first approach, where you’ve done some analysis and ask them if this is of value, you are asking them to do more work to evaluate if it’s useful to them. That’s probably not going to win you many friends. That’s the tail wagging the dog. The business people care about certain things, start from listening to them and then working to support them via data. You want the data to make their lives easier, not to add more work to evaluate what you’ve found and for them to figure out if it even matters to their strategic objectives and KPIs.

In a lot of the same vein but from a different angle, it’s really important to meet your business partners where they are with data. Look at their work-streams and their goals/challenges and find ways for data work to better support what they are doing instead of trying to reinvent the wheel or push them in an entirely new direction. The more friction to change, the more likely even potentially very valuable insights won’t drive value because it won’t drive actual action.

Aaron made a really good point about while the organization may have target outcomes, each person working to drive to those outcome has different responsibilities – and measures of success – and it’s important to figure out what aspect they own and how you can help them specifically with data. And be concise! He said a good way to think about it is in 3 slides to get your point across: “… here’s the challenge we’re facing, here’s the outcome we want to get to, and here’s next steps. And then are you all aligned to us?” Try to focus on making sure you are reducing workload for people in most instances rather than again making them do more work to get to value. Find ways to make it easier for them to focus on more and more valuable work and automate the important but rote stuff.

Understanding business partners’ goals is only one aspect of partnering well according to Aaron. You have to understand the magnitude of an improvement that would get them to move. There is friction to change so a 10% improvement is often not going to be enticing enough. Think about Aaron’s example of a rival cable company offering you a $2/month discount to switch. And you also need to understand how would you communicate opportunities to your specific business partners to spur them to action. How do we market our data-driven insights and improvements?

While we would probably all like to make major impacts with data, Aaron has seen it’s more likely you need to put together a track record of small quick wins to gain the trust of many business partners. Once you’ve done that, they will be more ready to partner with you on bigger projects. And while you get to those quick wins, you can more easily understand what drives them and where there pain points lie so you are better prepared for a bigger project when they bring it to you.

Aaron talked about the difference between bringing up new challenges you’ve found and planting seeds for something that might be important down the road. Planting seeds – letting people know a few tidbits of information along the way – is great to lay the groundwork for future work together. But most people will _not_ thank you for bringing a new challenge to their attention if it’s not a major unknown issue or opportunity. They are focused on what they are most aligned to, they have to do more work to assess if the new opportunity or challenge you brought to them is worth their time. So consider carefully whether to bring something like that up and if yes, how. Again, try not to give people more work unless it’s of significant value to them.

To get to a place where you can work on high-impact, large data work, Aaron recommends making sure you build from a solid core. Look to stabilize what data work is already occurring, look for and address value leaks, and build trust. Then you will get to a better partner position. And look to stay away from constantly trying to generate ideas instead of listening to your business partners’ ideas. They know their business better than you do and will almost certainly have better intuition about where to focus.

Aaron also believes it’s really important to prioritize and learn to say no. Don’t stretch yourself too thin. Again, focus on stabilizing and then start to work with people on future state but don’t add too much to your plate. Saying no is an incredibly powerful tool.

Another powerful tool Aaron recommends is marketing your work internally. Many data people fall into the trap of trying to focus simply on doing good work and not sharing what they are doing widely enough. A lot of data people got in to data to focus on doing interesting work instead of heavy communication work 🙂 But it’s important for data leaders to constantly be sharing what’s going on and just communicating in general. To understand where to focus your work, you need to understand people’s needs. And you need people aligned with what you are doing and why. Talk to them about what are the top challenges, what you are doing to address them, etc. Eventually, you can increase the data fluency level of your business partners to a degree where they can help you make strategic decisions too but that only comes with constant communication.

On the topic of data fluency, Aaron believes it’s probably better in most organizations for the data people to learn the business language and what drives the business rather than trying to teach a lot of deep data concepts to hundreds or thousands of business people. The business processes are what drive value – yes, data can significantly improve the business processes but without understanding which ones to focus on and how to improve them, does the data work really have much value?

Aaron, as many past guests have also noted, really recommends leveraging RACI matrices – responsible, accountable, consulted, and informed. Get really specific on who is responsible for what – get explicit and over-communicate to make sure there aren’t misunderstandings or gaps.

While it gets said a lot, making people feel seen and heard ends up having a large impact on partnering in Aaron’s experience. “You’re more likely to work with folks who you feel understand you versus people who were talking about something … you don’t at all care about.” If you learn people’s pain points and talk to them, even if you can’t address them right now, they are far more likely to lean into the conversation and future partnership.

Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him on LinkedIn: https://www.linkedin.com/in/scotthirleman/

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

Leave a Reply

Your email address will not be published. Required fields are marked *