Data is a marathon.

The headline: Everybody loves a quick win. And from early careerists to the c-suite, many treat data like sprint (and then wonder why data projects never finish). I see more similarities to a marathon and advise you to prepare your organization (or data career) as if it were one.

Why it matters: You prepare differently to win a sprint than to finish a marathon. Obviously. But many teams expecting "quick wins" from data projects underinvest and underprepare... and then wonder why it didn't create the value anticipated.

The backstory...

I finished my first marathon. I wasn't fast. I walked the last 5 miles with bad knee. But I finished, and that was my only goal. I was very nervous going in. Injuries hampered my training plan. I wasn't prepared. I hated knowing there was a risk I couldn't finish.

My nerves woke me up at 3 AM before the race. A true data nerd, I sat in bed and read about running data. I stumbled across this post from Brent Dykes along with his Forbes article, Data Analytics Marathon: Why Your Organization Must Focus On The Finish. It's good stuff.

It resonated. It doesn't matter how much you prepare or how fast you start if you don't finish. Having led numerous data projects, I can attest to the cost / value curve Brent puts forth. Data is an asset, but is actually a liability until you can use it and take action.

The last mile. Nothing else matters if you don't finish. The real value of data is realized only after effective data storytelling inspires organizations to take action. And many quit, stop, or simply don't make it to the end of the "data" race to create value. But why?

Data is a marathon.

My son is a sprinter for Taylor University. Just about anyone can finish a 200M sprint - even without any training. But most won't finish as fast as he will. He's trains daily, 9 months a year, to shave off milliseconds from his time.

What can your data strategy learn from a marathon?

• You must have a plan. I started running in 2020, but started training on 1/1/2024. The difference? I set a goal to finish a marathon and had 293 days to prepare. I made a running plan with specific milestones. Many orgs have used data for years, but have never had a clear plan to achieve a defined goal. A goal without a plan is a wish.
• Every stage matters. When my son takes off from the blocks in a 200M, there aren't really stages to the race. You just run as fast as you can. In a marathon, you need to pace yourself. In your data journey, you can't skip a stage. Data quality and data governance isn't as glamorous as AI and analytics, but they're the foundation.
• Build a community. I'm a HUGE fan of Communities of Practice. People achieve more, go farther, and stay consistent when they're in a group. If your org doesn't have one, start one. If you're not in one, join in. Even if it's virtual or on LinkedIn. What surprised me most was how much people cheering on the side actually motivated me to keep going.
• Run your own race. There were 3,658 other runners, but there was only one race for me to worry about. Mine. You just noticed someone else is a head of you? Stick with your plan. It's tempting to see someone else doing something innovative with their data and constantly pivot, but takes discipline to execute a well thought out data strategy.
• Enjoy the journey. The last 5 miles were the most enjoyable for me. Walking with a bad knee slowed me down, but gave me time to soak it in. I popped out my AirPods and walked with a big smile knowing I was on track to finish. I've seen a lot of orgs (and early careerists) try to run harder and faster than they're able and fail catastrophically.

A call to action: Treating your data strategy (or data career) like a sprint? Maybe it's time to make a plan for each stage? Maybe you need join a community? Maybe you need to run at your own pace and enjoy it. Whatever it is, reflect and do something.

Disclaimer: I'm not a marathon expert. I've only run just one. But I am a data expert. If you're looking to run a marathon, seek advice elsewhere. Data, however? I'm happy to help.

Final thought: I received a note of encouragement from Brent Dykes wishing me luck on the marathon, 31 minutes after snapping a photo of the sunrise on the Ambassador Bridge. I read it while running. Believe it or not, it meant a lot. I recommend Brent's article for anyone in data (and while I haven't yet read his book, it's third in the queue on my reading list).

Data is a marathon. Encourage those running alongside you. You never know when your peer -whether a c-suite exec or an early careerist - is running on empty, recovering from an injury, or thinking of quitting the race. A couple kind words can make a difference.

Looking for past articles?

1. The story my data cannot tell.
2. Is your data on track?
3. Happy Mother's Data!
4. How to stop data dandelions.
5. Outgrown data does damage.
6. Use your data like IndyCar.
7. Is your data ready for AI?
8. Find A-HA's in your data!
9. Experiment like a data pizzaiolo!
10. Step up your data maturity.
11. Does the data tool matter?
12. Does data governance need an ROI?
13. Are you in data debt? (Part 1 of 2)
14. How to get out of data debt. (Part 2 of 2)

This article is part of my blog, Running Thoughts on Data. My first post, The Story My Data Cannot Tell, shares the genesis of my blog. The views and postings on this site are my own and do not necessarily represent those of Plante Moran.