How to get out of data debt. (Part 2 of 2)

The headline: If you know you're in data debt, do something. Set a goal. Make a plan. Build a system. Just don't ignore it. If you're not sure, read part 1 of 2: Are you in data debt?

Why it matters: Escaping from data debt won't happen without a Goal, Plan, and System. Ali Abdaal breaks down his G.P.S. approach in 30 seconds. Apply it to your data debt!

One thing I've learned: organizations in data debt, are in it for a reason (and most often due to not setting "data" goals). Simply telling you to set a goal doesn't help. A goal without a plan is a wish. A plan without a system is an idea. You need all three:

• Set a Goal. Define "baby step" goals you want to achieve.
• Make a Plan. Outline the tasks and actions you'll take to achieve it.
• Build a System. Put disciplined routines in place to help stick with your plan.

One other thing I learned: Achieving big goals is hard. It's overwhelming... until you break them up in baby steps to be achieved in sequence. There's stacks and stacks of big goals never achieved. The biggest stack: goals that were were never set.

A quick running update

A moment of vulnerability: I shared (for the first time) in my last article that I set a goal to finish a marathon in 2024. It's a big goal for me. I didn't want to share it.

• What if I fail?
• What will people think?
• What will I say afterward?

An update: It's less than 30 days out. I'm nervous. After a couple unexpected injuries, my plan and system were thwarted. I'm not as prepared as I wanted to be, but I'm...

Getting back on track: I set new baby step goals. I adjusted my plan. I rebuilt a system. It's not too different from getting out of data debt... unexpected setbacks will happen.

What matters most: I'd rather this goal be counted in history in the the stack of goals not achieved the first attempt than the stack of goals that were never set.

Back to data debt

What is data debt? Data debt is the accumulation of data issues which prevent an organization from realizing the full potential of its data (and must eventually be repaid).

In other words: If data is an asset, it can also be a liability. Bad decisions made from bad data. Data privacy risks due to ungoverned data. Wasted effort cleaning messy data. Missed opportunities caused by siloed data. These are liabilities.

What you shouldn't do: If you have thousands $ in debt on high-interest credit cards, you probably shouldn't invest in a high-risk business opportunity. Likewise, if you're in data debt, you probably shouldn't try to take on that big AI initiative (yet).

The solution: Baby steps. Love him or hate him, Dave Ramsey 's Baby Steps have helped a lot of families. They're not perfect. You need to consider individual circumstances. They're not a Plan or a System, but they break big Goals into goals that can be achieved.

Worth a mention: Off topic, but here they are (and Dave has a Plan and System if you're interested). I have generally followed them. I think they're a great guide to setting priorities in your personal finances. On topic, they're analogous to getting out of data debt.

How I thought about data debt

Not interested in the how? No worries! Skip to the 7 baby steps to get out of data debt.

The idea: I reflected on "the why" behind each Baby Step. What is the purpose it serves? How is it a building block? Then I applied it to getting out of data debt.

1. Save $1,000. Why? Prevent minor setbacks from being major catastrophes.
2. Pay off all debt. Why? Pay off the past before pushing yourself forward.
3. Save 3 - 6 months. Why? Prepare for the unexpected rainy days.
4. Invest 15%. Why? Plan for your future and not working daily.
5. Save for college. Why? Pass down your legacy to others.
6. Pay off house. Why? Position yourself for purpose.
7. Build wealth & give. Why? Live your purpose.

Putting it into practice: Again, it's not this simple. You probably would want to invest and collect your 401(k) employer match even if you have an auto loan. But here's the beauty of it: the baby steps make the complex, simple. Here's my attempt to do the same.

The 7 baby steps to get out of data debt.

Two disclaimers: First, every organization is unique; these goals are not. Second, these are just Goals; they're not a Plan or a System. Interested in tailoring these goals to your unique circumstances and coming up with a Plan and System? More to come and I'm happy to chat.

1. Document your data. Start here. You don't need a fancy data catalog tool. Use a spreadsheet. Inventory all of your data. Who owns it? What's in it? Who has access? How's it used? Where does it come from (and where does it go)? Why should you (or shouldn't you) trust it? This will prevent minor setbacks from becoming major catastrophes. It starts your plan.
2. Start data governance. This is probably the cause of 80% of your data debt. Time to pay it off. Because data governance isn't as sexy as AI, no one wants to talk about it. Because the ROI is immeasurable, it was probably underfunded. (By the way, does data governance need an ROI?) This isn't "how to" and data governance is never done, but starting is step #2.
3. Standardize on a platform. A data platform isn't a tool -- it's a toolbox, integrated with a thoughtful architecture. The only thing worse than data silos are technology silos. I know. That one user really prefers this tool or that one department really has a unique need. Okay, cool. But architect an enterprise platform that is sustainable -- a rainy day is coming.
4. Manage data proactively. Having investments is different than managing investments. It's scary how many organizations don't manage their data. Without master data management, data quality and observability tools, and an enterprise data catalog you're unable to prepare for your future. You're making decisions on data that you can't confidently trust.
5. Promote data fluency. Self-service BI was once the big buzz word. Every org wanted their business users to slice and dice data. I love it. It's where I started. Launching data academies and analytics communities of practice worth it! But... it's not step #1. It's like giving a jackhammer to an 4th grader on a sandy beach -- dangerous and useless.
6. Operate data driven. Many orgs hear how others are driving innovation through data and aspire to do the same. Before you do -- operate data driven. That means you're truly running on KPIs and have systemized, or even automated, your business processes with data. Don't try this before steps #1 through #5. It's a recipe for disaster.
7. Innovate & experiment. Congrats! You're ready to strategically innovate and drive your org's vision and purpose through data. You may have had a few small wins before, but you've paid of your data debt, you've prepared for a rainy day, now it's time to take on a bit of risk in how you innovate your vision and strategy. It's time to live your data purpose.

The takeaway: There's a sequence to getting out of data debt. Focus on fixing the past before investing in the future. Prepare for a rainy day before risky innovation. Manage your data and train your team before deploying tools out to the untrained masses.

What's next: I'll weave these 7 baby steps into future articles and expand upon them. I'm also soliciting input from others in my data nerd network to refine them.

Calling all data nerds! Have something to contribute? Add a comment. Whether you agree or disagree, I'd be grateful to hear your perspective. Let's help others out of data debt!

Here's why: Tris J Burns ?? nailed it in this post. Your organization thinks it is data driven, but in the trenches, you're keeping it together with popsicle sticks and bubble gum. Speak up. Be heard. Be a catalyst for change by helping your org conquer its data debt.

A final running thought

Coincidently, my marathon is in 26 days. (For those unaware, a marathon is 26.1 miles.) I've thought a lot about if I can finish. My goal is only to finish. That's enough. There's a lot within my control. My preparation. My attitude. My resilience. My determination.

And there's a lot that isn't. Injuries. Weather. Even fixing my 43 year-old dad bod isn't within my control over the next 26 days. But it was worth setting the goal.

And if you're in data debt, it's worth trying to get out. Even if you're unsure how and when you'll achieve it. Even if your strategy isn't perfect. Even if you're struggling to get support.

Start small, but start.

Looking for past articles?

This is my 14th article, but only the 3rd that is officially part of my Running Thoughts on Data newsletter. I've been asked how to find the rest. I'm grateful. Here's a list:

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)

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.