If you’re like me, you might be a little sick of folks saying stuff like “data is the new oil,” or “data is the world’s most valuable resource.”
Of course, it’s good for a business to have data in order to support decision-making and test assumptions. But all that talk about data as a resource makes it easy to forget a simple truth:
Data isn’t something you have, it’s something you do.
It’s not just about being “data-driven” or using data to 10x your business strategy or whatever other buzzwords they throw at you at trade show keynotes. Data, and more specifically data management, is simply an integral part of the operations of almost every business.
Whether it’s customer records in your CRM or bookkeeping data you use to calculate your profits, most businesses can’t run smoothly without good data management.
And in an enterprise organization, data management is a responsibility of almost every team, not just your data science or analytics departments.
In this article, we’ll discuss some good habits for data management strategy that every business should follow.
Good habit #1: Realistic goals
Messy databases are like messy closets. Some people can’t deal with the knowledge that their clothes are in unfolded piles, and so will keep everything neat and organized automatically. Most people, however, simply shut the door.
For the non-neat freaks among us, it’s important to set realistic goals. You probably don’t need to color-coordinate your sock drawer, but it’s likely necessary that you at least keep matching socks together.
What is quality data? That’s for you to decide. There’s only so much time your team can dedicate to data management, so it’s important you focus that time where it will matter most.
Ask yourself what you actually need to get out of your data, and how data quality impacts different aspects of your business. Then let these realistic goals be the foundation of your data management strategy.
Good habit #2: Naming conventions
Inconsistent naming conventions are the bane of every data analyst’s existence.
Often, businesses fail to standardize their naming conventions until it’s too late. Individual departments or team members do things their own ways, happily chugging along, until one day you have a project that requires comparing two different databases — and then end up spending weeks or months cleaning that data to make it work.
The best time to standardize your naming conventions is the day your business starts. The second-best time is right now.
Ensure your naming conventions support the goals you set for your data management strategy, and that they are documented and enforced across teams, from sales to marketing and beyond.
Good habit #3: Data management training
Speaking of enforcement, how on earth do you do that?
A great data management strategy isn’t worth much if no one uses it, and we all know that the secret to driving adoption is robust, ongoing training.
This ties into the concept of data culture. It’s important to impress upon every team member the importance of data quality management best practices, and the consequences of poor data quality.
There are whole books written about building a data culture, and entire firms dedicated to data management training. For our purposes, we’ll stick to four basic suggestions:
- Be transparent about the goals of your data management strategy
- Make sure your naming conventions are easy to follow
- Check often to ensure your rules are being followed
- Document everything
Good habit #4: Use the right tools
From CRMs (like HubSpot) to CDPs (like Segment) to ETLs (like Talend) to reporting platforms (like Tableau), there are a plethora of tools and technologies that can support your business’s data management goals.
The world of data solutions is a little blurry around the edges. There are tools specifically designed to help you ingest, clean, transform, store, organize, or analyze your data, and there are tools that claim to do all those things.
Automate data quality with new workflow actions in Operations Hub
Often, businesses get stuck using tools that can technically help them meet their goals, but aren’t necessarily the best tools for the job. You can save significant amounts of time and energy by choosing the right solutions and using them correctly.
For example, we recently helped a client transition from spreadsheets to HubSpot CRM and Operations Hub. This platform has features that let them automatically handle errors while importing data, create and enforce rules for data validation, and even model their entire data management strategy visually. Excel just can’t do that!
If it’s been a while, it’s worth it to do your research and see what solutions are available to help you achieve your goals.
BONUS: Good habit #5: Measure your success
The first four items on this list are a good enough start for most businesses. If you’re ready to go one step further, here’s what we suggest: periodic reporting on the state of your data management.
What does that look like? We suggest getting an external partner to audit your data management performance and compare it to your goals once per year. That might mean setting KPIs, interviewing the stakeholders who use your data, and testing the quality of your databases.
This kind of ongoing measurement is useful to keep up your data hygiene and keep you on track to make your data management strategy a reality.
It’s never too late to break bad habits
Whether you’re starting from scratch or you’re staring at a tangle of completely unorganized data, these good habits will help you get — and stay — on track.
Remember, data isn’t something you have, it’s something you do. It’s the tools you use, how you use them, and the way you approach your data that makes the difference between data as a competitive advantage and data as a liability.
If you need help breaking out of bad habits and getting on the right track, working with an experienced partner can give you the jumpstart you need.
Let us help you create or audit your data management strategy.
