Blog: Finding Your Data Strategy
I've written on this topic before, from a different lens, but it's worth repeating. Whether you're a startup or larger shop, having a data strategy is essential for meeting business goals and customer needs; it's your team and company's
North Star for aligning with business objectives and customer success.
Your data strategy is your company's
North Starfor aligning with business objectives and customer success.
Where to start
Data can tell you lots of things, but without connecting your data to strategic objectives (end-goals), you may find yourself chasing your tail wondering if your team's efforts are doing anything of value; therefore, a good place to start with your data strategy is to connect your strategy's
success criteria with those of your company's strategic objectives. Effectively, look at
data as a useful tool in helping you accomplish business goals—your value prop.
Turn your data into actionable insights for helping you accomplish business goals—your value prop.
Success Criteria: 5
Once you make the connection with how you will use data to support the company's business strategy, some of your
success criteria for your data's strategy should account for the following 5-ish data
- Veracity - Accuracy of your data
- Variety - Kinds or different types of data do you have
- Velocity - Frequency and real-time of data and ability to analyze it
- Volume - Do you have high-volume of data, both in structured and unstructured form? e.g. Are you working with millions of records, or just hundres or thousandss?
- Value - Is your data, combined with the above
Vshelping solve user problems: does it support your value prop?
Note: I state
5-ish above as some teams may only use 4 of the 5
Vs. I'm sure with enough will-and-time in a day, you can come up with several more
Vs, however, these 5-ish are common across industry spaces and a good place to start.
Transparency & security
Every shop, generally speaking, has a
secret sauce for accomplishing their value prop, however, there's priceless value in being transparent with your users—internally and externally—of how your company uses data, particularly, when it comes to identifiable data. You can be transparent without giving away your trade secrets. In addition, being good stewards of the data goes hand-in-hand with transparency, so be sure to outline what you do and don't do with data you collect, including how you safe guard it.
Nurture & leverage your data
Once you have alignment between your company's strategic objectives and your data strategy's
success criteria, consider the following for leveraging and caring for your data (in no particular order):
Understand your customers and their needs over time. The more you understand customers now and analyze trends over time, the better you can use your data—insights!—to understand if your team's approach on solving a customer problem is working, or if a strategy, even a tactical approach, needs rethinking or pivoting.
Have a Data Quality Plan. Data is great, but there can be a lot of noise rather than signal (value) if your team doesn't nurture it on a regular basis. In addition to the
5vs, keep in mind: 1) data completeness, 2) consistency, 3) uniformity, 4) timeliness, and 5) data-type constraints. Also, if you're team has to do the occassional manual maintenance of the data, keep a log of what maintenance was performed and when and by who did the clean-up effort.
Analyze and adapt - Regardless of industry, there's always room for improvement. Whether it's in-product, operations, supply chain, etc., something can always be fine-tuned to perform better than before. Use data insights to reveal to you and your teams the often hidden stories of what's real going with your company and users and adapt accordingly to continously improve.
Regardless of your company's size, develop a data strategy; one that reveals and leverages insights for solving your customers' problems. We were successfully at Tesla in leveraging a data strategy to reveal insights for effectively scaling and streamlining product and operations worldwide, and I'm fortunate to now be on another team—Loop—doing the same in the B2B SaaS space. I hope the above is helpful to some folks looking to develop or simply re-assess their own data strategy.
better data = better decisions, so nurture your data so it's free from noise, including bias. The latter, I'll save for a follow-up post.
I am a problem solver: a tech and people leader with a passion and proven track-record in building and leading empathetic, productive teams—remote and on-site—within a continuous learning culture, while championing usable, inclusive digital products and online experiences. I am also a father, advisor, life-long learner, advocate, community builder, and speaker—I am Human. Learn more