Good Data vs. Bad Data Strategy
What makes or breaks the data strategy inside companies?
This is the Three Data Point Thursday, making your business smarter with data & AI.
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Let’s dive in!
Strategy is your “master plan.” Your business strategy is how your company thinks to reach its goals; it’s a set of steps and “if-then.” It’s the high-level initiatives your business uses to grow.
…. Now, a data strategy is the steps and initiatives your business takes to use data to the benefit of the business at a high level.
Most people think data strategy is the responsibility of the data people, data leaders, the CIO, or the CTO. But that’s just bull. The role of CIOs, CTOs, and data leaders is to guide good data strategy development and ensure it is implemented well.
So, let’s talk about what a good data strategy is …
A good data strategy is aligned with the company strategy. It is aligned because it is derived from it! A good data strategy exists in a company with a clear direction from the top to make data the most important thing.
A bad data strategy is on its own. Without connections to other departments, only tangent to the company direction. With a bad data strategy, data people complain about always being blocked by other departments.
A bad data strategy tries to revolutionize a company that doesn't want to be revolutionized.
A bad data strategy is driven & written down by the CTO, CIO, and the data people.
A good data strategy is driven by all leadership by product management, with the support of the CTO, CIO, and the data people. It’s the data leadership that helps the rest of the company to put a good data strategy into the business strategy. They guide, help, facilitate, and then ensure great implementation.
A good data strategy is all about people & users and helping them make decisions better. A bad data strategy is all about data products, datasets, dashboards, reports, and ML systems.
A good data strategy helps to drive up margins and creates a competitive advantage. A bad data strategy wastes resources.
With a bad strategy, data people are frustrated with the missing support of the rest of the company. With a good data strategy, data people focus 100% of their time on getting that support before doing anything else.
A good data strategy starts with the most unsexy word: "data democratization,." Helping people to use data. Bad data strategy starts with ML, AI, tools, a modern data stack, or BI. With bad data strategies, data teams fight to get PMs to use BI tools, they fight to convince them to use hypotheses to make product decisions, and everyone ends up frustrated.
With a good data strategy, PMs wish for better data to make better data-heavy products. With a bad data strategy, data-heavy products don't make it onto the roadmap.
With a bad data strategy, the data shapes the strategy.
With a good data strategy, the business shapes the data strategy that shapes the data. With it, you're willing to spend money to collect/buy data because you have a profitable plan!
The bad data strategy is extensive. A good data strategy is plain and simple.
Companies with a bad data strategy hire data scientists first and then wonder 2 years later where that investment leads.
Examples of plain great data strategies
Amazon:
Feed data into the recommendation engine, the “what others also bought” and the “because you bought X” engines.
People buy more things (yes, that’s proven) <= business strategy!
More data is available to….
Feed into the recommendation engine or develop more recommendation engines.
Note: If you want to be fanzy, look at the Amazon Flywheel. You’ll notice the data strategy is a Flywheel that fits right into that.
Netflix:
Feed data into “others also watched” or “here are 10 movies hot in your region today” algorithms
People watch more of these things and provide feedback to these algorithms
More data is available to….
Feed algorithms and build more algorithms
Spotify: I think you get the idea by now that the more people listen to music => the more music to recommend via data power.
So what?
These companies have data strategies tightly woven into their business strategy, not because of an accident but because they put in the work. The AirBnb founders realized from day one that they needed to tightly integrate data into their decision-making.
They hired their first data scientist, Riley Newman, as employee No. 10, back when this wasn’t common at all.
There is no ground between good and bad data strategy; there is just a vast chasm. If you want to make data work, you’ll have to work hard and integrate it deeply before you begin with any of the fancy stuff.
So, dear business leaders, don’t leave it up to your data people to develop a data strategy. Dear data leaders, don’t mistake your role; it’s facilitation, not a solo act.
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