Sabotage Your Data Strategy in Seven Easy Steps.

A prelude to chaos.

Do you want to ensure your data is a mess and completely a waste of everyone’s time? Do you want to add to the chaos? Your data and how you handle it are crucial to your organization's success. Mismanaging it can, at best, leave you lost. At worst, it can lead you to the wrong conclusions. So, if you want to ensure you fail spectacularly, read on.

1. Set as many goals as possible.

Why have just one bullseye when you can have many? They say if you aim for nothing, you hit it every time. But why stop there? Instead, make everything the target! Having the strategy that all roads lead to Rome isn’t much of a strategy. Flooding your strategy with KPIs guarantees that your analysis will drown in noise.?

You could challenge yourself to be judicious and prioritize your key performance markers, but that’s a lot of effort! Forget prioritization. Set as many goals as possible, and watch your focus disappear.

2. Ignore data governance.

Few things ensure disaster like living in data anarchy. Each department is siloed, every team uses its tech stack, and everyone handles data their way. Any request for understanding is met with an “Oh yeah, we do it this way.” In today's litigious, privacy-conscious world, any call for compliance would mean tracking down ex-employees from years ago just to find out where they hid the data. There’s no system. There’s no documentation, just a dark cloud of confusion.

Data governance is cumbersome and only worth it if you want to work together as an organization and care about your success and the success of your customers. If you let everyone do their own thing, there’s nothing you need to manage at a broader, more strategic level.

3. Use confusing naming conventions.

Naming conventions and proper taxonomy ensure clarity and longevity, but who has time for that? It's much easier to use whatever haphazard, undocumented name comes to mind. What’s even better is just calling it:

• new-kpi-412
• old_user_id
• zz_do_not_use

Be sure to not tell anyone whenever you make a change.

Keep everyone guessing, so organizationally, no one will know what’s what. Having a well-documented taxonomy is a surefire way to avoid this.

4. Misuse audiences and segmentation.

Poor segmentation excludes valuable data and skews your results. This will distort your data and cause you to draw inaccurate conclusions. When creating audiences, why bother with all users when you can just focus on those who made a purchase? This way, you don’t have to worry about the user’s experiences that abandoned your checkout flow or understand why. When it’s filtered out, there’s no need to optimize.

Segment however you like. Define audiences in your favor. Don’t worry about testing any UX changes; just implement them and hope for the best. Skew your user base in your favor. This will make it difficult to fully understand the user journey.

5. Analyze data without context.

You can easily dictate success by cherry-picking and decontextualizing your data. Always approach analysis with a conclusion already in mind. That way, you can confirm your confirmation bias! Then, that spike in sales is directly related to your campaign and not simply to the overlapping holiday. This way, your company can apply its marketing spend to your misguided conclusions and faulty assumptions.

While some might say this is poor decision-making, it is just a new form of data impressionism, where your analysis ‘brush strokes’ are simply more visible and pronounced.

Why let the data speak for itself when you can speak for it? Don’t consider context. The scope is just a barrier to true creativity. Find the attributes and metrics that best align with your narrative. Compare daily active site users and monthly revenue, with little regard to seasonality or other external factors. This is the only way to maximize confusion.?

6. Communicate poorly with stakeholders.

Assuming is so much easier than properly communicating. Poor communication and keeping stakeholders in the dark ensure that any insights are misunderstood or ignored.?

Use jargon and make things as complicated as possible. Don’t tailor your message to your audience. Make everything either overly vague or needlessly complex.

7. Set it and forget it.

Do nothing. Just assume that once things are set, no new process, system, or initiative will ever change the data landscape. Assume there’s no broader strategic business goal that could impact your prior effort. If you truly want to guarantee a data catastrophe, this is your best bet.

Never review your data. Make no changes. Conduct no maintenance. This is the easiest way to make sure no one trusts the organization's data.

Final thoughts.

An unclear, unkempt, and unsound data strategy is the surest way to make your organization incapable of making data-driven decisions. Remember, laziness is the enemy of intent. Follow these steps, and you'll turn your data into a liability rather than an asset.

Seven is just the beginning... I'm sure there are more. What are some of your "best practices"? Share your experiences.