Today, an ever-increasing amount of data is available to every business. And we all know that’s a potential gold mine — data provides insights and can help your company thrive. Given the benefits big companies reap from data-driven decision-making, it’s only logical that data engineers, data scientists, and data analysts work hard to provide access to those much-coveted insights.
With data analysis trending, though, we should look out for a common pitfall: analysis paralysis.
Analysis paralysis: a brief explanation
Are you analyzing for the sake of analyzing? Once you’ve gone down the rabbit hole of overanalyzing, you’ll quickly get stuck. The moment you reach that point, you’re suffering from analysis paralysis.
The term first came up in psychologist Barry Schwartz’s book The Paradox of Choice: Why More Is Less, in which he states that even though choice is critical to freedom and autonomy, we don’t seem to benefit from it at the psychological level.
Here’s the thing: when presented with a myriad of choices, you should compare and analyze them all. It’s very easy to get lost in complexity, feel paralyzed, and throw in the towel. Too many choices may prevent you from making a decision at all.
This tends to happen in the world of data analysis. Once you’re aware of all the things you can analyze, you will want to analyze everything. But that won’t benefit your business. First, you’ll miss the big picture because you will get bogged down in details. Somewhere down the road, you probably won’t remember why you started analyzing data in the first place. Or, worse, you’ll overlook major company issues that require your attention.
Plus, you won’t make any decisions. Think about it: there’s always “one more thing to analyze” before you can be 100% sure that what you’re about to do is correct. You’ll get stuck in an endless loop. For even if, at some point, you are 100% sure, shouldn’t you somehow validate that you’re 100% sure about that?
This type of reasoning creates a false sense of security. You’ll think a better understanding of data allows you to control everything, but in reality you’ve lost control over the real world. Besides benefits, data analysis also has its limitations: you should never lose sight of the fact that data is an extracted rather than an exact representation of the world you live in.
How to detect analysis paralysis: 6 red flags
If you hear any of the following statements in your organization, be extra alert: it might be a classic case of analysis paralysis.
- “But we have all this data at our fingertips! We should do something with it.”
- “I don’t know if this is a 1.71M or 1.72M business case. Let me collect more data so we can be more accurate.”
- “Yes, the problem still exists. The good news is, we’ve created tons of dashboards.”
- “There is no problem, as we’ve met all our KPIs.”
- “True, the building is on fire. But we have the best alarm system in the world.”
- “Let’s set up a dashboard to keep track of all the dashboards we create and every analysis we perform.”
Toward a solution: questions you can ask yourself
Whether you’re in the thick of analysis or have yet to get started, make sure you answer the following questions:
- Which problem do I want to solve? Or, what insights do I expect to gain before I can make a decision?
- Is this really the problem or is there an underlying issue that causes it?
- Is data analysis required to solve this problem or make this decision?
- Can I use easier or faster methods of analysis to get a rough idea of the playing field?