Operational metrics help you observe the day-to-day functionality of your business and determine whether you’re on the right path to achieve your long-term goals. However, it’s easy to make mistakes when measuring and reporting on operational metrics.
The Basics of Operational Metrics
Before diving deeper into the topic of operational metrics, consider reading an introductory operational metrics guide – especially if you’re not familiar with how these metrics work.
It’s important to understand that operational metrics aren’t the same as strategic metrics or performance metrics; instead of tracking your business’s long-term goals, you’re going to be tracking the operational function of your business in pursuit of those goals.
For example, in the marketing world, instead of tracking revenue or return on investment (ROI), you might track cost per click (CPC) or lead-to-opportunity ratio.
Top Mistakes Made When Measuring Operational Metrics
These are some of the most obvious mistakes companies make when measuring operational metrics:
1. Tracking the wrong metrics. One of the biggest mistakes is a somewhat obvious one to an outsider, but when you’re immersed in this field, you might not realize you’re making it. Tracking the wrong metrics can waste time, or worse, lead you to make poor decisions for your business. Some operational metrics are strictly better than others; they provide you with more meaningful information and are more closely tied to your performance metrics and long-term goals. Be judicious and discerning when choosing which metrics to track, and make sure you can objectively justify why each variable is being included.
2. Measuring everything. Conversely, some businesses suffer because they want to track anything and everything. On some level, more data is a good thing; it means you have more information and knowledge with which you can make better decisions. But it’s also possible to be flooded with irrelevant data points. If you have too many metrics to track, you could end up wasting time. If you’re tracking things that aren’t relevant to your bottom line, you could end up making false conclusions. Instead of measuring everything, focus only on your most important operational metrics.
3. Using bad data visuals. Data visualization is popular for a reason. With proper representation, visuals can make data much easier to understand and communicate. Unfortunately, not all visuals are appropriate for all sets of data. If you use bad data visuals, such as inappropriate charts or misleading representations, it can distort your data and lead you to bad conclusions. Don’t assume that all your visuals are a net positive.
4. Reporting inconsistently. If you want to be effective in your operational metric analytics strategy, you need to report consistently. If you only look at your data periodically, or if you don’t look at how your data is growing and changing, you’re not going to have your finger on the pulse of your organization.
5. Falling victim to confirmation bias. Confirmation bias affects everyone. If you’re not careful, it could completely distort how you think about your operational metrics. Instead of trying to prove your initial assumptions, try to disprove them; looking for contradictory and challenging pieces of evidence will lead you to stronger conclusions.
6. Comparing apples and oranges. When comparing two different sets of data, make sure you’re comparing apples to apples. If there are too many variables at odds with each other, you won’t be able to compare these sets effectively. As a simple example, you wouldn’t want to compare today’s transportation costs against last month’s average delivery time; these are totally different metrics that don’t necessarily correlate. You may have to manipulate the presentation of your data in some ways to come up with a more appropriate comparison in some cases.
7. Never updating your operational metrics. When you first start tracking operational metrics, you’ll probably choose a dozen or more core metrics to track. Should you keep tracking these, and only these throughout the course of your business development? The short answer is no. You should be constantly updating your operational metrics, including new metrics and eliminating ones that are no longer relevant to you.
8. Failing to make your insights actionable. Finally, make sure all your insights are actionable. It’s fantastic to learn new things by analyzing your data, but those new things are only going to be valuable for your business if you act upon them.
If you can avoid these common mistakes, you’ll be in a much better position to measure your operational metrics consistently, accurately, and effectively for your business. Remember that this is an ongoing process; you don’t need the master the art of data analytics the moment you adopt a thorough analytics strategy.
Instead, you need to gradually and iteratively refine your approach so you can see better and better results over time.
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