According to industry experts, enterprises that do not measure and analyze their performance in a data-driven environment, risk falling behind their competition. Companies are prone to stagnate and miss opportunities for expansion without the consistent improvement enabled by accurate, insightful measurements.
However, not all technological metrics are created equal, and a poor measurement strategy can be just as troublesome as none at all. In the hands of an inexperienced data scientist, even the best tools are meaningless, which is why modern businesses should have a well-thought-out assessment strategy related to business results.
4 mistakes in IT metrics and how to avoid them
When plotting metrics for a technology or product engineering strategy, here are four basic pitfalls to avoid:
Measuring too much or too little
When developing a technology metrics program, companies should consider their available resources as well as their organization’s ability to implement change based on data insights. Setting too many KPIs dilutes the impact of the most important measurements and makes it impossible to react to each data point. Over-measuring can also put undue strain on their tech/engineering teams, preventing them from focusing on the important metrics and activities.
Collecting too few measurements, on the other hand, can result in skewed or distorted results. Focusing on just a few performance measurements results in a lack of context, which means the insights gained from these data points could lead their company astray. Finding the correct measurement scope for the team entails coming up with a manageable figure that gives them a fair picture of their innovation apparatus.
Prioritizing efficacy above speed
Ultimately, the performance of a company is all about the bottom line. Are companies getting the most out of their ROI, generating revenues, and expanding their consumer base? Tech metrics should be developed to evaluate progress toward these outcomes, but all too frequently, the focus is on speed. Certainly, evaluating time-to-market has importance, but that value is diminished when the feature being released is defective or unimpressive.
Businesses should focus on quality rather than quantity-based metrics like velocity or lines of code; a suitable metric to assess performance quality could be the time spent on unscheduled work or rectifying earlier work.
Putting too much emphasis on local performance
While this is a problem that affects huge multinational corporations, it can equally affect small businesses. The most essential measure, in the end, is customer satisfaction; businesses should have a high-level view of this by tracking whether their service is working and whether their customers are suffering as a result of any errors or outages.
When teams focus too intently on individual performance rather than team performance, or on the success of a single office rather than the organization as a whole, they sometimes overlook the forest for the trees. Businesses should keep focused on the end goal and monitor their progress accordingly.
Failure to connect the output and the input
It’s natural for dev teams to focus on outputs, such as the quantity, quality, and speed with which features and tools are created. However, it’s critical to consider these metrics in the context of the inputs that came before them. How much money was spent to achieve a specific result? How much attention from developers was needed, and how many company resources were employed to achieve the goal? Measuring inputs allows teams to detect waste throughout the development process, allowing them to refine the system as a whole and improve ROI, as a result.