Assumptions About Metrics Can Derail Your Business

Getting an accurate, complete, and up-to-date understanding of a company’s business status has always been a vital part of running a business. And what better way to get that information with proof points generated by Big Data analytics? After all, you can use analytics software to plow through the mountains of data your business collects. Then, you can measure practically anything you need to know.


While helpful, overreliance on metrics can undermine a business’ health. Used without understanding human nature or attention to human judgement, metrics can lead to an inaccurate assessment of business health. Avoiding these dangers requires an understanding of what analytics can and can’t accomplish for your business. Here are three scenarios, in which false assumptions lead to harmful decision making.

Metrics are all you need for a solid business case.
Business metrics are standardized measurements of a company’s performance. Their function is to answer two critical questions: “What’s happening?” and “How are we doing?”

The main question is, can metrics alone be relied on to give a complete and accurate understanding of your business status? Probably not. Usually, you must add human judgment and experience to provide the Big Picture that supports effective decision making. Context is key. Metrics are snapshots, indicators of a system’s state or process performance. Successful decision making requires intuition and experience to flesh out the framework that metrics provide.

Users always handle data accurately and honestly.
There are several scenarios that disprove the saying that numbers never lie, an assumption that can do serious damage to a business. First, there’s the age-old problem of data providers consciously manipulating data to route resources or stakeholder support in a specific direction. Cherry-picking data or using out-of-date statistics to support a business case are just two ways to put the finger on the scale of honest analysis.

Users always understand and interpret data accurately.
Then, there’s the possibility that data providers (or consumers) don’t accurately interpret the data provided or understand its underlying principles. There’s nothing up anyone’s sleeve. Readers just don’t take away an accurate impression of business conditions.

For example, business users can misinterpret predictions based on research and past results as fact. Another common mistake confuses correlations (Events A and B occur at the same time) with causality (Event A caused Event B.) Intervening variables that occur in the marketplace or a company’s business operations might be more accurate causes to specific trends or changes. However, they must be identified and measured if they are going to provide useful business insight.

There’s no harm in focusing on easy-to-measure data.
Big Data analytics enable analysts to take a deep dive into customer, operations, and other types of system and process data. The sheer power of Big Data analytics makes it possible to discover and analyze business performance in ways that business leaders of earlier decades never dreamt of.

Nevertheless, many organizations still tend to focus on a limited range of metrics, which are easy to measure and understand. Quantitative data does the heavy lifting when it’s time to describe what’s happening at selected moments. Describing why this is happening through time, however, often requires attention to qualitative measures or a combination of the two.

Getting an accurate picture from hard-to-measure data is difficult. That’s why companies often focus on the easy-to-quantify metrics and leave the squishy, qualitative data alone. Nevertheless, taking the easy analytical road can do harm by:

– Diverting employees, whose performance is measured, to easily measured work activities. This scenario includes employees, who become less productive by spending time entering data rather than doing their jobs.
– Creating a “short-term” mentality, which emphasizes easy-to-measure performance (quarterly earnings, for example) at the expense of promoting a business’ longer-term health.
– Discouraging innovation and risk-taking in product and service design, creation, and support. Worrying about today’s numbers can squelch opportunities for value growth throughout the product life cycle.

So, while metrics provide the framework of a solid business case or status report, misusing them or relying on them alone is looking for trouble. Providing business owners with a robust look at your company’s business requires stamina and an open mind (that avoids assumptions), but it can be done.

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