In the world of business, averages are often used to measure and assess various aspects of a company's performance. From market revenue to customer spend to customer composition, averages are relied upon to provide insight into key business metrics. However, using averages alone can be a dangerous approach when it comes to making strategic decisions. This article explores the pitfalls of relying solely on averages and the importance of diving deeper into the component parts that make up these averages.

One of the biggest mistakes companies make is stopping at too high a level of averages when analyzing their data. While averages may provide a general overview of a company's performance, they do not necessarily provide a detailed understanding of the market, revenue, or customer base. For example, reporting that the average company spends $1,000 with your business may seem informative, but this figure could mask important differences in spending habits across different types of companies, industries, and geographies. Without examining the component parts underneath these averages, businesses are forced to make assumptions or presumptions about the nature of those averages.

To avoid these dangers, companies need to use segmented averages to gain a more comprehensive understanding of their data. This means breaking down averages by size of company, industry or geography, or by the types of products used. By doing so, businesses can identify which sub-averages are most relevant and meaningful for their strategic development.

It is essential to examine the state of the average company in an industry versus the average company in your customer list or business development pipeline. For instance, if 10% of typical companies are from the professional services sector, but 20% of your prospects are from this sector, using segmented averages becomes crucial. It enables businesses to understand where they are over or under the expected values and adjust their strategies accordingly.

However, simply using segmented averages is not enough. Businesses must also make the component values of any rolled-up average available and convey a signal that the average for the business is not very useful because it represents only a small percentage of their customer base. To get details, they need to go deeper. This kind of precision of execution is crucial to ensure the value of any information is useful for making decisions.