No matter the size of your business, whether you are the CEO or other leader, you need to understand the value of measuring your company’s performance. It is nearly impossible to operate a successful business without this information. But what metrics should you be tracking? How do you keep track of all this data, and how do you analyze it over time to understand where you need to improve? The answer to this question is not simple. Determining which metrics you should use depends on the type of business you have, what your business strengths and weaknesses are, and what your ultimate business goals are.
How many times have you been in a meeting where you heard someone recite a lot of business data that sounds good on paper, but you later find out the project or program is totally off track? The participants in that meeting were most likely measuring tasks, not outcomes. In other words, they were they were focusing on the wrong metrics.
When you find yourself or your team in this situation, try figuring out whether you’re making any of these three common mistakes. There are three common mistakes businesses make when trying to analyze data – and what you can do to measure what truly matters.
Mistake #1 – Not monitoring enough data: Sometimes companies don’t realize that there is certain data they need to be measuring but they are not. Are you measuring all the necessary metrics to get the visibility into where your company is at, and if it’s headed in the right direction?
Mistake #2 – Monitoring the wrong data: Data is not “good” in and of itself, but looking at the wrong data will give you the wrong expectations and results. The wrong data is just noise; it gives you false hope and creates false worries. Having the wrong data is in fact worse than having no data at all. Wrong data sets invalid expectations.
Mistake #3 – Looking at too much data: Measuring everything often equates to measuring nothing. Sometimes companies, rather than figuring out which data they need, will measure everything they possibly can—after all, more data is better than less data, right? But too much data just creates more confusion and more uncertainty.
The Problem of Focusing on the Wrong Data
We once worked with a client that sold a large enterprise software product. Each sale required the company go through a complex implementation process in order to complete the sale and make the customer successful. There was one group in this company that was responsible for all of this customer integration. At their weekly leadership meeting, they reviewed a report that had detailed metrics on all the steps involved in the integration. They conducted a very detailed analysis of the process and knew exactly what they needed to do for each customer, and how efficiently each step was executed by the various people involved in the process. They had data for everything.
As outside consultants, we attended one of these status meetings. It was clear that everyone was busy. But we asked, “How do you know you’re being successful with each implementation?” Silence.
Despite all of that data, none of it was able to show whether or not customers were satisfied with the installations. They knew how busy the team was with each step of the process, but nobody knew whether it met the customers’ expectations.
Just because you can measure something does not mean the measurement is useful. Sometimes simple is better. If you’re working on a big project, you are sure to have a lot of data to worry about—but a lot of data is often just a lot of noise. The company in the example above was completely ignoring the true valuable data, because of all the noise created by the unimportant data. They could not tell if customers were satisfied, an essential business metric for any company to measure. What you need is not more noise—what you need is actionable insights. If you have people generating data that nobody is acting on, that’s probably just noise. You need the data that allows you to make decisions and take actions to keep your business successful. These are actionable insights.
How do you know you are breaking through the noise? Is it actionable? To help our clients figure this out, we ask them two simple questions:
- What would it be like if all your desired outcomes were achieved?
- How would you know that those outcomes had been achieved?
These are the metrics to focus on. How would the company in the above example have known if it was successful with each implementation? The team could have answered those two key questions, and then focused on one simple metric to measure success: customer satisfaction scores after each implementation. Just using this one metric and ignoring the rest, suddenly the visibility into the effectiveness of the implementation team would have increased dramatically. Upper management doesn’t need lots of data, they need the right data.
Ken Gavranovic is the co-author of BUSINESS BREAKTHROUGH 3.0, is COO of Blameless and a board member and private equity advisor to several companies. While still in his 20s, Ken started Interland, now web.com, growing the company to $200M and leading its IPO. Since then, he has been responsible for hyper-growth at unicorn businesses, gaining experience across multiple industry verticals and leadership positions. Learn more at or www.kengavranovic.com.
Lee Atchison is the co-author of BUSINESS BREAKTHROUGH 3.0, is a software architect, author, speaker, and recognized thought leader on cloud computing and application modernization. At Amazon, he built the company’s AWS Elastic Beanstalk as well as its first software download store and led its retail website’s early migration to a service-based architecture. Learn more at www.leeatchison.com.
Business data stock image by Gorodenkoff/Shutterstock
