4 Questions to Ask When Defining Your Business’s Key Metrics
Ninety percent of the data in the world today has been created in the last two years alone. This data has been instrumental in providing insights into businesses – something business leaders could only wish for 20 years ago. As technology continues to become more powerful, we’re able to analyze more and more information. As a result, today’s overwhelming amount of data has made it difficult to prioritize information needed to gain insights into your business.
In working with many clients across various industries, Arete EPM has found there are four key questions that FP&A professionals should ask when trying to determine if information will be used effectively and efficiently to provide insight in business decisions.
1. What are the key metrics that drive your business?
The question seems straight forward. Yet, when teams are not aligned with the overall objective, you risk losing sight of what’s truly important for what you are trying to achieve. Defining an agreed upon list of metrics upfront becomes your reset button when competing agendas and new questions enter the situation.
2. Will the information add value or provide new insight into your business?
Due to limitations in technology and data sources, it used to be an accomplishment for previous generations of FP&A leaders to generate any actionable information to use in strategic decisions. Today it’s a different story. There is an unending amount of information at our disposal and the challenge is determining what data will provide actionable insights. A common mistake made when analyzing data is assuming correlation implies causation – if your numbers are telling you something then it must always be true. For example if a small coffee shop owner in Chicago realizes whenever it rains in Orlando, he sells more coffee. Logically there is no relationship between customers at a small Chicago coffee shop and the weather in Orlando, so this piece information is irrelevant.
3. How granular do you really need to go?
More detailed data does not always imply higher accuracy in results. It is dangerous to assume more detail is better. Rather it often leads to challenges impacting the complexity and quality of your results. Here are three of the most common challenges faced with granular data.
Challenge #1: The data is not complete or consistent.
An objective at a past client was to report on total operational costs across four groups of cost centers within the organization. Three of these groups had near-perfect data, but one group could not provide the same level of detail defined by the project’s original objectives. Based on this initial review, the decision was made to redefine the level of detail to ensure all groups could provide complete and consistent data.
Challenge #2: The data quality is low.
It is relatively easy to identify data quality issues when reviewing summary-level data points. Typically, this is because you are more familiar with the key results. However, when it comes to granular data, companies often depend on sources outside of their control to populate and maintain information. On average, 47% of newly-created data records have at least one critical (e.g., work-impacting) error, according to research done by the Harvard Business Review. If data population standards and processes are not properly managed, lower quality data can provide results that truly don’t represent your business.
Challenge #3: Substantial effort is needed to generate consumable data.
The quest for accurate insights through granularity can evolve into a much larger project than originally predicted. When you don’t currently have a source for a granular data point at the level of detail you have defined a need for, you’ll find a way to fill the gap through manual effort or through a complex or expensive process. It’s often the justification to implement new technology. Before jumping into an expensive or time-consuming solution, ask yourself “Will this solve the overall objective?”.
4. Do you really need this piece of information?
We’ve posed this question to clients in the past. The typical response is a definitive “Yes” followed by the “I can’t believe you asked that question” look. If we say the same piece of information will cost millions of dollars – only to provide a few thousand dollars in added value in return, the answer is much different. Unfortunately, it is impossible to predict the exact return on insights before starting a project. But by reassessing the value of information, you can avoid unexpected costs, time and complexity.
Take a step back and ask yourself these questions. The extra thought will help you find the key metrics that provide better insight into your business.
We will leave you with quote from the mathematician John Tukey, a pioneer himself in the information age.
“Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.” – John Tukey