Actionable Data versus Vanity Data

July 1, 2021

The world is awash in data.  Never in history have so many people had so much access to so much information.  Some of you would probably go so far to say you are drowning in data.  It has been said that there is both good news and bad news about data.  The good news is, we have lots of data.  The bad news is, we have lots of data. MMA’s risk prevention services support your insurance coverage by addressing the cause of risk at it’s roots. You know that preventing claims is the best way to lower costs, so designing and implementing injury and crash reduction strategies is the best way to improve your safety measures.

For those who collect, analyze and make decisions based on data, the key is to ensure the correct data is utilized to help accomplish goals.  Such data is often referred to as actionable data or actionable metrics.  Actionable metrics are those numbers you capture and track which help you measure progress toward a specific goal.  For example, in both trucking and agribusiness, if your goal is to lower your OSHA Total Recordable Injury (TRI) rate, actionable metrics are those data points that reveal whether or not you are actually achieving that goal; such as, Number of Recordable Accidents by Employment Tenure or Types of Injuries by Type of Job Assignment.

In the first example, tracking the Number of Recordable Accidents by Employment Tenure allows decision makers to cater mitigation strategies to those employees within a certain tenure status, such as those with less than six months of employment or those with 15-20 years of employment.

In the second example, tracking Types of Injuries by Type of Job Assignment might reveal that most injuries occur when truck drivers are securing tarps on loads or when farm workers are unloading grain bins. Such information allows decision makers to design and implement injury-reduction strategies specific to those situations. Thus, actionable metrics are those data points useful for making sound business decisions.

As opposed to actionable metrics, data points which are collected, but that do not aid in the decision-making process, are commonly referred to as vanity metrics.  As the name implies, vanity metrics are all about superficial appearance—meant to impress or support a position, but which have no real value toward reaching a goal.  The following flow chart will help you determine if your metrics are actionable or vanity in nature.  

Image Source: https://learn.g2.com/vanity-metrics

Three diagnostic questions will assist in determining if the data collected are actionable metrics or a vanity metrics. If the answer to all three diagnostic questions is “Yes”, then the metrics are almost certainly actionable.  However, a single “No” answer to any of the three questions usually indicates the data is non-actionable or is a vanity metric.  The diagnostic questions include:

  1. Do the metrics lead to an informed course of action, or inform a decision?  In other words, is the data necessary to make a sound decision about the issue being considered?
    • If the answer is “No”, the metric is not actionable and probably serves no legitimate business purpose.
    • If the answer is “Yes”, then consider the second question.
  2. Can the results be purposely reproduced? This question serves as a quality check and is critical to statistical integrity.  In other words, if another decision maker had access to the same data, would that individual reach the same conclusion about the usefulness of the data as applicable to the issue being considered?  The second individual may not make the identical same decision that you do, but would the data be critical to that second person in making whatever decision was made?
    • If the answer is “No”, the usefulness of the metric is questionable and the metric should probably not serve as the basis for important decision-making.
    • If the answer is “Yes”, the validity of the data is confirmed and the third question should be considered.
  3. Is the source of the data reliable? In simple terms, is the data set complete and do the numbers accurately reflect what the numbers are purported to reflect? If the data source is unreliable, the data itself is skewed and may lead to inaccurate decisions or be used to support a predetermined position.
    • If the answer is “No”, the data has little or no value to a decision-maker and should be rejected.
    • If the answer is “Yes”, the decision-maker can move forward confident in the accuracy and credibility of the data.

MMA’s Risk Consultants are dedicated to helping you achieve your organization’s risk management goals. We are here as your business partner to help you prioritize your data sources to determine which channels are relevant and to guide you in interpreting the information these data sources are telling you.

If you have additional questions on managing the data your company is collecting, please reach out to your MMA Risk Consultant for more information.