Accuracy – how close results are to the true or known value (validity)

Precision – measures how close results are to one another (reliability)

The approach you take to an accuracy problem may be different to a precision issue. Identifying the nature of a problem can inform what the most efficient pathway to improvement is and where the greatest consequences lie. Sometimes avoiding the negative is more important than increasing the positive.

Imagine you are managing a team, and you have a very important task that needs to be completed. If this task is not completed to an adequate standard the consequences could be severe, you and your team could lose their job. You have two team members who are available to complete the task.

Dave is reliable and always produces good work but never stands out as amazing or brilliant.

Dan has had some incredible successes and brilliant insights, but most of his work is good enough, mediocre at best.

Who are you going to pick for the task? Probably Dave.

What if the consequences of poor performance weren’t as severe and the potential benefits of a great performance were enormous? You would probably start to consider Dan too even if you still wouldn’t choose him.

The approach you would take to improving the performance for both of these team members would be difference too.

Dave may need more of a focus on refining his skills or processes to improve his performance. It is typically far easier to improve the performance of an individual or product that has high precision as it’s often easier to identify the problem in their performance (for example a marksman with a tight grouping that is off centre might need only to make a small adjustment on their scope to reliably hit dead centre).

Dan would require a different approach that is centred on reducing the occurrence of poor performances. This may be implementing new systems (or actually having a system), providing support for particularly challenging tasks or modifying their role and responsibilities.