One of the biggest causes of delay in finding the root cause of a problem is a lack of information – data that is vague, unproven, or simply not known. During these times, it’s not unusual to start chasing down information without knowing if this missing piece of information is truly needed to unlock the underlying solution.
If the risk is within acceptable limits, you can make decisions and try out solutions without gathering unnecessary data.
One way to keep data gathering activities moving and accelerate root cause analysis is to use the acronym NMD or “Need more data”. By labelling data that is vague or not known as NMD, you can then estimate the amount of variance or risk that has been introduced into the process. If the risk is within acceptable limits, you can make decisions and try out solutions without gathering unnecessary data. This allows you to move ahead with confidence and without frustrating your customer and subject matter experts (SMEs) by demanding that more information mustbe collected before proceeding.
Understand the quality of your existing data
In a best-case scenario, using NMD and weighing the value of gathering more data before moving ahead using only the existing data may even reveal that it is unnecessary for a root cause to be found.
A best practice approach, like the Kepner-Tregoe concept of NMD, requires assigning follow up responsibility to an individual or documenting when the missing data will become available. Instead of answering a question with “I don’t know”, using NMD should reference: 1.) that the data may be incorrect, unclear, and missing, 2.) the best person to ask for additional information, 3.) when that data may become available.
Pursuing incomplete or unsubstantiated information can quickly lead you down the wrong track in your problem-solving journey, wasting valuable time and resources. Before tracking down “required data” that is unclear, missing or incorrect, it is better to estimate the actual value of this data during your pursuit of root cause.