In statistical hypothesis testing, there are two ways of classifying errors. ‘Type I’ errors occur when a true null hypothesis is mistakenly rejected, while ‘Type II’ errors are the failure to reject a false null hypothesis. Though this may sound complicated, it can be simplified by framing them as errors of ‘commission’ and ‘omission’ respectively. In other words, a Type I error involves doing something incorrectly, while a Type II error is when it is not completed as well as it could be.
Now, it may seem like it makes the most sense to prioritise eliminating Type I errors within your business – why take steps forward when there are things pointing you in the wrong direction? However, research has shown that if the guiding principles behind an organisation’s success strategies are based on minimising losses and maximising wins to the exclusion of all else, then what often develops is a culture of ‘skilful incompetence’.
There’s no such thing as a perfect business strategy, so if this is the aim then the focus shifts from reducing the number of problems, to reducing the number that are identified – discouraging external enquiries and tests, and creating an incredibly defensive environment. This is a vicious cycle which inhibits learning and innovation.
In contrast, if the focus is on openness, validity and constant monitoring, then there is space for reflective learning and continuous improvement. You need to be able to see the transformation process, and this is done not by cutting out all of your mistakes and optimising every process, but by constantly striving to find opportunities for development and growth.
Understanding that everything within your business is relative, and viewed differently by different people, allows it to be improved in a way that effectively benefits as many people as possible.