Let’s talk about the Average Service (or Product for that matter).
The average is hugely underestimated, especially by those who createing or delivering a service or a product.
But before advancing any step further I feel that it is important to defien the word Average, because it has been mostly abused for delivering a mediocre service/product – we naturally pride ourself on our best moments and we show our friends & customers those moments, meaning that they are something quite regular or AVERAGE, while it is of course not. In the big scheme of things while our best moments definitely count for our clients, but on the daily basis it is our Average is what really counts and what our branding is standing for.
The average time to fullfill a service request, the average number of errors of na installation or a product update, the average quality of the simpathy, etc
It is not the best deploy/deliver that matters, it is not the most perfect service delivered to one particular customer, but how we handle a big number of requests &services in the statistical sense.
The calculation of the average will be tricky. You might be using a rather simple and plain calculation, but I am convinced that for a lot of cases that would be wrong and even dangerous.
First of all, taking out the outliers is essential – since your fastest delivery and a huge slipper while of course are awesome/terrible, but being the outliers they matter less (of course given that the slipper was not a huge disaster).
Secondly the selection of the funciton for the calculation of the Average: Median vs Mean vs Mode vs “whatever else you might chose”. This selection will be based on the industry, type of product, government/industry/etc requirements.
And do not forget the bias while your picking the outliers and picking the calculation function, because the data will confess whatever you wish, if you “torture” it enough.
I feel it is important to take care of the worst outliers, making sure that they will never happen again and the best way is to design the mechanism in the service that prevents them from happening ever again for the average situation.
Getting and finding out the uncomfortable results are absolutely essential in order to get to the bottom of the problems and start improving.
The strategy should be data-driven and the improvement decisions should be prioritised based on the importance of the overall service and not on one client in particular (though the implementation will of course always start with one particular customer). The obvious exception would be the case of the client which absence would simply destroy your company. :)
Why do I feel that this topic is so important and was worth writing about?
Because besides improving the quality of the product/service, it might be even a question of survival as a business.
If you think about sports and competition – the opponents will always try to eliminate the best players from your team while trying to explore the weakest link/the weakest player in order to succeed.
Transferring this into the product/service deliver we ensure our success by making the average knowledge of the team as higher as possible, thus protecting the company/service/product even from the outside interference.
Remember -> the goal is to drive the product/service average quality higher, and that starts by improving our worst delivered services/products. Driving our best moments on might fullfill the need of some of our customers, but on the average (pun intended) – the customers wants the Average service to get better.