Yesterday we talked about that the measure phase helps to find and define causes for your perceived problem. Today we are going to look into a few tools and methods which are used to achieve your goal.
The first step in finding the reasons for your problem is having brainstorming sessions with all potentially relevant stakeholders involved in the problem. Sticking with our problem of high customer dissatisfaction, we would involve service desk employees, their team lead, their head of division but also customer facing employees like account managers, sales managers and also product managers and technical personal, because customers mostly complain about products which do not work. Do not keep the group of people in your brainstorming too small, because you want to include all customer-touch points. Each person interacting with customers and interacting with the product might hold data and information which we can later use.
In the brainstorming sessions, stakeholders together fill out a so-called fishbone-diagram. Fishbone diagrams break down problem sources into six pre-defined groups (like people, machines, methods, material) and talk potential causes in those groups or categories. This pre-definition helps to lead group discussions and help people to stay focused on one topic. The result of the brainstorming sessions will be a long list of potential causes for the problem.
After that all processes involving the named causes from the brainstorming sessions will be mapped. This process discovery is one of the most important overlooked steps in A.I. projects. It sets potential causes in relation to each other and displays how people cause perceived problems while interacting across departments, teams and time. After developing a set of more and more detailed process maps, which we will look at in later chapters, the process maps will be converted in so called value stream maps where each process step will need to show which data points will be created there and what value it creates. These process step parameters will be later used by your A.I. outsourcing partner to fuel their models. As you see, your initial business problem was first embedded in your business processes and the process steps now are converted to data producing units. If you are at this point, your outsourcing partner will be able to much easier bridge the gap between your business and its ability to create data models.
In a next step, Analyze Phase (s.index below) you will again come together with your brainstorming brain trust and reduce the potential causes for your problem. Why would you do that? Well, imagine you came up with 100 reasons for bad customer experience. Fixing all of these problems would take a long time and cost a lot of money. However, you should always focus on the main reasons for your problems. This will always yield the highest ROI. The following example will make it clearer: Imagine 9 out of 10 customers complain about products being broken after having been shipped and only 3 customers complain about Jim in customer support. What do you do? Well, it is obvious: fire Jim ;) Joke aside, of course you would look at a new packaging solution, which in this case does not involve any A.I. at all.
1. Process Optimisation Overview
5-Phases of Process Optimisation
6. Control Phase