In the case of Telenet we used a combination of workshops and interviews to arrive at a relevant understanding of the AS IS situation. This exercises yielded a clear view on the current set of frustrations & challenges across all different stakeholders. The result of this initial workshop were three context-sensitive questions that guided & aligned everyone going forward.

These questions formed the basis of discussion on what the To Be should look like. Through our custom workshop we started looking at where AI forecasting models could make the difference and how they would influence current processes. What decisions were being made on gut feeling rather than data? What felt like it could be done better, faster or cheaper? From there our digital innovation strategists went to work to design between 3-4 experiment proposals per questions based on all the previous conversations had. For each experiment proposal the business context, how the AI model would work e.g. what its output would be, what KPI’s it was designed to impact & what the minimal data requirements would be - expanded with ‘nice to have data’. We've added an example below with sensitive data removed. 👇

Finally a prioritisation exercise was done based on feasibility vs impact. From this exercise, 3 short term & 4 long term projects arose. From those 4 longterm projects a “data gap” was made apparent which in turn provided a couple of strategic targets with regards to data to acquire. These experiments were then assigned to a digital innovation owner who will help these ideas go from concept to business impact over the next couple of months.