Situation. Data in isolation is dumb and useless. Data is only ever a resource for whoever that needs the data. Data only has value in use. To make data smart we must align it to their situation. Who are they? Why do they need the data? What do they do with it? What and whom are they doing their thing for?
Problem. Again and again, we spend a lot of time and money to try and adopt new data- and AI-enabled ways of working. Everytime our projects, teams, and approaches fail. Why? We do not adress the operations that data and analytics are supposed to boost. What do they need the analytics for? They are trying to boost the business operations. That is what we need to make data smart about.
Implication. We need a useful methodology for deciding with the business how data and analytics should boost their operations.
Why? Because doing that, and doing it well, is the very first order of concern in any project, regardless of the size or the data/AI maturity of the organisation. The objective is to spend our efforts and time where it counts: serving them something that is useful and adoptable.
Need. Dairdux has, together with our clients, over the last years co-created methods to be used by any size project in the initiating phase. These shape and frame the project more clearly and in a repeatable way, from the perspective of the impact the business wants from their data and analytics use-case.
This is the story we will share on stage in this key note.