Data-driven Decision Making: Closing the Skills Gap
Digital platforms and tools continue to transform daily operations within firms. Talk a bit about the challenges this is creating for managers.
These new technologies require analytical tools and frameworks, familiarity with data, and an ability to put data, market requirements, and firm strategy together to form insights. For most people, this is very new; and it’s also new for the people they work with and manage. As a result, there is a huge skills gap at many different levels within firms.
Going from data to a managerial insight is actually quite complex. Data is messy, the world it represents is complex, and both training and effort are necessary to arrive at sound interpretations. The problem is that many managers avoid complexity, almost instinctively: they’re busy, they have information overload, and they want to keep things simple. I have a lot of sympathy for that. Simple truths can be very powerful, and it can often be time- and cost-efficient to focus on simple explanations and decision-rules. Unfortunately, though, complexity is only increasing, and it must be grappled with. This takes time, investment in both hiring and retooling talented workers, and important changes in how daily decisions are made within firms. Unfortunately, this is generating a lot of anxiety and insecurity — which can make people resistant to change.
This comes as no surprise. In Trust in Numbers, Theodore Porter takes a philosophical and sociological look at the role of data in society, noting an interesting interaction between data and authority: when access to objective data is limited, we rely on peoples’ seniority and experience to determine and justify what needs to get done. Suddenly having reams of objective data can undermine the power of high-status people and create conflict in organizations. It also places heavy burdens on the data-users and analysts to be accurate and to communicate effectively. Becoming data-driven is not something that happens overnight.
When the skills gap is closed and everything else comes together, what does a ‘data-driven organization’ look like?
The essential consideration for every organization is to make sure that the data they are collecting actually address the core challenges they are trying to solve. Firm strategy and objectives should drive the entire process: from data