What are the key skills required, to not only make us effective now, but to ensure we remain relevant in this ever-changing and demanding world? Visiting our members, I get a unique insight to how different data teams, analysts and Insight specialists interact and operate. From this experience I’ve identified the following key characteristics:
Asking powerful questions is a key skill for any business leader. For analysts this is about asking inquisitive questions to understand, learn and identify the root cause of the need for analysis. Too often analysts can be at the wrong end of questions and requests. Asking good questions helps us to develop our own understanding and that of others.
Add: Where? What? Who? Why? When? How? Etc…
How do you know you’re doing a good job? How do you know a change initiative has worked? Setting the right metrics to evaluate prediction and performance is critical. Targets are often mis-understood as not enough time is spent on the communication of the metric, versus the updates and the alerts.
Statistical Significance; distinguish between correlation and causation
Just because it has happened once, doesn’t mean it will happen again. Knowing the margin for error and confidence in your data and communicating this to your stakeholders is critical.
Making decisions, or influencing and driving decision making is crucial, but how can you limit, or eliminate, cognitive bias from these?
Confirmation Bias: favouring information that confirms previously existing beliefs.
Self-Serving Bias: tendency to attribute positive events to their own behaviour.
Hindsight Bias: the tendency to overestimate their ability to predict an outcome that could not have been possible to predict.
Optimism/Pessimism Bias: cognitive bias that causes someone to believe that they themselves are less likely to experience a negative event.
In-group Bias: tendency that people have to favour their own group above that of others.
Visualisation & Communication
Data doesn’t make decisions, people do. Poorly represented and displayed data drives poor decisions, so it’s important that analysis drives the right outcomes. Representing the data in a way which helps key information to stand out and support correct or, at least, better decision making isn’t easy; especially if different people have different preferences. It’s fair to say that one-size-fits all, however, there is a limit to the number of methods you can use. Educating your stakeholders is key, as they will only know what they know. Help them to learn how to use the data, tables, graphs and dashboards and create a feedback mechanism.
Technology developments move at a fast pace, so the ability to embrace the right “new” technology versus continuing with existing is critical. Being a pioneer and frontrunner is hard work, as you can end up just clearing the way for others to move faster behind you. Whereas sticking with the old technology may be reassuring and help you to demonstrate your tried and tested skills, it could also limit you, your team and organisation in the long-term.
Expectations and demands are higher than ever, and this is not likely to change. Being on the front foot, leading with analysis and insight will be crucial. When new requests are made the speed in which analysis and answers are required will need to be timely. Rather than just being reactive – waiting for requests and using data to report on and evaluate the ideas of others, we are now seeing insight teams being proactive – understanding their stakeholders’ goals and using the data together with their knowledge and experience to generate ideas and solutions. The aspiration for any insight team is to find solutions to problems before they happen and exploit opportunities nobody knew existed.
Arthur: Ian Robertson