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2020 Vision: what skills help the modern analyst stand out clearly?

Published on 27 July 2020

2020 Vision: what skills help the modern analyst stand out clearly?

In this ever-changing and demanding world, how can we develop ourselves to be in demand, not just now, but in the future? Visiting our members, I get a unique insight into the ways in which the data teams, analysts and insight specialists interact and operate, across all types of organisation and team. From this experience I’ve identified some key skills and characteristics of effective analysts. With more and more data available,  and an ever-growing expectation to use this information the role of Data, Analytics and Insight analysts has never been more exciting.

Questioning skills
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. Asking open questions starting Where? What? Who? Why? When? How?, can help not just in understanding your stakeholders but in analysing your data.

Self-evaluation
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
Just because it has happened once, doesn’t mean it will happen again. You need to help people distinguish between correlation and causation. Understand the margin for error and confidence in your data. Communicating this to your stakeholders is critical.

Cognitive bias
Making decisions, or influencing and driving decision making is crucial, but how can you limit, or eliminate, cognitive bias from these? Take a look at some typical types of bias (see box), how would you spot them?  

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 as 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.

Understanding technology
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. Sticking with the old technology may be reassuring and help you to demonstrate your tried and tested skills, but this could limit you, your team and organisation in the long-term. So, don’t be lulled into a false sense of security; push yourself to the end of your comfort zone. 

Rapid pace of change
Expectations and demands are higher than ever, and this is not likely to change. The aspiration for any insight team is to find solutions to problems before they happen and exploit opportunities nobody knew existed. When new requests are made, analysis and answers need to be fast and timely, or the opportunity will be missed. Rather than just being reactive, waiting for requests, or using data to report on and evaluate the ideas others have already had, we are now seeing insight teams being proactive. They understand their stakeholders’ goals and use data, knowledge and experience to generate new ideas and insight. Take time to review your and your team’s strengths and weaknesses. How can you use your strengths to improve the value of the insight you produce? Where can you use the strengths of others to support you? How can you focus your and your team’s personal development to make the biggest difference?

Cognitive Bias: common types of bias 

Built from ideas developed by Daniel Kahneman and others in the 1970s, a cognitive bias is a routine, often unconscious bias in our decisions and judgments, sometimes related to memory and how that is stored. 

  1. Confirmation Bias: favouring information that confirms previously existing beliefs.
  2. Self-Serving Bias: tendency to attribute positive events to their own behaviour.
  3. Hindsight Bias: the tendency to overestimate their ability to predict an outcome that could not have been possible to predict.
  4. Optimism/Pessimism Bias: cognitive bias that causes someone to believe that they themselves are less likely to experience a negative event.
  5. In-group Bias: tendency that people have to favour their own group above that of others. 

This article was first published in the 2020 Best Practice Guide - 2020 Vision: Crystallising your knowledge

To download a full digital copy of the Best Practice Guide, click here

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Author: Leanne McNamee

Categories: Library, Data, Analytics & Insight

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