6 Aug 2021

The Problem with Positive Feedback in Decision Making | mpro5

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Are people in your organisation actually using data and visualisations effectively to make better decisions?

Probably not.

It’s clear that businesses around the world are on the journey of digital transformation to keep up with modern demands. But many companies, when I first speak to them, only want to see their top performers, the best scores and the success stories, reflected in good-looking visualisations. KPIs that paint a positive picture won’t tell you the whole story, let alone provide guidance for improvements.

Why go to the effort and cost of making sense of your data and visualising it to tell yourself what you already know? Because the real value of emerging technologies is in their ability to tell you what you don’t know and to drive improvement through your understanding of failure.

 

Positive feedback makes us happy

It’s very human to seek and enjoy positive feedback and it has its place, especially as a tool to encourage and reward your staff for their hard work. But focusing exclusively on positive data has diminishing returns for business analysis. Data visualisations that only show the positives are typically used for around a month before they become redundant to the user and stop providing actual value. The novelty of seeing this data in dynamic and pretty visualisations tends to wear off quickly.

A dashboard that is all ‘green ticks’ can hide potentially business-changing information and in turn, areas for improvement can go unnoticed. Visualising what needs improving helps establish where action is needed and the areas that will start to move the needle. Without this, you’re playing Battleship to decide on strategic and operational decisions.

 

What KPIs should be tracked?

KPIs should always be aligned to your strategy so start there and don’t waste time with those that don’t link to it directly.

Once you have a set of KPIs that are strategically relevant, methods of visualisation should be carefully considered. Bad visualisation is a common occurrence unfortunately, leading to beautiful but inscrutable dashboards that are mostly useless to their users. You’ve probably seen at least one graph that made you wonder, what is this actually showing me? The short answer is very little most likely.

Visualisations need to be easily understood by business stakeholders who are usually time poor and may not have an in-depth or technical understanding of the business area being analysed. Information should be easy-to-absorb. Ensure best practices are being used by those creating the visualisations and never lose sight of why you are visualising the data in the first place.

 

Stop playing the blame game

KPIs are not there to pat you on the back, nor are they there for proverbial whip-cracking. Instead, the focus should be on using KPIs to understand where a problem lies, what factors are contributing to the problem and to inform strategic and tactical decisions.

By taking a more well-rounded and considered approach to KPIs and data visualisations, businesses can monitor their dashboard to see where they can make positive changes to the business. Once changes are made, it’s critical to track whether the chosen response actions drive improvement over time. Don’t miss this part or you’ll never see the fruits of your labour!

 

 The perfect blend of technology and people

Artificial Intelligence (AI) is useful for organisations who have got to this stage. AI can be utilised to predict how long it could take for chosen actions to improve poor performance areas identified by holistic dashboards and clear presentation of data. AI effectively supercharges data analysis by probing into data and correlating multiple anomalies, revealing insight and predictions. But be careful and use AI consciously to improve your KPIs, always being vigilant to avoid it becoming a vanity project.

To get true value from data and visualisations in the context of business performance, it’s not all about the data and technology. Leaders within business should be open to honestly looking at problems and then evaluating their processes and internal capabilities for maximum results. Because succeeding is often about truly knowing your failures.

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