In ‘Future Ready’ I described how best to generate ‘facts’ about the future in the service of decision making in organisations. But most of the information used in decision making and to assess performance are facts about the past.

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People in some circles make fun of this. They call it ‘driving using the rear-view mirror’. But at least what has happened is ‘real’, whereas even the best forecasts are ‘made up’ and likely to be wrong in ways that we cannot anticipate.

 

At first glance you might think ‘facts are facts’, so there is no mystery or problem to be solved, but that is far from the truth.

 

Firstly, the problem is there are lots of facts. Far too many for us to assimilate easily. Over the course of my career the problem has changed from ‘we don’t have enough (reliable) data’ to ‘we have too much data and we don’t know what to do with it’.

 

Second, even though we can now capture facts reliably, what these facts tells us isn’t at all clear. One reason for this is that all data is infected by random noise which confuses, complicates and obscures the signal buried in it.

 

Worse still the conventional tools that we use to attempt to make sense of data are useless. Not only do these not help us to make sense of what is going on, they often actively mislead us. 

 

The reason for this is that our ‘go to’ method is variance analysis, or comparison to target, where we take a single data point (infected by an unknown amount of noise) and compare it to a target that is often no more than an out-of-date guess. 

 

The artificial and unhelpful nature of fixed targets as a basis for setting goals and measuring performance has been well understood in Beyond Budgeting for many years. But the question that needs to be answered  is what should we do instead? 

 

This was the challenge I set myself when I set out on the project which ended up as ‘Present Sense’. What seemed at the start to be a straightforward and perhaps mundane task become richer, more complex and more interesting as I worked on it.

 

What became increasingly clear to me is that to help us make sense of performance in a world of super abundant data there was no simple technological solution. The world is simply too complex, dynamic and ambiguous for that.

 

Instead, we need tools to help our brain apply its phenomenal sense making capabilities to take on a task more complex and on a much bigger scale than evolution had equipped it for. And to do this we need to understand how to exploit its strengths and mitigate its weaknesses. 

 

But sense making is only part of the problem. The second part of the challenge to be able to present the results to decision makers in such a way that their brains can assimilate the information and form sound conclusions as quickly and as easily as possible.

 

Our existing tools fall lamentably short of the standard required. Too often these are no more than the representation of data in a tabular form which is a completely alien way of communicating for our brains as they have evolved. So it soon became clear to me  that communicating insights also requires an appreciation of the process of human cognition. 

 

So, the first half of the book tackles the process of making sense of data, drawing on the latest developments in neuroscience and what I have learned from my work in analysing forecast performance to be able to separate signals from noise.

 

The second half of the book is informed by my work in software design which familiarised me with the advances being made in data visualisation, both as a means of discovery of insights and a medium for communicating them to an audience. This again draws on cognitive neuroscience and how these insights have been exploited by Edward Tufte and Steve Few to help present statistical information more effectively.

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The book content is organised as follows:

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PART 1: Rethinking the process of performance reporting

1. Why do we need to change the way we do stuff?

PART 2:SENSE: The science of extracting meaning from data​

2. Performance reporting: What is it and what has it got to do with brains?

3. Direction: performance as flow

4. Uncertainty and unpredictability: big data and the weak signal

5. Level: what does good look like?

PART 3 PRESENT. The art of communication by visual means​

6. Communication by visual means.

PART 4: Action​

7. Reporting is reporting (not storytelling)

8. Now what?

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When I was writing the book I was conscious that simply talking about what needed to be done was not enough. The book itself needed to be a model of effective communication. The result is a high quality, well-illustrated ‘coffee table’ hardback book. You can buy it through the normal retail channels or from my bookstore in either a physical or PDF format.