Are you delivering just Analytics or the Actionable Insight needed?

Over decades of leading and developing analytics teams I’ve lost count of how often their internal customers ask for ‘actionable insight‘. Often commercial leaders don’t know exactly what they mean by that phrase. But they are clear when they are not getting what is needed.

I hope you found Morwenna Causey’s post on running an Analytics Hackathon helpful. I expect that approach makes good progress towards identifying insights. Max Shron’s “Thinking with Data” book provides some great methods for a structured thinking approach to insight generation.

Last month I set a challenge for my guest bloggers to share their experiences and thoughts on insight generation. You can always rely on Tony Boobier to share something in reply. Regular readers will remember that Tony is an AI & Analytics expert, mentor and author. In this post, in his usual style, Tony muses on the real meaning of insight. By so doing he challenges us to think more deeply about what we deliver as analysts. Is it only the result of our analytics work or the real insight our business needs?

Actionable insight, just what do you mean by that?

The expression ‘Analytics creates Actionable Insight’ is one that I’ve lived with now for over a couple of decades. It implies that the use of analytics isn’t simply an academic exercise. That there is something more involved. Analytics has limited value, or perhaps even no real operational value if we don’t act on what we have gained an insight into. 

By interrogating data through analytics, the intention is to find patterns in the information provided. Then perhaps also to express or communicate what is discovered in a way which is meaningful. We’ve written before on the matter of visualisations as a critical part of the communication process. 

By ‘action’, the intention is one of making some sort of a change. This may be in the form of creating a new set of business rules, designing a new specification, reorganising the business or in some way changing how we traditionally operated. Effective use of analytics in effect creates a ‘call to action’.

Learning from History and Etymology

The focus historically has been on those two words ‘analytics’ and ‘action’, but perhaps an invaluable part of the equation has been overlooked. That of ‘insight’. 

The expression ‘insight’ is a very old word, going back to ‘innsihht‘ from circa 1200. The word can be found in both Dutch (inzigt ) and German (einsicht) dictionaries of the Middle Ages. The original expression meant “sight with the ‘eyes’ of the mind, mental vision, or understanding from within“. But it has also come to mean ‘penetrating understanding into character or hidden nature’.

In a more modern sense, ‘Insight’ is fundamentally about putting the results of analysis into context. Something new has been learned, or perhaps what was already known or believed has been reinforced. Insight is more than simply observing a situation and reporting on it. Rather it is about recognising its relevance and how greater knowledge and understanding might solve a particular problem, or makes things better in some way.   

A creative interlude can complement your technical strenths

The concept of insight is often used to explain poetry, literature or great works of art. It looks behind the curtain of what might seem to be obvious. Insight gives greater meaning to what we observe. This can equally apply to matters of business. 

The concept of insight is something which is often ‘unlocked’ by a combination of experience and relevant education. That is perhaps why data scientists, as clever as they might be at crunching data and creating code, are only part of the equation in terms of creating business insight. Data scientists need to work hand in hand with others who understand the operational issues through effective teamwork. 

Data scientists alternatively can acquire that understanding themselves but this is not always simple. Is it easier for a data scientist to learn about business; or a businessman or woman to learn about data science? There is an increasing mood for both disciplines to meet somewhere in the middle. Merging the separate jobs of data science and business operations (or strategy) into a single hybrid role. Invariably, future business professionals will need to know about both functions, perhaps in equal measures. 

What do the analysts of tomorrow need to learn?

Educational institutes and professional institutions need to recognise that the future is not simply an extension of the present, with technology added on as some form of an afterthought. Many education courses include technology as a stand-alone module. To me, that seems to be missing the point. Rather, technology is increasingly integral – and vital – to almost all professions going fordoward. How can we prepare our young people for working life in 2050, when we still teach them as if it is 1950?

Whilst insight might be, arguably, one of the passports to success, on the other hand, it can also be a critical tool in understanding why something hasn’t been as successful as everyone had hoped. We all hate to fail. The expression ‘failure’, in other words, describes a form of reasoning as to why a person or individual might not have reached their desired goals. ur

To effectively find that ‘form of reasoning’ and to understand why this might have happened also requires insight. This is usually in the form of candid feedback but often it is possible to find evidence, or proverbial footprints in the sand, which might give an indication that things haven’t been going as planned. 

Actionable insight is needed, but can you learn from the past?

It seems to be a human trait not to want to share bad news, especially in a performance-orientated business environment. This might be one of the reasons that bosses (and perhaps politicians as well) think that everything is going fine, when those on the front line and in middle management know that this is far from the truth. In receiving accurate information, coupled with appropriate insight, we hope to understand how to do it better next time.  

So, to try and bring all this to some sort of conclusion, we need to recognise the idea of ‘insight’ as a vital component both in achieving success and in understanding failure. Insight is a combination of knowledge and experience, placed into an appropriate context. It is, as those Medieval scholars knew all along, all about ‘having an understanding from within’.

Thanks to Tony for his always engaging musings, questions and challenges. What do you think dear reader? Are you clear as to how you generate actionable insights? Do you know the forms of insight that your business really requires? Can you train your analysts & data scientists on how to generate insights? I’d love to hear your thoughts and keep sharing best practices across our community.