Organisational Science

17.12.15   White paper

Stupid is, As Stupid Does.

Business Intelligence is now an accepted phrase in the lexicon. Every business wants to have a better understanding of their customers, operations and organisation. As a result, an industry of consultants and software offering ‘Business Intelligence’ (BI) has emerged to meet this ever growing need.

And yet, when we look closely at most BI software, we often find that it isn’t intelligent at all. It is a blank slate that requires you, an intelligent user, to provide knowledge and understanding. It can’t simply ‘plug-in’ and find insights buried inside data. It needs you, the subject matter expert, to tell it how to crunch and present that data. In other words, it is merely a powerful calculator that is awaiting instructions.

Intelligence is the practise of applying knowledge. If software doesn’t understand the nature of the data it is handling, it cannot be called intelligent. Consider the data held by the Finance team and HR team respectively. The nature of the data (e.g., dollars vs. employees) and the analysis (e.g., P’n’L vs. engagement) is markedly different. So if the software itself doesn’t have the knowledge or the ability to intelligently understand the nature of the data it is handling, is it not actually quite stupid?

Expect more, See Further.

There is an alternative approach. Truly intelligent software that has been specifically built to get the most out of one particular type of data. In other words, BI that has in-built best practices and knowledge. The difference is key to unlocking the true value of Business Intelligence.

Let us consider People Analytics for a moment. If the software understands all the different types of people data, it can begin to intelligently find insights within that data. For example, it can be programmed to understand spans of control and have the ability to highlight issues within organisation structures. This is the beginnings of a real Business Intelligence.

Analytical software built by HR professionals and organisational specialists can take on aspects of their knowledge and experience. This means it can assume aspects of their intelligence as well. Less experienced professionals using that software can benefit from their experience, seeing further into their own organisations.


There is a further, less obvious benefit to specialised analytical software. Most large businesses have many data analysts. Each analyst might interpret data differently. As a result, something as simple as attrition can be calculated in many different ways within the same organisation. This is a significant problem.

Is the attrition improving or worsening? What is the comparison of attrition across different teams? To have an accurate answer we would need the same analyst to prepare all of the data in the same way, without human error. Over time, that is highly unlikely.

Now let’s consider a truly intelligent People Analytics software that understands attrition and calculates it in a completely consistent way, without error. Furthermore, it does this not just for one business but for multiple businesses. Accurate benchmarking becomes possible for the first time. An invaluable step forward on the road towards real Business Intelligence.


Business Intelligence software is a misnomer. If the software doesn’t understand the nature of the data, it cannot be called intelligent. After all, intelligence is the ability to apply knowledge.

We believe that embedding HR knowledge within software will enable a new breed of analytical tools for the HR team. That is the basis by which we built Qlearsite. It contains within it sets of analysis that offers users instant people insights.

But we’ve gone even further. We’ve also embedded into our software other areas of expertise, including statistical knowledge and machine intelligence. In doing so, we’ve created a software that is a powerful People Analyst, capable of seeing into an organisation’s future, reading and making sense of thousands of survey responses simultaneously and helping find hidden sources of value. But that’s a story for another day…