Business ‘not so’ intelligent 

I’d like to challenge what I see as the traditional view of Business Intelligence (BI).

On a daily basis I’m having conversations around BI; there is no doubt much of what is talked about is very powerful and useful, but now I’m questioning the ‘intelligence’ part. In reality, I find that most conversations about BI are really about the tools. Get into any dialogue about BI and it will often end up with, “so what do you use?”.

Business Intelligence is lacking in intelligence –  there I’ve said it! It is merely a feature of a potential benefit that an organisation ‘might’ be able to harvest. The work involved to produce the output (dashboard, etc) is, I believe, only one third of the story. For me, if we are to leverage data for the significant potential it holds, we need to shake the traditional tree of BI.

Define the business context.

The first imperative is to define the business context – why are we doing this? The ‘why’ does not need to be prescriptive but it does need to have some level of clear intention. The purpose and direction you’re heading should, in some part, align to the wider enterprise. Just another report that helps validate a corporate key performance indicator (KPI) is of limited value when customer engagement is waning.  Drawing a line to the customer context (public or private) will always deliver the greatest return.

Data engineering.

The next part of the equation is the traditional paradigm of BI, the tool set. This does require skilled capability of operators to bring the data-sets together; in reality its dealing with the content of data available. I need to be clear; I’m not trying to trivialise this part of the task, merely I wish to move the focus away from the established perception of what is ‘BI’. Moreover, I firmly believe this second part of the task is the field of ‘data engineering’. Real data engineers understand the value of presenting the content in a simple form.  Today that should be visualised and presented in the business context defined in step one.

Evidence-based decisions.

Finally, the part that I believe makes data intelligent is the decisions you make. What an organisation does with the context and content is the critical part.

The value of timely and accurate data is only realised if an appropriate decision is made based on the insights provided – the truly intelligent part. 

Knowing what decision to make can only be relevant if the context has been realised at the outset. Moreover, any decision made will in itself produce results. Those results must be entered back into the process if the intelligence capability is to grow.

If we are to get serious about the value of data, let’s get serious about how we use the vast investment by many organisations in the tools used. In today’s complex data world a relevant BI capability can only be the sum of all three parts.

Neil Glentworth
Executive Chairman