As the Information Age continues to gather pace, there’s three terms which continue to pop up about becoming data driven:
These three areas are generally presented as three separate capabilities, each offering something the other areas can’t. This perception is reinforced as the companies offering these services continue to try to differentiate themselves by coming up with all sorts of creative names and descriptions. To make things even more confusing, there’s hundreds of different technical terms which get thrown in - things like Hadoop clusters, test driven development, responsive design and my favourite architecturally driven dissemination (whatever that means).
The result of all these words getting thrown around? Key decision makers who know the exact effect they want have no way of deciphering the noise to see if the method being proposed will give them this result.
In this post, I’m going to offer my perspective on these terms and explore the central question: Is this method going to give me the effect I need?
The Endstate: Competitive Advantage
It doesn’t really matter if you’re a not for profit, government organisation or good old profit driven enterprise, the entire purpose of organisations is to deliver lasting value to key stakeholders. It follows, then, that the entire purpose of becoming data driven is to allow your organisation to create a competitive advantage through the capture, analysis and dissemination of relevant data across your organisation. In my mind, I define this as:
To deliver decision quality information to decision makers when and how they need it.
And that’s where it really starts. There’s actually no point in investing in becoming data driven if there’s no competitive advantage to be gained. Furthermore, unless an organisation invests in becoming data driven with an understanding that this the greatest competitive advantage to be had, there will not be the will to go through what can often be an uncomfortable change process.
With this in mind, I present a picture on how these terms all relate:
Starting at the base of the triangle, I’ll tackle Information Management first. In a previous post, I go into detail about some of the aspects of what information management is, but in the context of this discussion, I’d like to add some thoughts.
Creating, controlling and delivering the flow of information across the organisation.
Put simply, Information Management is really the delivery, when and how mechanism of being data driven. There’s plenty of different terms and methods relating to this, and the companies selling this stuff will often talk at length about their Operating Systems, Hadoop clusters, storage solutions and why their technical solution is better than the oppositions. One day I'll write about some of my experience in this area, but it's key to understand that regardless of using Red Hat, Windows Server, SQL Storage or No SQL storage you're still ultimately building the pipes which connect an organisation.
It’s for this reason that Information Management is at the base of the triangle. The first challenge for any organisation is to figure out what on earth they’re trying to track (data), who needs what (information) and how to get it there (management). Understanding this flow and then enhancing it will literally change how you do business!!!
The natural desire once data is being gathered and information is being passed around, is to start analysing the day to day transactional nature of things to see what deeper insight can be gathered. There’s a fair bit of art and science which goes into this analysis, but really, from an effects perspective, analytics can be defined as:
Finding out what the gathered information is telling decision makers about their organisation.
This is where all the branches of analytics spring from. All the different methods which get mentioned in sales pitches are really about trying to give decision makers quality information about what is happening, relieving them and their staff of the burden of gathering this information themselves and it’s something I’ve written about in previous posts.
However there’s some pretty important intricacies about analytics which often get missed.
Firstly, analytics requires a pretty equal split between data scientists and operationally focused individuals. It’s imperative that any solution is developed in tandem with an organisations culture and decision making process.
Secondly, analytics is never ending (at this stage). It seems that the deeper you go into analytics, the more you realise that you’re just scratching the surface. For instance, in my latest work, I and a team of five individuals are tracking user interactions with data to start speeding up how quickly this information gets given to them. I’ll go into this in a later post, but in this instance, my team and I are actually developing analytics upon analytics, with predicted massive increases in efficiency. The take away point about this is there’s no such thing as a one off purchase in this area.
As the top part of the triangle, business intelligence spans the point at which analytics is fed through to decision makers. It requires an effective information system combined with quality analytics and will take a while to get going.
The art and science of providing decision quality information to all decision makers.
Theres a few points I’d like to make here about business intelligence.
Does this method give the effect required?
Hopefully by now a method of assessing how effectively you manage your data is being drawn out, along with a framework for building your own capabilities. Here’s a few questions I typically work through with any team I’m involved with to continue to build this framework.
To wrap up today, I’d like to take the time to encourage you if you’re on this journey. The Information Age transformation has just begun and it’s only gathering pace. Mastering the three areas discussed in this article will take time and be a hard journey, but it’s worth it when you start to see what can be discovered about your organisation!
I love analysing data. I've done it for nearly 10 years now in various shapes and forms, and for me it's an endless world of wonder. There's nothing else I'd rather be doing!