Over the past 22 years we’ve seen many organisations embark on internal IT projects. Of all those projects only a scant few could have been classified as being truly successful though. Of the rest:
- Many failed to reach the finish line and were abandoned, quietly ignored and eventually forgotten about with the remnants being sneakily swept under the carpet
- Plenty were dragged, often kicking and screaming, over the finish line to deliver a small proportion of what was originally promised
- A small number reached the finish line and managed to solve some of the problems that were originally identified but created a whole pile of new issues along the way
It’s actually only a small proportion that have delivered good business benefits in the end. Just a few that have not only paid for themselves but also generated a return. What is it about these projects that has made them successful? Is there a common theme? Yep, you’ve guessed it – each of them has been business led.
In the last few years more and more of the failing projects we’ve seen have been BI projects. There’s good reason for this – everyone has the data bug. All the large consultancies are telling us all that we’re creating more data than ever before, the value of ‘Big Data’ is apparently through the roof, and we’re working with companies that are striving to add ‘data’ as an asset to their balance sheets. We’re entering an age where information is perceived to be more valuable than our people, our customers and even our products and services. Everyone is rushing to build gargantuan data warehouses or buying data blending tools and we’re all looking to hoover up as much information as we possibly can.
There’s a fundamental problem with this though. As Nate Silver tells us in The Signal and the Noise, more data doesn’t mean better decisions. In fact, more data is, in the vast majority of cases, just confusing the issue. The more data you have the faster you approach chaos in every sense of the term.
You don’t actually need more data. You need the right data.
This is surprisingly true even as we enter this new world of machine learning. Many machine learning techniques are built around looking for the right data, seeking out that tiny signal in a sea of noise. Most of us are standing on the outside of all this new technology looking in right now, so more on that in a future article.
So without piling all of this data into some deep learning, neural network and hoping for the best, how do we sort the right data from the wrong data?
Well, instead of starting with all the data you have and attempting to piece it together in order to identify some correlations and then looking for causality, we flip the whole process on its head. Start with the questions that are important to your business. Instead of leading with technology, lead with business requirement. It sounds so simple but you’d be amazed how often IT leads the charge.
Even in businesses where a true business need kicked a technology project off we have found time and time again that the IT function delivering the project disappeared into their office and only popped their heads back out ten months later with a solution that resolved a completely different problem. I want to be clear here that this is in no way IT’s fault alone – we do see IT teams going rogue but, more often, we see business sponsors disengaging because they have other things to do.
Being business led is hard work. It requires much more engagement from all parties. It will, however, ensure you answer the truly important questions. This will help you to gain buy in across business users early on and, crucially, it will mean you don’t have to mothball any more failing projects. The initial cost might be greater but the risk is so reduced that it should just be common sense.
Let’s talk about how you can keep your Business Intelligence project on the right track. First up you need to understand what’s important to your business. This will help you to work out what to measure. If you have a clearly defined business strategy, then you can begin by diving deeply into that; it should give you everything you need.
You will probably find that there’s quite a lot that seems to be of great importance and you will need to prioritise and focus if you’re going to keep your head above water. Start with statutory and regulatory reporting requirements, then look at your financial needs. You absolutely need to know how much money you’re making and how much money you’re spending. From there you can branch out based on your business’s focus.
If, for example, you’re a customer focused company then focusing on customer’s requirements should be your first port of call. Map your customer experience and start looking at all the touch points your customers have with your business. Think about how you can measure how effectively you’re servicing their needs and how you can determine their satisfaction. Then bring in measures that will help to improve your service.
This highlights one final point: business led Business Intelligence is about making better decisions. We measure performance so we can see what needs to change and, once we’ve made changes, we continue to measure performance so that we can check that the decision we made has resulted in a measurable improvement. If you are staring at analytics that are telling you that things are going terribly but you cannot see why or what you need to do to turn things around then you need to focus back in and take a longer, deeper look.
I’ll be absolutely clear here – this isn’t easy. Getting to the bottom of your analytics will take time, care and thought but, if you’re business led, you’ll be looking in the right place and you won’t be swimming in a sea of metrics you don’t properly understand.