Many IT projects fail to reach the finish line and are 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 finishing line and managed to solve some of the problems that were originally identified but created a whole pile of new issues on 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? Well, it is clear each of them have been business led.
In the last few years more and more of the failing projects have been business intelligence projects. There’s good reason for this – everyone has the data bug.
>See also: Bridging the business intelligence and analytics gaps
All the large consultancies are telling businesses that the population is creating more data than ever before. The value of big data is apparently through the roof, and companies are striving to add ‘data’ as an asset to their balance sheets.
Business is entering an age where information is perceived to be more valuable than people, their customers and even their products and services.
Everyone is rushing to build gargantuan data warehouses or buying data blending tools and everyone is looking to hoover up as much information as they possibly can.
There’s a fundamental problem with this though, 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. Businesses don’t actually need more data. They need the right data.
This is surprisingly true even as society enters a 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 businesses are standing on the outside of all this new technology looking in right now. So without piling all of this data into some deep learning, neural network and hoping for the best, how do businesses 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, you should 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.
Even in organisations where a true business need kicked started a technology project the IT function delivering the project often disappears into the office and only pops its head back out ten months later with a solution that resolved a completely different problem.
>See also: The pros and cons of shadow business intelligence
This is in no way ITs fault alone. More often than not it is a case of 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.
How can you keep your business intelligence project on the right track?
First, identify what it is important to the business. This will help working out what to measure. A clearly defined business strategy should provide everything needed.
Prioritising focus is also key to keeping heads above water. Waterstons, an IT consultancy, suggests starting with statutory and regulatory reporting requirements, then looking at financial needs.
It is crucial to know how much money is being made and how much is being spent. From there businesses can branch out based on the business’s focus.
If, for example, you’re a customer focused company then focusing on customers’ requirements should be the 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.
>See also: The new business intelligence
This highlights one final point: business led business intelligence is about making better decisions. Businesses measure performance so changes can be identified, and once changed organisations should continue to measure performance so that they can check that the decision they made has resulted in a measurable improvement.
This isn’t easy. Getting to the bottom of business 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.
Sourced by Alex Waterston, senior IT consultant at Waterstons