Posted by Martha Bennett on July 29, 2013
Too little data, too much data, inaccessible data, reports and dashboard that take too long to produce and often aren’t fit for purpose, analytics tools that can only be used by a handful of trained specialists – the list of complaints about business intelligence (BI) delivery is long, and IT is often seen as part of the problem. At the same time, BI has been a top implementation priority for organizations for a number of years now, as firms clearly recognize the value of data and analytics when it comes to improving decisions and outcomes.
So what can you do to make sure that your BI initiative doesn't end up on the scrap heap of failed projects? Seeking answers to this question isn't unique to BI projects — but there is an added sense of urgency in the BI context, given that BI-related endeavors are typically difficult to get off the ground, and there are horror stories aplenty of big-ticket BI investments that haven’t yielded the desired benefit.
In a recent research project, we set out to discover what sets apart successful BI projects from those that struggle. The best practices we identified may seem obvious, but they are what differentiates those whose BI projects fail to meet business needs (or fail altogether) from those whose projects are successful. Overall, it’s about finding the right balance between business and IT when it comes to responsibilities and tasks – neither party can go it alone. The six key best practices are:
· Put the business into business intelligence.
· Be agile, and aim to deliver self-service.
· Establish a solid foundation for your data as well your BI initiative.
· Select the most appropriate tool set.
· Seek external help if needed.
· Make change management and training an integral part of any BI initiative.
Where there are best practices, there are by definition also pitfalls to avoid. We identified the most common ones as:
· Taking an IT-led approach may seem easier.
· Choosing too rigid a process – or none at all.
· Treating governance as an afterthought – or overdoing it.
· Allowing technology selection by accident.
· Abdicating your responsibilities after you’ve brought in external partners to assist.
· Focusing on technology development and roll-out rather than change management and training.
Applying the best practices that we've identified – and avoiding the pitfalls - will help deliver the BI capabilities required to make organizations more data-driven. Read the report Best Practices: Maximize Your Chances Of Business Intelligence Success to find out more details about the best practices as well as the pitfalls, and why they’re so important.
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