Six misconceptions of a BI implementation – part 1
Business intelligence systems provide a significant return on investment for organisations when they’re effectively designed, deployed and managed. But BI applications often have a more limited impact, and less of a payback, than they should.
Several indicators help illustrate the limitations and shortcomings of many BI deployments: A typical Fortune 1000 company implements six or more different BI tools; BI technology hasn’t become widespread at most companies, in fact, on average, the use of BI apps has plateaued at about 25% of business users over the past few years; Spreadsheets remain the only truly pervasive BI tool.
In many cases, the success of BI systems has been constrained by some common misconceptions about both the design and deployment processes.
Here are six:
BI applications should be designed for the business power user. Power users are the most active BI users, and they can offer insights on business needs and valuable feedback on the pros and cons of different BI tools, but the reality is that they don’t represent the characteristics of a typical business user. It’s the same as with new smartphones or other consumer technologies: The initial buyers (or users) are great to kick off adoption, but to be successful, products (or applications) have to reach out to a more mainstream audience. Too often BI systems are too complex or over-engineered for the mass of business users who just want to read reports or do simple data analysis through business intelligence dashboards. Companies can avoid this trap by becoming more inclusive and getting a variety of users involved in the planning and design stages.
One BI style will satisfy all business users. Originally, BI deployments involved a bunch of static reports that were distributed to end users. BI has evolved greatly over the years and now includes a wide range of analytical tools and styles. They include dashboards, scorecards, ad hoc querying, data visualisation, data discovery, self-service and mobile BI not to mention big data analytics, predictive analytics and other forms of advanced analytics. It’s all too common for BI teams to assume that every business user wants to analyse data the same way, with the same tools. Users get frustrated when they’re pigeonholed like that, and many revert to using their spread sheets.
BI systems work best when IT departments run report factories. Some IT groups and BI teams believe that the only way to consistently provide high-quality and high-performance reporting capabilities is for them to control the development of all the reports that business users want to see. Although their intentions are good, the results are almost never beneficial to the business. An IT or BI team that believes it can create all the reports a business needs will quickly be overwhelmed, leaving it with an insurmountably backlogged report queue.
Self-service BI means you just need to give users access to data. At the other end of the spectrum from centralising report creation are short-sighted self-service BI implementations. Self-service software offers plenty of potential business value and should be part of a BI portfolio, but it isn’t as easy as it sounds. Many organisations get caught up in the self-service hype and think all that’s needed for success is to give business users tools, grant them access to BI data and get out of their way. But users of self-service BI tools often need more support than expected — on an on-going basis. Also, self-service applications don’t reduce the need to eliminate silos of inconsistent and incomplete data. If they persist, effective BI analysis will be a challenge.