Business Intelligence

Business intelligence, or BI, is an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. BI as a discipline is made up of several related activities, including data mining, online analytical processing, querying and reporting.

Companies use BI to improve decision making, cut costs and identify new business opportunities. BI is more than just corporate reporting and more than a set of tools to coax data out of enterprise systems. CIOs use BI to identify inefficient business processes that are ripe for re-engineering.

With today’s BI tools, business folks can jump in and start analyzing data themselves, rather than wait for IT to run complex reports. This democratization of information access helps users back up—with hard numbers—business decisions that would otherwise be based only on gut feelings and anecdotes.

Although BI holds great promise, implementations can be dogged by technical and cultural challenges. Executives have to ensure that the data feeding BI applications is clean and consistent so that users trust it.

When charting a course for BI, companies should first analyze the way they make decisions and consider the information that executives need to facilitate more confident and more rapid decision-making, as well as how they’d like that information presented to them (for example, as a report, a chart, online, hard copy). Discussions of decision making will drive what information companies need to collect, analyze and publish in their BI systems.

Good BI systems need to give context. It’s not enough that they report sales were X yesterday and Y a year ago that same day. They need to explain what factors influencing the business caused sales to be X one day and Y on the same date the previous year.

Like so many technology projects, BI won’t yield returns if users feel threatened by, or are sceptical of, the technology and refuse to use it as a result. And when it comes to something like BI, which, when implemented strategically, ought to fundamentally change how companies operate and how people make decisions, CIOs need to be extra attentive to users’ feelings.

Lai’s seven steps to rolling out BI systems:

  1. Make sure your data is clean.
  2. Train users effectively.
  3. Deploy quickly, and then adjust as you go. Don’t spend a huge amount of time up front developing the “perfect” reports because needs will evolve as the business evolves. Deliver reports that provide the most value quickly, and then tweak them.
  4. Take an integrated approach to building your data warehouse from the beginning. Make sure you’re not locking yourself into an unworkable data strategy further down the road.
  5. Define ROI clearly before you start. Outline the specific benefits you expect to achieve, and then do a reality check every quarter or six months.
  6. Focus on business objectives.
  7. Don’t buy business intelligence software because you think you need it. Deploy BI with the idea that there are numbers out there that you need to find, and know roughly where they might be.