The beauty of business intelligence systems is that they provide structure and capture a ton of data-a fact that can be, in some respects, overwhelming to the people tasked with using the systems. Many industry executives have found that they needed to more clearly define the specific data sought and, in some cases, tighten system capabilities, narrow data fields and better script final data presentation to avoid data overload.
As one industry executive put it, “Good business intelligence is like a good self-guided tour; it’s all mapped out for you, but you choose where you want to go.”
Another lesson learned for many executives is that the quality of the business intelligence is only as good as the data being inputted; more discipline is often needed. One executive pointed to move-out codes as an example; many companies often have too many codes, which can make it more difficult to pull meaningful information out of the system. By rethinking the number and type of codes, the executive said his company learned that roughly twice as many move outs were residents moving to another company-owned community than previously thought.
However, during a roundtable discussion on technology and corporate strategy, a number of executives expressed frustrations about the rigidity of many business intelligence systems. Many blamed consolidation in the technology sector for leading to stitched-together technologies that ultimately are inflexible in many respects. Executives said they often have to do one-off alterations to customize off-the-shelf products to meet their specific business needs. Having a higher level of customization or a larger menu of options within the systems would be a competitive advantage or market differentiator, executives said.
The ability to access benchmarking data was also a noted shortfall of many business intelligence systems.
Beyond just the question of getting the right data, the other question is of storage-what to keep, where to store it and how long to keep it. Many apartment firms have started business intelligence data warehousing initiatives, but as one executive said, “It can get so exponentially large, you need to step back and say, ‘Okay, what do we want to do with this data?’”