Copyright: Zuraihan Md Zain
Big data and business intelligence (BI) bring oversized challenges to organizations looking to wrap their arms around the mountains of data available to multifamily firms today. At the 2016 OPTECH Conference & Exposition, a panel of leading industry experts shared best practices for getting your next BI initiative off the ground.
At the beginning of any new BI program, it can be easy to get carried away and try to solve every data issue in one fell swoop. Instead, evaluate what are the most pressing needs.
“You really need to start with what are the requirements of the business and what moves the needle,” said Scott Moore, executive vice president of strategy and innovation at Cortland Partners. “If you can focus there, the rest will come to play. Otherwise you’ll use the boil the ocean approach and never solve anything.”
Scott Pechersky, vice president of technology at Alliance Residential, hired a director of BI in the first six months of their initiative to understand where the information was coming from and what was important.
“Our property management software is really important, but there were key pieces of Google data or surveys that we really wanted to pull in. Information management and data governance is probably the most important part to get this off and running,” said Pechersky.
Auditing the data needs can lead to key revelations and new efficiencies. Your BI platform shouldn’t just regurgitate existing legacy reporting.
“Our people were creating this report in Excel, and killing themselves to make it. And our CEO said ‘I don’t look at this. I don’t look at that.’ He was looking at a completely different set of data,” said Scott Machado, director of information technology at Sequoia Equities.
Organizational buy-in is a critical step to getting BI off the ground. Given the level of effort required for a successful BI project, the panelists agreed that you need a senior level executive who can serve as an advocate.
“You need a champion,” said Machado. “It’s a lot of time. There are a lots of points of potential failure.”
“If you’re just starting out, try to find some ways to get some quick wins,” added Moore. “From there you can talk about longer term needs like if you need a data warehouse.”
It’s also important to understand the limitations of BI once you have a system in place. Many of the initial revelations may be from identifying where you have bad data. Moore described how his company’s maintenance requests went from being 20 percent closed on time to 80 percent.
“We weren’t actually only 20 percent on time, people just weren’t closing out the work orders,” he said.
Pechersky said that the next wave of BI is actually using data to anticipate decisions.
“We’re playing with IBM’s Watson to see if we can get some predictive analysis,” said Pechersky. “That’s the holy grail.”