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iStar Financial

iStar Financial uses XLeratorDB to move its internal analytics from Excel to XLeratorDB

iStar Financial

When senior executives at iStar Financial meet for strategic planning, their focus almost always includes a review of numbers. A leader in commercial real estate investments, it has completed more than $35 billion of commercial real estate investments over the last two decades to become one of the most experienced companies in the U.S. commercial real estate finance markets.

iStar says it provides a Return on Ideas.

“We believe that great ideas, developed by great people, generate great returns.”

Reporting – transforming data into usable information – is key to increasing our effectiveness, said Philip Burke, iStar’s CIO. One of IT's consistent goals is to streamline processes while producing clean data that executives can rely on for decision-making without wondering where it came from, or how accurate it is.

“When you contrast today against the go-go-go days like 2007, back then it was just trying to get out of the way. Now we have created a number of systems to automate our processes. It is tough to be under that pressure and given that opportunity in IT, but it is interesting to be part of the company's productivity story.”

While Excel can be an essential tool for many internal analytics and projections, iStar realized that for its most sophisticated and critical models it needed something more robust. As firms across multiple industries from manufacturing and retail to financial services have learned, heavy reliance on Excel can lead to 'multiple versions of the truth'. One common result is business meetings that often start with dueling spreadsheets to decide who has the most useful numbers.

With $6 billion of commercial real estate assets to manage, iStar’s senior management team has better uses of their time than debating figures in multiple spreadsheets. The company invests across its four business lines: real estate finance, net leasing, operating properties and land.

For each project iStar creates an extensive asset summary that is part of its risk rating process.

“We rate our assets’ risk parameters every quarter on a scale of 1 to 5 based on our assessment of potential risk,” he explained. “Part of that process involves projecting total returns (IRRs) based on actual results to date and projected performance.”

“Before we acquired XLeratorDB, that component of our analyses was done offline on Excel,” says Burke.

The models were distributed throughout the company, and each asset manager in each region had different ways of using the models.

“It was impossible to really confirm that numbers had been updated and reflected the most current projections, because all you would see was the resultant number.

The metrics -- projected IRRs, projected multiples and earnings multiples -- were for internal purposes, he added. The shortcomings of Excel led to an internal managerial push to improve.

“The process was inconsistent, there was no visibility,” he added. If quarterly projections were not updated in Excel, that would not necessarily be apparent to headquarters which simply took the regional numbers and plugged them in to the database.

“We needed to correct this without implementing a quality control process that would eat up time.”

The company looked at two solutions before selecting XLeratorDB.

“It has been very useful in ensuring that our projections are more accurate because now we can dovetail our historical and projected performance and you can see any disconnect quite quickly.”

With XLeratorDB, cash flows are pulled from historical transaction systems and projections into the database and from there they stream into the report seamlessly. The combined cash flows are auditable and available online, and they are consumed by senior managers, the CEO and the executive committee.

“The process is faster, more accurate and we have control of the data from start to finish,” Burke added.

It is also much more efficient, important in a time when companies face pressures on margins.

“Every dollar counts now, and clean and accurate information in the hands of management is incredibly critical,” said Burke. “This management team needs to understand the risk/reward of every opportunity and structure in order to capture the best risk-adjusted returns. Being able to run many scenarios efficiently has increased our computational horsepower. It is all about how to invest that next dollar, what is our real return going forward, is it better to invest in project A or look at other projects with a higher rate of return.”

“Further it’s helped productivity as well. Now all of our reporting groups across the company are working from the same set of numbers in real time, cutting down on countless hours spent reconciling.”

With current reporting running smoothly, the next project using XLeratorDB is to create a historical asset return database, said Burke.

“We have purchased and managed hundreds of loans and assets for which all the asset cash flows and return data are stored separately in a spreadsheet somewhere. Now we are converting all the data into SQL and calculating the metrics.”

The first step is collecting cash flows into a single system for a single version of the truth, he added. Then iStar will provide the ability to slice and dice those historical cash flows and any other attributes such as region, property type, asset manager, and asset type such as senior debt, mezzanine debt or equity.

“It will be unbelievably powerful in understanding our historical performance. And with that, we can make better decisions going forward -- why were certain regions better performing than others, which borrowers stood behind the projects and which walked away? Which strategies proved most efficient for selling condominiums?

Internally, he has received positive feedback over XLeratorDB from people in operations. The company has reduced staff but still maintains strong demand for information, so technology has to take on the extra work.

“Information is more critical than ever. Through projects like these we are able to automate a lot of processes and give people back their time so they can do work that provides a higher rate of return.”

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