How data analytics can improve real property management

Rana Lahiri and Mark DeRosa.

Rana Lahiri, left, and Mark DeRosa say improved analytics can help alleviate problems caused by poor utilization of federal real estate.

Who is the nation’s largest property owner?  According to the latest data from the Federal Real Property Council, it’s Uncle Sam.

Here are three staggering numbers relating to the federal government’s real estate inventory:

  • 3 billion square feet: combined area of the federal real estate property portfolio.
  • 80,000:  number of federal properties that are either completely unused or sorely under-utilized.
  • $1.7 billion: dollar value paid by taxpayers for upkeep of unused federal properties.

At NASA alone, a 2012 inspector general assessment found that the real property inventory consists of more than 100,000 acres, including more than 44 million square feet within approximately 5,000 buildings and other structures. Over 80 percent of these facilities are 40 or more years old, and NASA faces a backlog of deferred maintenance, totaling $2.5 billion.

These statistics demonstrate the enormous breadth of responsibilities the federal government faces in managing its real estate footprint. Luckily, the opportunity exists to adopt leading-edge technologies to help agencies be good stewards of that footprint.

The Promise of Data Analytics

Poor utilization of federal real estate and facilities is a pernicious budget problem. Not surprisingly, GAO’s 2013 High Risk List includes management of federal real property as a notable issue. However, federal property managers have a golden opportunity to turn this worrisome situation around. 

With improved analytics, organizations can better predict their future portfolio utilization, moderate operating costs and potentially defer or eliminate costly capital projects. To do so, agencies first need to understand how data analytics related to financial performance of the federal real estate portfolio can help with:

  • Ascertaining key performance measures.
  • Accounting for all of an agency’s assets.
  • Forecasting future facility demands.
  • Determining space requirements that align with agency missions.
  • Notifying owners about potential financial risk.

With limited off-the-shelf solutions available, the agencies can accelerate to a next generation analytics model. By implementing, managing and utilizing disparate big data sets through a seven-step data analytics process, government can create a symphony of real estate management enhancements:

  1. Identify data sources to define what information is needed to serve as the input for subsequent stages.  
  2. Collect and integrate data to extract and collate it in preparation for analysis and reporting.
  3. Prepare data to cleanse and transform it into meaningful information that the end-user can trust.
  4. Analyze and validate data to detect patterns and trends to make informed decisions.  
  5. Report and visualize data that quickly displays relevant information in tabular/text format as well as graphical output (dashboards, scorecards and maps) and helps users consume information.
  6. Create predictive models to forecast scenarios around space utilization, capital risk, spending cycles and sustainability.
  7. Evaluate and improve the methods, from data identification through information delivery.

Using this approach, agencies can begin to build their real estate analytics framework from the foundation up. Fortunately, current technology trends are unleashing promising cloud-based solutions that provide client, web and mobile options. Cloud-based solutions, sometimes referred to as “off-premise” platforms, ease deployment and maintenance concerns. The result: a federal real estate community capable of delivering consistent and reliable information.

Ultimately, a high-velocity business intelligence process helps federal real property managers realize the true advantages of analytics. It enables a comprehensive solution that is flexible, tailored, proactive and, most importantly, not siloed for real estate executives.

Agencies that embrace the possibilities of such analytics have the potential to compress operating and energy costs through improved facility utilization to achieve savings of 5-12 percent annually -- numbers that can be music to everyone’s ears.

About the Authors

Rana Lahiri is director of the real estate consulting practice at Definitive Logic, a performance-based organization headquartered in Arlington, Va., that provides management consulting and systems engineering services to government and commercial clients.

Mark DeRosa is director of business intelligence and analytics at Definitive Logic.


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