Using Data to Allocate Time & Capital across a Multi-Family Real Estate Portfolio

Data-driven decision-making is the process of basing operational and investment decisions on actual data, rather than intuition or observation alone. With an 11,500-unit portfolio stretching across 14 states, we develop operational and design strategies around energy and water usage, costs, and tenant comfort for each building. Our data sources are public, invoice-derived, meter or sensor-derived, along with human observations and interactions, and range from continuous to quarterly. The decision-making drivers are based on sustainability values, investor thresholds, regulatory benchmarks, tenant comfort, property business plans, and capital cycle and constraints. This data-driven process allows us to preemptively identify problems within properties as well as opportunities to improve tenants’ experience and increase net operating income. We’ll show how you can do the same for your properties.

Session Chair(s): 

Event Time: 

Thursday, September 24, 2020 - 12:30pm to 1:30pm

Experience Level: 

1 (no prior experience/knowledge needed)

CEU Information: 

AIA 1.0 LU

Learning Objectives:

  • Summarize how building data can be used to improve net operating income (NOI) in multi-family properties.
  • Identify building data sources and summarize how to use them to understand your building better
    Identify challenges and potential problems with data sources
  • Use multiple utility and data management platforms to make better decisions about allocating time and capital.
  • Describe case studies illustrating various data sources, platforms, project sizes, and various results.

Session ID: 

NYC20-112