User Manual

MYTH 1: ONE SIZE FITS ALL

When it comes to choosing big-data analytics software to manage energy

and sustainability for an enterprise real estate portfolio, not all solutions

are created equal, or have equal application.

In our interviews, executives estimated that there are somewhere between

50 and 150 companies that have some kind of product offering, whether

it’s a building automation system, analytics, fault detection or some other

solution. Several of the executives we talked with were bemused by how

most of these providers say they do similar things, claiming “we can do

fault detection” or “we can aggregate and analyze all your data for you,”

even though reality doesn’t always live up to such claims.

Clearly, not everybody can do everything. According to Steve Frank of the

National Renewable Energy Laboratory (NREL), “A provider might claim

to do fault detection diagnostics for your building when, in reality, the

fault detection and diagnostics are very, very speciﬁc to certain kinds of

systems. So you might have a company that claims, ‘We do fault detection

diagnostics for HVAC systems.’ But what they really mean is, ‘We do fault

detection diagnostics for packaged rooftop units,’ and that’s it.”

Another obvious factor that providers often overlook is that different

buildings have different requirements. Chris Magee, Executive Director

of Sustainable Facilities for MGM Resorts International, observes, “Big

box retailers like Target and Walmart do a really good job, but they have

a straightforward path. They can build a central ofﬁce that might handle

HVAC and lighting control. We have such a diverse infrastructure with

theaters and changes in occupancy in our buildings and the towers and

the ballrooms. So we have to take a very sophisticated approach.”

Chrysler Energy Manager Faiz Yono concurs. “There is probably more effort

spent on the commercial side of things doing data analytics then there is

on the industrial side. They’re looking at more of a pattern of occupancy in

determining how they mine the data versus what we look for with a 24-

hour operation. I have to be a lot more creative about the type of energy

efﬁciency projects I do in this environment and that requires different

analytics.”

It is critical to understand the requirements of a speciﬁc organization’s

enterprise-wide building portfolio when determining a big-data analytics

strategy. This will drive a solution that works best for your enterprise.

Technology

providers often

overlook that

different buildings

have different

requirements.