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fund a large-scale deployment as a first step. The good
news is that they do not have to. In fact, a cautious start
is recommended. Start with a small, well defined project
that focuses on easily accessible data. If you are unsure
of the benefits, don’t try to engage in a science project or
boil the ocean. Prove the value of analytics with a man-
ageable project. Look for easily available data and explore
the value that data can produce.

Using this approach will also highlight the challenges of
accessing equipment data, demonstrate the results avail-
able, and create processes to drive actions in accordance
with your capabilities. It enables a financial benefit with
low risk within a short timeframe. You will then be ready
to move on to expand and extend the use of analytics. As
you progress, you will be better able to ‘engineer’ the next
phase of your project.

Even with the inherent uncertainty, there are ways to
structure projects to minimize risk and validate invest-
ments. Some include:

• Look for proof in the market – success stories and
case studies abound. Analytics have been applied
across thousands of buildings and millions of square
feet.

• Engage with owners and operators of similar facilities
the age and feature set of their systems; others may about their experiences. Don’t stop when you hear a
be limited by proprietary restrictions, which often single good—or bad—story.
come as a surprise to owners when they attempt
to get data they thought they had access to. Often, • Start small to prove results – do an exploratory
owners and operators are not fully aware of the data project.
they have available and the challenges in accessing
it until they start an analytics project. That is in fact, • Plan organizational involvement. Analytics only save
part of the exploration process. money if you act on the findings. For example, if you
had 20 problems with your systems today, how would
Defining Project Scope - What are We Trying to Do you respond with triage, assessment, funds to address
with Our Data? the issues?
Analytic software is a tool that can be used in many
ways – from simple to sophisticated. For example, Starting Cautiously is Not the Same as
we could simply start by applying analytics to interval Staying on the Sidelines
meter data from a main electric meter to identify load One of the most striking things we have seen is how the
curves, demand peaks and compare these profiles and uncertainty can lead to decision paralysis, where orga-
performance to similar buildings. Or, we could acquire nizations delay doing anything and thereby forego the
data from all environmental systems by connecting financial benefits their operational data can provide. While
to a Building Automation System and perform Fault understandable, an over-focus on attempting to pre-engi-
Detection & Diagnosis (FDD) on all equipment systems. neer a perfect end result can prevent owners from moving
Both approaches would have value and enable different forward with steps that can result in fast and significant
insights into facility operation and performance. financial return.

How Organizations Can Deal with the Uncertainty Simply accept the reality that moving forward with data
With the inherent uncertainties, it’s logical that organi- analytics is an exploratory process. Initial results will
zations may not be comfortable taking a leap of faith to identify specific actions to be taken. Those actions will

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