In this article, we look at the challenge presented by the ever-increasing amount of data produced by complex buildings. We take a specific look at an often overlooked, yet crucial, element to data being used in an impactful way, people.

Complex buildings such as manufacturing facilities or office towers can produce vast amounts of data from an array of sensors and equipment. In this context, complex buildings could be described as “intelligent” or “smart”.

However, the complexity and quantity of data produced does not automatically mean building owners, on-site operations teams and contractors can actually utilise this information in a meaningful way. At best, this data can be used to improve operational efficiency, decision-making and workflow management. At worst, the data is collected and left unutilised.

The Data Landscape in Complex Buildings

Complex buildings such as manufacturing facilities use data and technology across all facets of their operations to improve supply chain efficiencies, productivity and quality to name just a few. Typically, different organisations are at different levels of maturity on this digital journey.

One area where most organisations are commonly lagging is in the use of their facility or building data. Often they have a building management system (BMS), building automation system (BAS) or distributed control system (DCS) that is poorly maintained and poorly understood.

In some cases, the system is no longer supported by the vendor due to obsolescence, which is both a security risk and an operational continuity risk in the event of system failure. In general, the BMS (or BAS, DCS) offers limited visibility and direction to guide facility maintenance and general operations.

Commercial buildings are similar in the sense that they have different amounts of data depending on the complexity and age of the building. However, they too have difficulties accessing and making use of building data for smarter operational decisions related to improved comfort, energy performance and maintenance efficiency.

This can be down to a number of reasons, such as proprietary data locks, a difficulty understanding the data or dealing with inherited workflows.

HVAC Maintenance and Data Analytics

The Data Challenge

There are a number of challenges every complex building owner must face when attempting to make use of the data produced by their building or facility.

Accessing the data – This is the first hurdle because data can often be controlled by the vendor with limited, or costly, works required to make the data visible and extractable.

Making sense of the data – Often the data is poorly named and configured, meaning even if you have access to the data, it is difficult for most people to decipher it.

Understanding what to do with the data – Often people have access to thousands of data points, but there is no real understanding on what to do with it or how to make use of it. Perhaps the most challenging step is turning raw data into information that can provide insights to guide decision-making.

To do this, you need to understand how to extract the data, what the data points are and what they mean to the system operation, but more importantly, understand how these individual data points converge to help improve decisions and create actionable insights.

Often, people are flooded with meaningless data and as a result, nothing is done with it. It is important to ensure that the extracted and stored data provides value, along with a clear way to use it to create value. Ignoring this aspect often leads to an ocean of information and alerts, but without anyone on the facility maintenance and general operations teams putting it to use.

The Importance of People

As mentioned above, the people relied upon to make use of this data are often overlooked. The importance of people, and how to best interpret and serve this data to them, is of huge importance if complex building owners and managers are to gain maximum value from it.

An ocean of data offers little to no value if it is not being used in a meaningful way. In other words, smart buildings are only as smart as the people who operate them, and how they interpret and use this data is crucial.

The objective, then, is to provide individuals and teams with the right data, at the right time and in a way that matches their skill level. Facility managers, engineers and contractors may be excellent at their job, but they are not data scientists. So, it is important to present data in a format they can easily absorb and put into action.

Responsibility and Ownership

Even if you use a building analytics platform to take in data, interpret it and give your teams easy-to-understand actions to work on, it might not be enough. Buy-in, responsibility and ownership will still need to be developed and nurtured among those using it.

The people and teams in charge of maintaining and improving the operational efficiency of a manufacturing site or complex building should be asked for their input and be involved in the implementation process. These individuals are the very people relied upon to implement changes and improvements based on the information uncovered by your building analytics platform.

A Cultural Shift

When looking at sustainability, which is just one aspect of running an efficient building, the need to provide your people and teams with data-driven, easy-to-understand actions was highlighted in a recent study.

A 2020 survey by the Institute of Engineering and Technology found that 67% of manufacturers and 71% of construction firms need more engineering and technical staff to reach the skills and knowledge needed to lower their environmental impact. This demonstrates the importance, and difficulty, of making sure end users understand the data and how to best leverage it.

The Solution

Very often, the issue faced by large complex buildings is not the ability to generate data, but more what to do with that data and how to turn it into actionable information and decision-making.

Building management systems (BMS) and similar platforms can offer some help here, but anyone working with a BMS on a regular basis will tell you their system rarely provides the right quality of information, especially when it comes to decision-making, prioritisation of tasks and workflow management. Or, it provides far too much information, causing BMS alarm fatigue and very few alarms ever being resolved.

Building Analytics

This is where a building analytics platform can make a huge impact. A building analytics platform sits above a building management system (BMS) where it collects data from multiple existing sources such as air handling units (AHUs), chillers and so on. The building analytics platform ingests this data, standardizes it and the best building analytics systems apply automated fault detection and diagnostic rules to provide you with prioritized actions.

Building analytics uses machine learning and building intelligence to provide you with metrics, insights and leading platforms will also deliver prioritised actions. It can find the exact root of inefficiencies and offer a solution. For example, if the temperature in an area fell out of its normal operating range, finding the source of the issue could be difficult because this error can be caused by any number of reasons. A building analytics platform will use data from multiple sources to help you quickly find and fix the issue.

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