Businesses have always kept a close eye on expenditure. Whether that’s been spending on capital items such as plant and equipment or operational expenses such as maintenance and energy, companies have looked to maximise the return on capital investment and manage operational expenditure as effectively as possible.

At the heart of that have been two keys: information and intelligence. The ability to access the right information at the right time, combined with expertise and experience have guided businesses. But our ability to achieve further efficiencies using these tools has plateaued. The next phase of efficiency gains will be turbocharged through the use of advancing technology.

Start with data

Great decisions always start with having timely access to the right information. Investing in technology that can collect the right data and normalise it so it can be used is a critical step in supporting any business as it seeks to better manage operational and capital expenditure. 

For example, using IoT sensors, it’s possible to monitor performance and perform pre-emptive maintenance. When the performance of a machine starts to drift away from its optimal specification, this can trigger an alert so a maintenance engineer can fix the issue before it escalates. This could be anything from oil pressure in a compressor through to excessive oscillation in a fan. Almost any machine can be monitored but much of the data that is produced remains opaque although it is incredibly valuable.

People + machine learning

The challenge with taking a data-led approach is that the volume, velocity and variety of data exceeds what people can process in the available time. But machine learning can support people by doing a lot of the heavy lifting. Models and algorithms can be built to learn and understand the normal operating behaviour of large systems in commercial buildings, warehouses and other large complex environments.

When a set of conditions are met, this can trigger an event. This could be anything from increasing the temperature to alerting the maintenance team that a machine is nearing a potential failure. The data can even tell the technician what component is in danger of failing so a replacement can be ordered ahead of time.

This approach not only ensures the more timely detection of issues and faster remediation but also removes the guesswork from fixing problems. When the data tells you precisely what’s going on, better decisions can be made. Experience and intuition are complemented by data.

Building technology = better decision making

The ultimate goal of using technology in this way is to make better decisions. As well as delivering significant operational benefits, data can be used to support improved capital expenditure planning. 

Data delivers a greater understanding of how equipment is being used. For example, in a building there may be two chillers used to maintain a comfortable working environment. One may be a high capacity unit while the other is a smaller unit only used during busy times. When the time comes for the larger unit to be replaced, the temptation might be to make a like for like replacement. But by using data such as energy use, businesses may discover that it’s more cost effective to operate two smaller units all the time rather than one large unit. This delivers operational benefits and reduces your capital costs.

Using data intelligently helps businesses take the gut feel and guess work out of operational and capital expenditure decision making. By collecting data and using it with AI and machine learning models, technicians can detect and remediate issues faster than ever before, resulting in improved operational efficiencies and reduced downtime. And the C-suite can be empowered to make better judgements about where to allocate capital funds.