You probably have a lot more building data available to you than you realise. Here’s Iain Robinson on how to identify it, use it and keep it tidy.
Before you even start having conversations about pouring data into a BMS (building management system) to automate and streamline your operations, take stock of the data you’ve probably already been tracking and recording. At Grosvenor we tend to divide it into categories: maintenance data (or human-made data), utility data and machine data. Maintenance data is manually collected on-site by technicians, engineers, service contractors and vendors. It could take the shape of maintenance reports, service reports, annual checks and such like. Every site holds a large, growing chest of maintenance data. Next is energy or utility data: electricity, gas, water and all those associated bills. Finally, there’ll be machine data from various services already running on the building. This could come from a lighting system or a fire services system, CCTV, energy metering or perhaps solar – it’s your overall services in general. Even smaller buildings have this running. While today it’s being connected, integrated and used to automate building management, all this data can also be used manually with a good data strategy.
Any data strategy should start with you taking a look at what you’re trying to achieve. Think about possibilities, yes, but also clarify the objectives. Are you looking to enhance tenant experience? Reduce energy consumption? Often you’ll just be looking to save money. That’s where you start: have a clear idea of what you want to do, because then an auditor, BMS system, consultant or adviser can guide you in your data journey.
I can give you an example. We’re currently working on an integrated services proof-of-concept with a large property company in Australia, across two of its warehouse sites. Its end goals are essentially to guarantee customers the best value on resilient and sustainable building, and to reduce operational costs through better preventative maintenance, informed by transparent reporting and deep insight from building data. It currently has multiple smart systems, but none of them are talking to each other. We got involved at the design stage, and now we’re finalising the scope of the work to integrate these services and push all that data into the cloud.
For us, the first stage of the concept is ‘how do we get all of these devices talking?’ across a common network, where the data is easily accessible regardless of product or vendor. How do we get that data to a common point?
The next stage is working out how to visualise that data and what is to be done. We can make recommendations out of our experience, but at the end of the day it comes back to what the facility manager wants to achieve. It’s clear things will change throughout the process, which can in turn change outcomes, but it must finish where the customer needs to be.
It works out better for everyone that way, when you can set up baseline templates, a structure for moving forward to how the data will be connected with other systems and buildings.
Once you have an idea of the knowledge and insight accessible to you – the data you already have – it can start to sort of flow into one. You may seek a professional asset audit, while also considering the installation of a system that can help you store, review and action your network of data. Here’s where the BMS really comes into play – you can integrate your systems to run in one conduit. For our property client, we’re currently at the point where systems, services and contractors can communicate in common languages and protocols, so all can be connected up. It helps them understand the how, the when, the where and the why of everything going on in their assets, and helps us compare future options and solutions.
Throughout this process, we come across different services contractors with different offerings; there may be a third party offering that gets the same thing done with a better cost rate or more efficiency, or gives us scalability moving forward, but now we can compare and make the right choice.
Data overload is something to look out for right from the start of your data journey. It’s something I think we’re all going to get no matter what we do. Again, a focus on your goal and what you’re trying to achieve at all points will help minimise this. Too many people track things for the sake of tracking, or gather data without this clear idea of objective or outcome. When that happens, data can just become white noise. Make sure you’re always coming back to that desired outcome, from which you can backwards engineer it to the data strategy design stage.
To help manage this, you can familiarise yourself with standards like Project Haystack or Brick Schema. These get your data speaking the same language. When you follow naming conventions and data tagging, you give meaning to the data collected, helping you process and analyse it. You can also find relationships between data items and trends. It keeps things consistent so you can compare your data to that of another building. Many industry bodies are now working to these guidelines, and there’s a big focus from practitioners on getting this part right, which is great.
These will even help you compare your maintenance and machine data, as you’ll have consistency with how they’re collated. It will also future-proof your operations, regardless of resources or personnel changes – because the scope is adhered to as best as possible. I’ve seen it applied within the industry, and even when things changed, users managed to keep it consistent for their customer base or their application. These systems give you great guidelines with which to move forward.
Iain Robinson is Operations Manager – BMS – at Grosvenor Engineering Group.
