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The Future with Effective Data Insights in Facilities Management

Keith Weston
About the author : Keith Weston

Managing Director, Sodexo Australia

Published on : 6/24/20
  • Imagine waking up to a dashboard which presents you with your top three priorities for the day. This vision is one of the future innovations I look forward to in a world where data will curate and enhance many areas of our everyday lives. Data is around us everywhere, and while we’ve become adept at harvesting that information, it’s only useful if we can draw out key insights – it’s these insights which give us action.

    Anyone in the game will tell you that data is the world’s next major commodity, not just in facilities management, but across every industry. Working with data daily, the potential for innovation and exponential developmental growth is something I think about often. At the moment, I believe we’re only in the beginning stages of understanding how to leverage data for insights.


    I currently focus on developing our current capabilities in the facilities management sector, such as using data to schedule performance-based maintenance over and above calendar-based assessments.

    Generally, there are three maintenance models used by facilities managers:

    1. Reactive – fix it when it breaks;
    2. Preventative – check and repair as necessary;
    3. Predictive – use technology to predict when a problem may occur and fix it before it occurs.

    One statistic shared by Akita Box suggests 85% of maintenance spending is on reactive maintenance. As the name suggests, this reactive approach can elicit a knee-jerk response, rapidly deplete resources and cause further issues with a lack of strategy and planning. Fail to plan; plan to fail.

    The aspirational model is the proactive approach, predicting when an asset may fail, perform poorly or otherwise demand attention. This model allows for appropriate resources to properly maintain the equipment, while also providing cost-saving measures due to the reduced efforts to fix or replace parts prematurely.


    The last three decades have seen remarkable shifts in the solutions we apply in FM, thanks to the evolution of technology.

    Those of us working in the late 90s and early 2000s would remember when supply chains worked independently of each other – some solely for customers, some exclusively for suppliers. It was a time for experimentation, for the introduction of Integrated Workplace Management Systems (IWMS), and the evolution of FM to move away from bricks and mortar management to include assets and technology.

    Back then, it was a project management-style role with little to no reliance on data and a focus instead on removing costs through vertical integration. With all information encapsulated in one system, the essential tools for informing decisions became Enterprise Resource Planning systems (ERPs).


    In the last five years, I’ve watched data-driven insights and decisions become a staple of facilities management. Access to data mining and data science has created a highly competitive environment, where more substantial companies, with their extensive processes and systems, have little advantage over the agile and nimble smaller organisations.

    Now, the data driving your decision-making must be not only accurate but accurately interpreted. Data is only as good as the insight it provides. With this in mind, the data will only be semi-useful, unless you’ve identified and agreed on the:

    • problem or opportunity you are trying to measure;
    • reasons why;
    • data location.

    Businesses taking their data and converting it to useful information are the businesses that are achieving their commercial goals. Essentially, the ‘sweet spot’ is when you’re able to combine digital data forensics with predictive data to inform when and what facilities need maintenance.


    Predictive data models provide significant savings of time and money and create capacity efficiency. When data is monitored remotely through sensors and other digital parameters, we can redeploy personnel for more complex or creative work aligned with their skillsets.

    This predictive model needs to be driven from the top down. CEOs need to understand data better and then push this knowledge through an organisation, building core competencies in teams. Similarly, senior leadership need to continually be asking questions when it comes to the effective use of data – it’s a duty I try to hold myself to each day.


    At Sodexo, we leverage our ability to audit performance in real-time to ensure we can effectively collect data and convert it to useful trends, performance and information to drive change.

    The ability to take facts and figures and create a sentiment that can inform a response (such as measuring the temperament of a complaint) or predict future events is a levelled-up approach to FM. We currently mine and interpret data to get an accurate understanding of sentiment across our villages, portfolios and teams. The speed in which we can do this allows us to move from a solution concept to application in 60 days.

    Through continual learning processes using work order data, Sodexo is on track to achieve a 12.5% reduction in service visits due to the increase of first-time fault resolution and applying proactive preventative maintenance. Further, a 7.5% reduction in time spent servicing equipment and assets allows for higher productivity and cost efficiencies for clients.

    Cost savings and improvements in efficiency at this beginning phase of the data revolution is a taste of things to come.


    What will the future bring? There’s no way to answer that definitively, but I do have a few predictions.

    I think we’ll see more collaboration between data scientists and decision-makers, where now a communication gap exists. Data analysts need to mine like an analyst but think like a CEO and, on the flip side, CEOs need to challenge the status quo to inspire continual innovation.

    It won’t be long before many of our individually run activities, such as employee engagement surveys and customer satisfaction surveys, are integrated through data mining processes. Once this happens, facilities management companies will be able to build a barometer which alerts the level of maintenance required at particular sites.

    The pathway to innovation is through experimentation and by making mistakes. Sodexo encourages 80% tactical business activity and 20% ‘sandpit’ playtime to test and experiment with technology, processes, systems and procedures. We want to take part in the change and evolution of our industry and, more broadly, the universal use of data.

    Sodexo has recently released a report on current trends in the facilities management industry, including data mining and predictive data. You can read the full report here.  

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