It's a fact that data is still not driving key FM decisions. Currently, businesses analyse less than half of the data they collect and FM often lags far behind. What analytics do you need to run a successful FM operation?

According to Forrester Research businesses typically analyse less than half of the data they collect. FM teams are the same, if not worse. Most FMs aren’t collecting data systematically, with only 30% using FM software to track and optimise their performance in any meaningful way.

How does data analytics help with FM planning?

The objective of analytics is to turn data into information, and information into insight. This insight helps facility managers, understand trends, identify work priorities, model outcomes and optimise performance. A good analytics package makes planning and forecasting FM resource requirements and budgets easier and more accurate.  

What data analytics tools do modern FM teams need?

There are 4 kinds of data analytics that can and should inform modern facilities management

  • Descriptive
  • Diagnostic
  • Predictive
  • Prescriptive

Learn how to write and present a world-beating business case for FM software

1. Descriptive analytics

Descriptive data gives you a complete historical overview of what’s been going on across your operations. For FM, this data can be pulled from all kinds of sources - work order and asset management records, as well as finance and building management systems. 

Available in one place, this data can tell you about:

  • The current state of your open work orders
  • The current state of your assets
  • The number of equipment breakdowns reported and fixed
  • Contractor hours billed, total maintenance spend
  • Your compliance status by site
  • SLA benchmarking across the board

The right data analytics package will convert this data into charts, graphs and tables that will show you trends in activity, spending, and other metrics that are significant to you. It will help you develop and set the KPIs that matter to you - the data points you need to track to show when you have been successful.

Looking at the descriptive data in your system should provoke questions.

  • What’s the reason for trends?
  • Why aren’t you hitting SLAs and KPIs? 
  • What could happen next?
  • How can I influence a better outcomes

2. Diagnostic analytics

The next step in data analytics is understanding what’s driving the trends and issues you can see emerging in your operational data. To be an effective diagnostic tool your analytics package needs to be able to isolate and overlay data to spot the causes of upticks and downturns.

  • Which assets are failing and why?
  • Are persistent failures associated with specific locations and specific equipment?
  • Why are some contractor costs spiraling?
  • Why do some contractors achieve a better first-time fix than others?
  • Why are some contractors responding and attending quicker or slower than others?
  • Why are certain members of my internal maintenance team so much busier than others?
  • Why are some members of my helpdesk slower at responding than others?

The right analytics tools let you zone in and troubleshoot particular areas of concern. Having the foresight to predict costly repairs, you can avoid emergency work orders and save money, helping you remain within budget.

3. Predictive analytics

Now comes the key question - what will happen next? Using data to predict outcomes is key to improving and optimising the way FM works. Wasted money can be avoided if facility managers use analytic tools to predict repair and follow proactive maintenance practices across their real estate.

  • Can you adapt your software to concentrate on improving service performance for certain underperforming contractors by adapting your automatic communications?
  • Do your FM tools help you calculate key metrics such as average time to equipment failure’?
  • Can you model future maintenance needs based on past events?
  • Can you use your data to create a predictive-based schedule that reflects the recurring maintenance needs of your equipment? 

4. Prescriptive analytics

Prescriptive analytics is about using data to support strategic decision making.

  • Can you flag your costs to be audited when you don’t receive the service you have asked for? For example, making savings by auditing a cost for missed Attendance SLAs
  • Can you remind your supply chain with improved communications to improve service performance?
  • Can you improve the quality of the data input from sites to achieve a better first-time fix? 
  • Can you use your data to model a different future? Consider a significant piece of equipment (like a refrigerated unit or an HVAC) that is constantly failing.
  • Can you assess the potential costs of repair going forward against the cost of replacement?
  • Can you calculate the optimal time for replacement and capital expenditure?

Analytics really matter 

Data analytics are critical to any FM operation. Without the data available to look at past performance, diagnose problems and predict potential outcomes you won’t be able to determine and track KPIs, set realistic targets and model a different and more profitable future. 

But today many Facility Managers are relying on patchy and fragmented data (backed up by experience and gut instinct, of course) to drive their resource allocation and strategic decision-making.  But effective data analytics takes the guesswork out of budgeting and planning, and helps you choose the best course for your business.

But access to data is pivotal

Even so - right now, the most important data is often in short supply for FM teams. Data around contractor performance, asset condition, and budget expenditure might all exist - but it can’t be easily accessed, analysed and cross-referenced. 

As FM teams have been slow to digitise, data is not in a single, accessible place or format. It can be:

  • Spread out in Excel files, servers and paper documentation
  • Lying ‘unstructured’ and noticed in emails and other outputs
  • “Locked up” in Business Management System or equipment hard drives

Businesses that want to release this data need a plan to get them from a state of fragmentation to a single source of operational truth.  

Choosing the right CAFM tools will help FM teams first centralise their operations, ensuring all engineers, contractors and managers are tracking the following in one place:

  • Users from every stakeholder
  • Work orders
  • Supplier services
  • Asset service history
  • Communications
  • Time & attendance records
  • Compliance documentation
  • Costs and invoices 

Then, when they’ve started gathering, controlling, and reporting on these fundamentals, the right tools will help them scale up their data capture and analytics capabilities. Through the right integrations with financial software packages, business management systems, and even IoT enabled equipment, companies can then become ever more sophisticated in the way they monitor success, predict issues, and model different financial scenarios.

In this way the CAFM system will become a hub of information and analysis that the entire business uses and relies upon.

The right FM software partners will help you on this journey. But they won’t demand you run before you can walk. They’ll help you build a strong foundation of FM data collection across the business - that can then support the data analytics activities that will move the needle for you.How to choose a CAFM system

Tom Wilcock

Written by Tom Wilcock

Tom Wilcock is the COO and Co-Founder of Expansive Solutions. He is a digital expert with a background in delivering large-scale business digital transformation. He specialises in project management, product user experience, business ecosystems and data intelligence.

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