Property owners and managers can make great strides by gathering property data. This is hardly a surprise; there’s almost no escaping the buzz around leveraging data to improve property- and portfolio-level operations. But data is not inherently valuable in isolation, and collecting data points to release a one-off report or resolve a single challenge represents a failure to properly operationalise.
Working together, day-to-day operational tasks and high-quality data can yield significant gains: reduced costs, strengthened resilience, improved sustainability performance, and streamlined operational efficiency.
In this article, we will outline the best practices every firm should consider to effectively operationalise their property data and realise the benefits of a well-developed data analytics strategy.
Put the data in context
Understanding the context behind your data is almost more important than the data itself. Even high-quality data amounts to little more than white noise if you don’t know why—and how—you’ll use what you collect. If energy consumption at a property is high, why is it high and how should Facilities Managers respond? What next steps will reduce usage without compromising tenant comfort? Consider early on how you will put your data to good use.
One way to do this is by aligning your data and business strategies. Any misalignment between values, strategy, and vision with the data you are trying to operationalise will create new challenges. If greener operations are a strategic focus, ensure you have the means to collect and interpret data surrounding your energy consumption and efficiency, identifying next steps to correct any gaps. Similarly, if tenant comfort and the customer experience top the list of key business drivers, do not commit to collecting data without understanding which metrics relate to this vision and how you will act upon them.
Another important consideration is to avoid getting bogged down with data overload. Site teams, for example, can become overwhelmed by ‘BMS alarm fatigue’ when there is a lack of refinement in terms of the data being collected and the associated alerts that it triggers. Rogier Roelvink discussed this in the FMA’s (Facilities Management Australia) recent ‘Facilities Perspective’ magazine,
“By learning to be more selective in the data and information they request, teams can help increase their knowledge and provide actionable insight, leading the way for greater productivity.”
Embrace the ‘Data, Information, Knowledge, Wisdom’ pyramid
The DIKW pyramid represents the relationship between data, information, knowledge, and wisdom. Each step builds upon the one before, answering different questions about an initial data set and increasing value with each level. The pyramid reflects a natural progression of putting data in context by focusing on increasingly targeted questions about building data as you go. Consider how this framework is applied to the context of outside air temperature lockouts below.
- Data: a raw chart tracking fluctuations in outside air temperature.
- Information: outside air temperatures are identified as sitting within certain thresholds.
- Knowledge: the building's chillers and boilers may be operating unnecessarily at certain hours, meaning efficiency gains are possible.
- Wisdom: implementing an optimisation strategy whereby chilled or hot water systems are either ‘locked out’ or made available for operation when the outside air temperature is less than or greater than a given setpoint.
The FMA elaborates on the nuance between data and information in the context of facilities management in their Good Practice Guide,
“Facilities information does not exist; it needs to be generated. Data is the source for information, containing the facts and figures obtained through measurement, monitoring and observation. Information is created by providing context for which the data becomes useful - giving meaning to facts and figures or combining datasets to conduct analyses whereby the outcome becomes useful.”
Redefine your company culture
Many businesses, especially those that have been operating for years, develop a culture of decision-making through ‘gut feel.’ But the biggest obstacles facing businesses aren’t technical; they’re cultural. Don’t neglect to emphasise a working culture in which employees rely on data to make decisions.
“We’ve moved away, thankfully, from that gut feel, ‘I think this is the right decision’. Having far better optics and transparency around what’s happening in your building really allows you to make that data-driven decision … so it comes from a position of knowledge, rather than, ‘I think it’s right.’ ”
This is particularly important for Facilities Managers, contractors, and anyone else on the operational front lines who implements data-driven decisions. Ensure that these teams understand the long-term impact of data on the business and why it matters. Develop strong data literacy at all levels of employees and parters, making it easy to interpret and act upon.
This will do more than strengthen your portfolio performance; you’ll also cultivate a team of data-minded individuals who deeply understand your mission. Further, by understanding the source and security protocol of datasets, team members will also gain the peace of mind that comes from knowing the tools they are using will not compromise the company’s data security.
Pair analytics with clear actions
An analytics platform that enables intuitive visualisation and reporting will deliver far more impactful ROI than one requiring tedious manual input. When any user—not just the technical experts—can easily assemble collected data to tell a straightforward story, the path to lasting organisational change and direct data impact is clear. Be sure to invest in platforms that deliver user-friendly analysis that identifies the next logical step.
Once you have a user-friendly analytics platform in place, make sure your data points directly to clear actions. If a sensor is malfunctioning, users should easily be able to determine what has gone wrong and how to fix it. Data and analytics for each property should align directly with actionable responses, making it easy for teams to take the next logical step toward achieving a resolution.
Digital data and analytics tools should empower non-technical users to find and fix faults, then go one step further by optimising their buildings and reducing energy consumption. A tool that merely delivers an alert about a fault is not enough anymore; to have operational relevance, it should also deliver a detailed description and diagnostic steps to resolve. This is the difference between having data and operationalising it.
Optimise data toolkits and organisation
Large quantities of data can get overwhelming very quickly without the right resources to hold and organise it. One serious barrier to collecting and sharing data across business units is a lack of effective, automated tools. Tools for digitising property operations must be flexible enough to integrate with your BMS and connect seamlessly with other onsite data points, creating a rich and complete picture for the operations team.
Grant access to as many team members as possible, limiting each user’s view to the metrics relevant to their team and role. If an employee can directly impact an outcome, they should have easy access to the data informing good planning around that outcome. Effective operationalisation cannot occur using manual entry spreadsheets and unplotted data. Instead, firms should leverage automated, cloud-based data platforms that save countless hours of labour and diminish errors inherent in manual entry.
These systems also provide a single source of truth that any team member can access and refer to when in doubt about the best way to proceed. Automated data capture that monitors building performance over time and can also zoom out to a portfolio-wide view is essential for firms looking to realise consistent performance improvement.
Data is not inherently valuable on its own, and one-off reporting or manual data tracking represent failures to properly realise the value data can provide. Data that tells a clear story, points toward next steps, and improves day-to-day operations is well worth the time and effort it takes to generate. Operationalised data can directly reduce operating costs, improve sustainability performance, enhance resilience and streamline operational efficiency.