Pros vs Cons: The 3 Maintenance Models in Commercial Buildings

Successfully managing maintenance in your buildings means just one thing: finding that ideal balance between preventative costs and performance outcomes.

Fortunately, there are new technologies and processes that can help you achieve that operational equilibrium. Unfortunately, most maintenance models in commercial facilities have remained the same for decades, creating a massive disconnect between the evolution of operational technology and the strategies facility teams can leverage to keep their buildings and equipment running.

Current best practices often cause building managers to struggle with inefficient processes and a lack of accountability, factors that can impede proactive decisioning. To truly modernize, facility leaders need to be able to track and forecast maintenance activities, democratizing data to assess performance, and decipher new ways to increase efficiency, productivity, and autonomy – especially in enterprises that manage many sites.

Let’s dig in to understand the real pros and cons of the 3 maintenance models in commercial buildings.

Model 1: Reactive Maintenance

The break-fix method, also known as ‘run-to-fail’ is the oldest, and simplest strategy for managing equipment in buildings. Put simply, building managers allow assets to operate until they fail and then they repair or replace the equipment. The obvious pitfall is the impact on asset lifecycles and the significant effect this hands-off approach can have on a company’s productivity and reputation.

Accepting that breakdowns will eventually occur does offer a few short-term benefits to operators:

  • Low day-to-day operating costs.
  • A minimal requirement for full time facility staff.

However this trade-off to maintain low operating and labor costs often results in an increase in average utility costs and environmental impact due to the poor performance of equipment over time. In addition, large capital expenditures are required more often when building equipment is not properly maintained. And of course, faulty equipment leads to more downtime which can impact the productivity and experience of those using the building – leading to:

  • Compliance issues and penalties.
  • Loss of revenue.
  • Damage to company brand equity.

In short, cutting corners on maintenance doesn’t pay off in the long run.

Model 2: Preventive Maintenance

The drawbacks inherent in break-fix strategies made room long ago for the preventative maintenance programs that occur in most buildings today. Scheduled, or calendar-based maintenance models involve regular inspections of building equipment and services performed (often by third parties) at regular intervals either time-based, or through usage-based triggers such as hours of runtime or number production cycles.

The benefits to a preventive approach over a reactive model are numerous. Equipment that is regularly inspected and serviced with the replacement of small components (such as belts, fans etc.) is more dependable and efficient, ensuring:

  • Minimal downtime.
  • Stable efficiency and energy savings.
  • Reduced CAPEX costs resulting from extended asset lifespans.

While this method may be more cost-effective in the long term than a break-fix approach, it doesn’t stand up well to the original goal: “finding a balance between preventative costs and performance outcomes.”

Preventative maintenance costs sit in perpetuity on the facility leader’s balance sheet; and with much of the labor performed (and paid for) based on technician man hours rather than a transparency of data, there is low accountability between facility leaders and service providers – leaving facility leaders wondering:

  • What return am I getting for my maintenance investments?
  • What percentage of the components replaced at pre-determined intervals are truly necessary?
  • How much downtime have we avoided?
  • How much energy consumption and emissions have been avoided?

Labor-based, scheduled programs leave building owners and managers blind to the outcomes of the services they pay for and busy managing a continuous barrage of service visits and invoices. Yet one thing remains certain, some percentage of the work performed is wasted on equipment that is running perfectly well at the time of service.

Model 3: Predictive Maintenance

If equipment could speak, if it could self-diagnose and alert facility staff when a malfunction occurs or an issue is impeding energy efficiency, technicians could service equipment without wasting time performing inspections or replacing parts unnecessarily. In this way, facility staff could preserve reliability, energy efficiency and asset life without the financial waste.

So how do we enable equipment to speak? Through the democratization of data.

Breakthroughs in the IoT, remote connectivity, cloud computing, and machine learning analytics are coming together to make predictive technology a viable component in the digital transformation of building operations.

By performing equipment condition monitoring and applying statistical, machine and deep-learning algorithms, Predictive Maintenance technologies can empower facility teams to:

  • Identify unseen anomalies in equipment - before they become large malfunctions.
  • Know when equipment components need to be replaced - without regular inspections.
  • Visualize asset performance data and aggregate that data across sites.
  • Accurately determine the ROI of their maintenance expenses.

Conclusion: The Future is Predictive Maintenance

Adopting predictive maintenance technologies isn’t just another step in the evolution of building maintenance, it’s a transformation in which facility personnel fundamentally change the way they work. As they do, real estate leaders and facility teams are likely to experience:

  • Improvements in energy efficiency, environmental impact, and asset lifespans.
  • Increased transparency in maintenance services and outcomes.
  • Reduced cost of ownership within their buildings.
  • Greater control over their data, people, and portfolio.

Shifting from a manual-first, reactive mindset to a data-first series of processes empowers teams to perform the right service, in the right place, at the right time - without the guesswork and without the waste. And as many in the industry have attested, adopting data-driven processes like these is the first true step towards a future of autonomous building operations.

To gain a more in-depth understanding on predictive maintenance technologies, including steps on how to get started, read the whitepaper: The Evolution of Predictive Maintenance.