March 21, 2019

Intelligent processes driving efficiencies for service providers

Around this time last year, my colleague Geert van Offeren wrote about the importance of defining the business value and identifying the use cases your organization wants to explore before jumping into an IoT project. 

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As artificial intelligence (AI) is another frequent buzzword in the facility management industry, I want to stress the importance of using Geert’s advice when approaching this topic as well.

For organizations and facility management service providers, it is crucial to research the use cases that are relevant and valuable to your own organization. It’s important to answer questions like, what specific AI solutions is your organization looking for? What value will using AI in this way bring to your organization?

In addition, organizations must explore the quantitative (costs) and/or qualitative (user experience, building performance) perspectives for each relevant use case is to craft a successful business case.

Process Efficiency

A compelling AI use-case for a facility management service provider would be one that supports process efficiency in order to increase profitability. As our research has shown, the average profit margin from providing hard services is between 5% and 6%, while the margin on soft services is even lower at 2% to 3%. That means that improvement to this bottom line will need to be proven before any technology investment can be made.

Here’s one example of where you can prove the benefit and added value of AI: Service Level Agreements (SLAs) can vary per customer, as can the bonus/malus rates and the services offered. This creates the need to evaluate each incoming request for work against these contractual parameters.

The process of aligning services delivered with individual client contracts is one of the primary challenges service providers face in creating efficient business processes. When this process can be automated, you can see a direct impact on profitability. For example, one way to do this is with intelligent capacity planning and smart dispatching that considers both your organizational resources and your clients’ SLAs. Artificial intelligence can support several steps in this process.

Smart process mining

A process can be seen as a set of activities that are executed in a predefined sequence with predefined options. Processes are also generally conducted in a repetitive fashion. Any changes or deviations to and from the standard process are usually made by people. In some cases, the outcome of activities themselves are based on decisions made by people as well.

In well-defined processes, people make decisions based on data that is available in the context of the process. When the right data is available, and an artificial intelligence can understand the context, systems can start to make some decisions that people made earlier, creating the potential for high-speed operations.

Predictive and prescriptive processes

When machine learning is applied to data analysis, it produces capabilities in these systems to identify correlations not previously identified by people. This is where the true business value comes into play.

This type of AI can potentially solve problems or identify hiccups in processes that people were not aware existed. Applying this type of learning capability is commonly referred to as predictive analytics, which predicts developments as they evolve, and prescriptive analytics, which describes appropriate responses to developments.

This allows a service provider to get alerts and notifications when the system predicts that an individual contract could be more profitable if specific actions were taken; or if replacing this asset now would save money later; or if staff could be better optimized; or if there are actions that would reduce throughput time and make processes more efficient.

These are the use-cases that will drive artificial intelligence adoption in the world of facility management. Which use-cases are you working on? Do you see the benefits of AI? Let us know in our survey.

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