Last year, Verdantix, an independent consulting firm, performed research on the use of technology in facility management outsourcing. They recommended that facility management service providers should utilize technology to improve service quality experiences and customer retention.
In 2020, Gartner, an analytics firm, proposed hyperautomation, also known as “Intelligent Process Automation”, as one of the top strategic technology trends for 2021. This process combines several separate software into a corporate IT strategy to identify, analyze, and improve end-to-end business procedures.
This strategy aids decision making, reduces error-related risks, improves operational efficiency, and enables improved employee performance. It does not necessarily remove people from the process – instead, hyperautomation empowers staff to focus on customer experience and more difficult, value-added tasks. In summary, this strategy helps service providers focus on collaboration and improving resource capacity.
Hyperautomation relies on software such as Robotic Process Automation (RPA), Machine Learning (ML), Artificial Intelligence (AI) and Process Mining to improve business workflows. When implementing these processes, it is important to ask questions, such as:
- How will these technologies help achieve organizational business objectives?
- What specific intelligent solutions is your organization looking for?
- What added value will the technology bring to your organization?
Before implementing these technologies, each company should consider a variety of perspectives to ensure they are investing in the correct and beneficial software to them individually. In addition, organizations must explore the quantitative (costs) and qualitative (user experience) perspectives of relevant use cases to craft a successful business acquisition.
Now, what use cases should a facility management service provider focus on?
Process mining is a technology related to data science and process management. It is used to support the analysis of operational processes based on event logs and is seen by Gartner as a subset of hyperautomation. When a service provider uses a single platform for all service operations, a process mining tool can easily determine inefficiencies and discover new processes as they occur. This information helps determine how processes can be optimized through automation and improve the use of other intelligent technologies, such as sentiment analysis. Process mining assists in determining where AI and other technologies have the most beneficial value in support of operations.
Contract driven process efficiency
A compelling AI use case for a facility management service provider would support process efficiency to increase operational margins and customer retention. 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%, according to facility manager Panorama. With margins being this tight, potential technology investments should support either revenue increase or cost reduction strategies to achieve the best impact.
The Service Level Agreements (SLAs) are a perfect example of producing the benefit and added value of AI, which varies by customer. Each deal is different with an agreement-specific bonus, malus rates on performance, and a diverse range of services offered. This process creates the need to evaluate each incoming request for work against these contractual parameters. Research from Verdantix proves that 56% of service providers have challenges with proving contract compliance due to gaps in monitoring performance.
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, there is a direct impact on profitability. For example, one way to do this is with intelligent capacity planning and smart dispatching, which considers both organizational resources and clients’ SLAs. Artificial intelligence can support this process through planning scenarios that optimize profitability, service quality, and customer experience.
Predictive and prescriptive analytics
By applying machine learning to data analysis, the identification of correlations enables the company to gain recognition. This is where the true business value of machine learning comes into play. Machine learning can identify hiccups in processes that people were not aware of. This is commonly used for predictive analytics, which provides insight into company evolution, and prescriptive analytics in response to new developments.
This allows a service provider to receive notifications when the system predicts that an individual contract could be more profitable if specific actions were taken; or if replacing an asset now would save money later; or if staff could be better optimized; or if there were actions that would increase efficiency.
Want to know more?
I hope that this helped display some of the valuable use cases and benefits of hyperautomation for facility management service providers. Are you curious to know how mature your digitalization strategy currently is and how your organization can move towards a hyper automated business? Take our interactive assessment to find out!
To explore this topic further, you can also attend our upcoming webinar “Hyper automation: the strategy to drive FM business growth” Tuesday, July 6 at 1:00 PM EDT. Register for this event today!