Increasingly, social landlords are turning to the potential of enhanced Artificial Intelligence to strengthen their operational performance, and raise their levels of customer service and skills retention, writes Lee Hawkes
AI continues to be high on the news agenda, earning both a positive and negative spin.
The Beatles have used generative AI to enhance the audio on recordings made 45 years ago, enabling a new track ‘Now and then’ to be released. All whilst British prime minister Rishi Sunak announced a world-first AI safety Institute for the UK, examining risks such as bias, misinformation, and existential threats.
Many will recognise how chatbots began gaining popularity in the mid-2010s. The technology and its applications have significantly improved, making it more accessible and useful. We’ve moved from simple forms of automation to more complex queries.
This has grown opportunities in guiding tenants through the property search and application process. For the social landlord, the data provided is a gateway into screening applications, identifying reliable tenants, and reducing fraud.
Chatbots are one example of AI working for the tenant and provider at the same time. Today’s AI solutions are addressing a specific rebalancing: From pure-play customer service improvement to the transformation of operational performance.
For scheduling specialist FLS – Fast Lean Smart, AI has the power to transform field service management through our proprietary algorithm and machine learning capability. The initial idea behind it: How do operators achieve the optimal field service plan? How do they solve scheduling and in-day control of routing in the most resource-efficient and SLA/KPI-oriented way, and without having to wait for the answer?
This is a highly complex mathematical and logistical problem. If you analyse the optimal sequence of 10 field service appointments for a single operative, there are 3.6m solutions. Other influencing factors to consider include time constraints, fixed appointments and breaks, order specifications such as skills required, and human factors, such as illness and cancellations.
FLS’ solution, the PowerOpt algorithm, was developed and evolved over 25 years of specialist focus and has matured as the market has transformed. After all, new workflows, such as the Internet of Things (IoT), demand new decisions.
The algorithm is the core intelligence for optimised scheduling and dynamic route planning, taking into account all factors in seconds, scheduling appointments, employees, and materials. It makes it possible to control logistics and service processes in the field in a cost-optimised, sustainable and customer-oriented way, with complete transparency over the outcomes produced.
AI calculates in real-time, including predictive traffic on each road segment for the time of day, through continual optimisation of planning and ongoing coordination without intervention necessary.
Opportunities with AI-supported field scheduling
For social landlords, AI-optimised field service management is providing a solution to many long-standing topics, including the reduction of ‘no-access’ visits, planned maintenance backlogs, understanding the requirements of voids, and results -data supports compliance and tenant satisfaction reporting.
FLS’ AI enhances scheduling accuracy through sophisticated predictive analysis. This enables intelligent predictions about appointment durations and arrival times. Thanks to this machine learning approach, appointment accuracy is continuously improved, whilst taking the latest call data into account. Advantages include:
- ‘What if’ simulations for optimum capacity and resource scheduling
- Increased up-to-the-minute appointment accuracy using geo-coding and predictive traffic for specific journey times
- Improved scheduling accuracy for linked appointments and follow-up visits
- Increased customer satisfaction management through features such as enabling field operatives to begin shifts from home locations and built-in depot visits
FLS is Microsoft’s scheduling partner for Dynamics 365, seamlessly integrating with Customer Engagement and Field Service. Microsoft recognises FLS VISITOUR as the best-of-breed field scheduling, which extends beyond the capabilities provided by its own Resource Scheduling Optimization (RSO), and it’s this development of AI and machine learning that gained FLS their ISV and Managed Partner status.
The FLS solution is also available as an upgrade with most leading housing management systems.
Risks
Dangers appear when developing AI algorithms, including compounding human bias (should it exist) in collected data and modelling.
Oversight must ensure compliance with regulation and overall fairness. Intelligent field service automation is used to reduce response times and provide more precise information for customer enquiries. There could be data privacy risks for residents here, and evolving AI regulations that promote transparency and responsible use of machine learning models must be adopted before any blanket bans prevent their potential.
Predictive analytics evaluates historical data using mathematical methods that discover trends and patterns and incorporate them into a calculation model for future predictions. Social landlords are already using these to identify trends to counter mould, optimise energy management, and assist sustainable estate development.
The best-known methods for these evaluations include decision trees, regression, and neural networks. While decision trees and regression are relatively easy to model, neural networks require much more effort. They can be represented using AI and allow very precise recognition of patterns and trends in real-time.
They can only be used effectively if a corresponding volume of intelligent data is available. Intelligent data is created with clear objectives, diverse and representative sampling, testing, and regular review.
Now and then
Although technology leaders have called for a pause in developing powerful generative AI models whilst potential threats are explored, the power of innovation available from utilising AI is available today and should be embraced by the UK housing sector.
FLS utilises AI to design the best result in line with unique circumstances. To focus and produce the fastest, most cost-effective and sustainable solution, typically achieving results in a split second.
Social landlords do not have to wait 45 years for AI to catch up. Field force scheduling teams balance and optimise their operations, completing as many repairs and maintenance jobs, surveys, and welfare checks as possible with the highest quality.
With an AI-powered scheduling and routing solution, more appointments are enabled and completed, benefiting both tenants and operatives.
Main image: Lee Hawkes is housing sector lead at FLS – Fast Lean Smart
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