In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector. In the final part of this series on AI our panellists, FieldAware's Mark Tatarsky and ServiceMax's Amit Jain, discuss if the technology compliments a wider strategy or can it operate in a silo.

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector. In the third of a four part series on AI our panellists, FieldAware's Mark Tatarsky and ServiceMax's Amit Jain, discuss the benefits the technology can bring to a business.

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector. In the second of a four part series on AI our panellists, FieldAware's Mark Tatarsky and ServiceMax's Amit Jain, define the difference between Artificial Intelligence and Machine Learning.

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector. In the first of a four part series, we turn our attention to AI where our panel includes FieldAware's Mark Tatarsky and ServiceMax's Amit Jain.

 

Just how important is ArtificIal intelligence going to be in the future of field service?

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Mark Tatarsky, SVP Marketing, FieldAware

Artificial Intelligence (AI) is already working its way into many different aspects of field service delivery today.

However, its prevalence and impact will be more influential for some field service organizations than others. It really depends on the industry served; the type of service provided as well as the complexity of the equipment serviced. AI can impact all field service delivery to varying levels.

In many instances, AI can be applied behind the scenes to improve efficiency without the end-user, even knowing it is at work.

An example of behind the scenes activity is when AI improves the optimization engine results for scheduling and routing. Even basic consumer-oriented routing systems like WAZE or GoogleMaps use varying levels of AI to help select the most efficient route.

When field service organizations are servicing sophisticated equipment monitored via IoT connectivity, AI will be applied to the monitoring and deployment process to enable predictive maintenance and automated dispatch based on AI processes and equipment tolerance thresholds.

 

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Amit Jain, Senior VP of Product, ServiceMax. 

Artificial Intelligence is going to play a significant role in many areas that are crucial to field service delivery today and moving forward—it is early stages now.  Much of the conversation in field service now is centred on two key aspects - how we drive efficiency and how we establish the 360-degree view of the customer. In each of these areas, data is an essential factor in terms of driving improvements - and having a view into asset service data is equally important.

Connected asset and service data as maintained in the field hold insights far beyond the service department, providing a better business lens for almost every other line of business. Within field service operations, a major component of any day-to-day business is the data that is used in the variety of operational processes. Field service engineers, dispatchers and managers rely on and collect valuable data direct from source and ensure its accuracy, whether that’s product status and performance, contracts, location or account details.

With the advent of predictive analytics and condition-based maintenance, this data, which can be curated and fed into an organization’s data system has the potential to provide accurate intelligence across the organization. As it gravitates towards the data lake, it can touch and enhance other data sources such as CRM, ERP, parts, logistics and supply chain, HR, compliance and even data sources such as traffic and weather forecasting. Essentially, field service and asset data gives all other data relevance and accuracy.

However, the sheer unprecedented volumes of data being generated today, which is set to continue to increase almost exponentially moving forwards, is simply too vast to be useful unless we implement Artificial Intelligence within FSM systems. This is also the case with interpreting IoT data, which is largely predicted to be the backbone of field service operations of the future, and is empowering field service organizations to move away from the traditional break/fix approach to much more effective and profitable advanced service models.

The second part of this Big Discussion will be published next week, when the pair are asked the difference between Artificial Intelligence and Machine Learning.

In the second part of this series on rugged hardware, our panellists Varlink's Mike Pullon and Janam's Robert Hurt, discuss the role the technology plays in retaining and attracting new talent to the sector. They also ponder the right time for a firm to consider replacing their current mobile hardware solution.

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector. In the first of a two part series, we turn our attention to rugged hardware where our panel includes Varlink's Mike Pullon and Janam's Robert Hurt...

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector.
In the final part of our series on dynamic scheduling our panellists, FieldAware's Mark Tatarsky and Fast Lean Smart's Chris Welsh are asked if SMEs can also benefit from optimised scheduling.

Can smaller and medium sized organisations benefit from optimised scheduling, or is it only beneficial for enterprise-level field service providers?

Marc Tatarsky, SVP Marketing, FieldAware
Advances in cloud computing, multi-tenant SaaS solutions, and new micro and macro optimised scheduling capabilities enable optimised scheduling to scale down. Optimization is now an effective solution for organizations of all sizes.

Micro optimisation enables service delivery firms to build a library of business policies that can be used to tune the optimiser to create a work schedule for an individual team or region. The business policy contains the rules that ensure competing business objectives are balanced appropriately. The rules ensure the right field technicians are considered for the work while managing business objectives such as limiting travel time, delivering priority work, or balancing the number of jobs across the team. 

The business policy library can cover how the team should work in various business scenarios. These can include an emergency schedule; prioritising installations at the end of the reporting period to assist in achieving revenue targets; during seasonal changes, etc.

Running the service delivery business is easier when you select the business policies you want to apply to different teams and then change them as needed to reflect the changes in their business. The benefits of accelerating time to value and reducing the cost and complexity of maintenance that a micro optimised schedule provides small and medium sized organisations equally apply to the enterprise.


Chris Welsh, Director, FLS – FAST LEAN SMART
Yes, most definitely, optimised scheduling will help even small service operations that are performing multiple jobs per day to be more efficient and deliver reliable customer service – essential in an ever more competitive industry where customer expectations are rising.

Even with a handful of engineers, there are thousands or millions of possible permutations for job assignment and most providers will resort to allocating work according to postcode patches. This makes it easy to allocate jobs but the ‘hard borders’ between resources can be the greatest inefficiency for field service delivery and you might turn down an appointment request that was actually achievable and cost effective. 

An optimised schedule considers all resources and travel time without these hard borders and, in my experience of performing scheduling tests, an optimised schedule compared to a manual schedule will typically reveal a 25%-50% reduction in mileage whilst making sure appointments agreed are achievable - that might be 1 to 2 hours saving per day for the engineer to do that extra job.
Perhaps equally important, only engineers with the right skills and parts turn up and engineers get home on time! This contributes to greater employee engagement and to the success of the company.

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector.
In the third of a four part series on dynamic scheduling our panellists, FieldAware's Mark Tatarsky and Fast Lean Smart's Chris Welsh identify the biggest mistakes companies make when implementing a scheduling system.

What is the biggest mistake field service companies make when implementing scheduling solutions?

Marc Tatarsky, SVP Marketing, FieldAware
Companies often expect a ‘silver bullet.’ They aren’t prepared for the challenges that come with a successful implementation. One problem is capturing the implicit decision-making processes used by dispatchers today. Another is looking at how those processes can be enhanced to take advantage of new optimisation capabilities.

These tasks can seem daunting but are essential to define the rules and objectives of the optimisation engine and give valuable results. However, by phasing the implementation initially with manual or semi-automated scheduling, service organizations can achieve faster adoption while simultaneously creating a positive environment.

The company can define what it wants to accomplish by implementing schedule optimization so that it can give appropriate weighting to seeminglyconflicting objectives. FSM vendors have a parallel role to play here. To minimize friction during adoption, vendors should create intuitive workflows.

These workflows include setting up rules, objectives, working time, etc. Vendors can also help instil confidence in the solution by providing feedback and visualisation of optimization results. These metrics allow dispatchers to compare manual and optimized schedules.

Chris Welsh, Director, FLS – FAST LEAN SMART
The biggest mistake is not managing the ‘rate of change’. A company decides it’s objectives for performance improvement, chooses a new technology to enable automation and new processes. However, it is important to understand and manage the perception, challenges and priorities of all the stakeholders: the customer, the management team, the back office and the field force.

Introducing a scheduling solution is best considered as a journey with continuous improvement, ensuring the entire service team are engaged and ‘bought in’ along the way and change taken in steps that the business can consume. It is also important to have a system with transparent visibility of how scheduling decisions were made so users will understand and have confidence in the results.

With system design, focus on the fundamentals with a pilot area to begin with and then listen and learn from feedback. At FLS we offer this stage ‘precontract’ so there is no doubt in the technology, the business case, and what is required for deployment.

Next you refine/improve based on these learnings, show you take feedback onboard, and expand the use. Sometimes company improvements are not obvious for individuals who only see their own workload. Measuring and reporting overall statistics is therefore important not only for ROI calculation but also for positivity across the service team.

The final part of the big discussion will be published next week, when the panel are asked if SMEs can also benefit from optimised scheduling. You can read the first part of the discussion here and the second part here. 

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector.
In the second of a four part series on dynamic scheduling our panellists, FieldAware's Mark Tatarsky and Fast Lean Smart's Chris Welsh, ponder if optimised scheduling should be an accepted part of a wider FSM platform.

Should optimised scheduling still be considered as a best-of-breed solution or should it now be an expectation of wider FSM platforms?

Marc Tatarsky, SVP Marketing, FieldAware
The most significant expense for a service organisation is the cost of its field resources. In a hyper-competitive market where service delivery is a crucial differentiator, service organisations must excel at customer service delivery whilst sustaining high levels of operational productivity.

Given these increased pressures, an optimised scheduler is a core feature of any world-class FSM platform. Ensuring work schedules are compliant, deliver the intended service to the end customer, and are operationally efficient is essential.

Traditionally, providing this depth of capability was cost-prohibitive for an FSM platform. Implementation projects were either too lengthy or too complex to configure an optimizer efficiently.

Modern, micro optimisation capabilities enable service delivery companies to quickly and cost-effectively implement optimised scheduling at a team level. Moreover, for those workflows needing a manual or semi-automated scheduling, advanced FSM tools also provide options such as Planning Mode.

This capability allows schedules to be built and adjusted in a safe environment either manually or through interactive optimisation cycles. When the Planner or Dispatcher is satisfied with the scheduling outcomes, they can publish and dispatch the approved schedule to the field technician’s mobiles following the team’s dispatch policy. 

Chris Welsh, Director, FLS – FAST LEAN SMART
Making do with scheduling included in an FSM platform might seem logical, however the benefit can be so great that best-of-breed is the way to go. Not only does schedule optimisation minimise cost, it also helps ensure you can deliver on the increasing service expectations of your customers.

In 2019, I believe it reasonable to set the minimum bar at the following capabilities to describe field service scheduling as ‘optimised’: 
1. Dynamic schedule optimisation to incorporate all engineers and jobs over a substantial radius, not just assigning work to an engineer because it’s their patch or have a space to fill in the diary;
2. Route calculation with actual average driving speeds for each road segment according to the time of day.

FLS are one of the few companies with this expertise, honing our solutions for over 25 years to provide the fastest, leanest and smartest configurable algorithms that can be integrated easily into any established FSM solution or new project.

Our customers are using most of the leading FSM/CRM/ERP technologies and FLS are happy to prove the benefit free of charge, starting with a scheduling test to compare how FLS VISITOUR would have scheduled your work - expect to be amazed at the unlocked potential!

The third part of the big discussion will be published next week, when the panel diagnose the biggest mistakes companies make when implementing a scheduling system. You can read the first part of the discussion here.