Although resource planning should be the cornerstone of any services business, organisations are still experiencing missed service level agreements (SLA’s), resulting in unmet customer expectations. A survey, conducted by HBR Analytics, found that executives are not seeing the predictability expected from planning because of the need to prioritise speed. While planning and agility are both equally necessary for business success, frequently changing plans render the hours spent planning fruitless. However, when issues arise, they are often alleviated by decisions that were made days, weeks, or even months ago.
Reap the benefits of consistent resource planning
Organisations that make resource planning a component of their everyday business benefit from tactical workforce decision-making capabilities that have the ability to scale – to meet even the largest organisation’s requirements. To account for every available moment, organisations are implementing planning systems that are powered by artificial intelligence (AI) and machine learning (ML). And when integrated with real-time business operations, resources’ time is completely accounted for and missed customer commitments become a distant memory. Optimised resource planning delivers an array of benefits, including:
- Comply with SLA’s and boost revenues – According to Gartner, by 2022, more than 60 per cent of asset manufacturers will offer outcome-based service contracts. This figure reflects a 15 per cent increase when compared to 2018. Because capacity planning takes into consideration high priority work and necessary resources, services businesses can use it as a competitive differentiator. Since reserved time ensures an organisation’s service team can consistently comply with SLA’s, businesses are in a better position to use SLA’s as a competitive differentiator. (Source: MQ FSM 2019)
- Minimise reactive field service resourcing – According to The Service Council, the most pressing internal challenge service leaders face is a lack of resources to meet service demands. To address this issue in a cost-effective manner, service leaders need full visibility of capacity risks in advance of the planned service. With this knowledge in hand, leaders are better equipped to make smart workforce decisions. Options to maximise workforce utilisation may include relocating resources, adding overtime, or hiring contractors.
- Anticipate and manage fluctuating demands – Also, per the Service Council, 59 per cent of service leaders say increasing the predictability of their business is a top business initiative. Capacity planning allows businesses to account for short-term spikes in demand, including marketing campaigns and seasonality. Increased insight allows organisations to add to or reduce their workforce accordingly — while maintaining balanced utilisation of resources with the right skills for the type of work that is anticipated.
Optimise resource capacity planning with technology
The ultimate measurement for any customer-centric business is the performance provided on the day of service. While reaching perfect service every time is a goal worth striving for, the reality is that perfection is not always achievable. Instead, a more achievable and realistic goal is for businesses to simultaneously increase revenue and reduce costs. This can be accomplished by ensuring that there are always enough resources available to perform revenue generating work, while not violating customer commitments or SLA’s. Meeting these rigorous customer demands requires technology that is geared towards helping businesses achieve successful capacity planning.
AI and ML are powerful technology tools that can help planners identify areas at risk and allocate resources to ensure all work is completed in accordance to SLA’s. In the event of a capacity shortage, planners can take strategic thinking to the next level to determine the best recourse such as relocating resources from another district, hiring contractors, or relaxing overtime rules until commitments are met.
To keep customers satisfied, a business’s mobile workforce must be kept engaged. And this means a reduction in idle time so they can complete as many jobs as possible that are well-suited to their individual skill sets. Many service planning processes are highly manual and involve multiple spreadsheets, as well as a bit of guesswork. When AI is introduced into the capacity planning mix, it seamlessly accounts for historical demand data, scheduled and unscheduled work, and available resources. This ensures all business priorities are enforced across the entire service lifecycle. Businesses also need to take into consideration schedule disruptions, for example when a technician calls in sick. Instead of missing customer commitments, AI-driven technology alerts the service organisation of the risk so that action can be taken to reprioritise the work. Similarly, when scheduling work that is tied to an SLA, planners have visibility into whether the next available time for an appointment is within the SLA window.
In the service industry, capacity planning helps ensure that there are enough available field resources to manage both scheduled and unscheduled work on any given day. When too many resources are scheduled, the result is idle resource time. Schedule too few and missed SLA’s are bound to happen, emergency work will not be able to be handled, and customer satisfaction will be put at risk.
To achieve resource capacity optimisation, it’s more important than ever for businesses to embrace technology such as AI and ML. In doing so, they will be able to more accurately forecast workload demand and allocate the right resources at the right time and in the right place. As service leaders have shown, achieving alignment and optimising key performance indicators (KPI’s) by planning ahead is critical for delivering exceptional service and growing the business.
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