The metrics that matter

Transcription

1 WHITE PAPER The metrics that matter How actionable analytics can transform field service management performance. www.

2 Introduction The top strategic action for two-thirds of service organisations is to develop or improve the metrics or KPIs used to measure field service performance 1. And yet only 18 percent of companies believe they have the skills necessary to gather and use insights effectively 2. These two statistics represent the predicament of many field service organisations today - they know actionable analytics are vital for business success, but fully utilising the information they gather is a daunting and difficult task. This white paper aims to disentangle the vast quantity of data available in the field service management industry by highlighting the metrics that really matter and demonstrating how analytics can be used to improve business performance. Customer centric servitisation Many organisations have data at their fingertips but are paralysed by the complexity and number of data sources available to them. They rely on anecdotal evidence or intuition to make decisions rather than informed business intelligence in order to drive competitive advantage. Research shows that service organisations that fully interrogate data outperform their rivals. A like-for-like comparison between organisations which use advanced analytics and those that don t, reveals that adopters of analytics are seeing a 60% higher increase in year-on-year revenue 3. Increasingly businesses are adopting analytics to gain deeper insight into operational performance and customer behaviour to improve overall customer experience. In some cases, customers have begun to expect this from every service provider they encounter, in both their private and working lives. Adding to this motivation is the concept of servitisation. Many organisations are recognising service as a key revenue stream and some are servicing products manufactured by competitors to increase revenue, build customer loyalty and improve customer experience. With this customer centric approach and the revenue opportunities servitisation presents, comes the requirement to really understand the customer, the service they experience and to continually seek to improve service delivery and associated processes. It s time to learn from the early adopters of analytics and embark on a new era of data interrogation - one that facilitates the evolution of a predictive and proactive service model. But how do you go about turning the ever growing volume of data into useful intelligence that drives change and innovation? 2

3 Analytics for Field Service Management (FSM) Analytics for FSM should be based around assets in the field, the resources (time, money and people) it takes to install, maintain and repair those assets and the customer experience. Initially an organisation may just want to understand the numbers around these key activities, then in time improve processes. Ultimately the goal should be to deliver forecast and predictive analytics that achieve optimisation across service delivery. For field service this goal can be delivered at both strategic and operational levels, for example a director might want to understand how a shift in approach can create gains for the organisation, whereas a manager might want to understand how exactly that shift can be made. In FSM there is a current trend towards investing in planned preventative maintenance to deliver greater efficiency and lower costs. With the use of analytics and modelling, the ultimate goal is to achieve predictive maintenance. Through predictive maintenance, organisations can shorten the time from failure detection to intervention and maximise the ability to detect true events and minimise false alerts. This kind of predictive analysis becomes extremely powerful when coupled with big data sources - like machine sensors - which can constantly measure and record data. This rich source of information can then be used to create a deep understanding of performance by component over a timeframe. An organisation would then be able to evaluate whether a reactive, planned or predictive approach would be the most effective for them. Effectiveness or success could be defined by cost /customer satisfaction or another measure which may vary from organisation to organisation, depending on their service model. Incorporate the metrics that matter To ensure analytics are able to deliver valuable insight, the right KPIs must be identified. Every service organisation must identify their own metrics based on what success looks like for them. There are however some common measures in the service industry which should be tracked by any service organisation regardless of which sector they operate within. Organisations that leverage advanced analytics and big data are able to decrease operating costs year-over-year by twice as much as those not using analytics 4. 3

4 KPIs (Key Performance Indicators) for field service management should include the following: 1 Business process Optimised business processes are at the heart of service delivery and therefore form the backbone of efficient (field) service management. Business processes should be continually assessed with the goal of reducing the number of steps in any process which in turn minimises the opportunity for delays and bottlenecks. The main unit of measure for process is time: time to complete the process, various steps in the process and delays in the process. 2 Service delivery Often tied to Service Level Agreements (SLAs) - whether providing a service to an external or internal client. SLAs are one part of the service story; if set correctly they will reflect the most important (client) metrics but may not show the whole picture (cost). Organisations must therefore ensure they also match service metrics against cost to ensure this critical factor is considered. Exemplary customer service is something to aim for but not at any financial cost. It is also critical to capture time-to-resolution and downtime. 3 Customer service The KPIs for customer service are closely related to service delivery KPIs and some measures may in fact feed into both. Unlike service delivery, customer service is viewed from the customer perspective and is around the handling of customer communication (regardless of the channel), the severity and quantity of complaints, and customer satisfaction scores and feedback. Combined, these factors can give a deep understanding of how your customer service is perceived and enjoyed by your customers. 4 Efficiency The efficiency measure offers a broader snapshot of your service operations, comprising several factors from the measures already outlined together with some additional measures to present an overview. The factors chosen will vary from organisation to organisation as efficiency is as subjective as KPIs. Ultimately it will come down to how a company defines its success. A measure that should be consistently captured however is around process delays - which should always be minimised - so the number of times an alert is raised, the number of reminders and the number of staff involved in a particular process. This is by no means an exhaustive list - each metric should unlock more in-depth measures which require analysis. Clear actionable insights will be revealed as part of the analysis from which the organisation can take evidence based decisions and improve the process associated with that measure. This should be a constant cyclical review process. 4

5 The analytics journey Assuming a set of KPIs has been defined, there is a hierarchy of analytics that can be applied, dependent upon the richness of the data and the analytics resource available. The advanced analytics journey demonstrated in chart 1 articulates a staged approach which starts by examining the data and finishes by optimising the intelligence which has been discovered. Evidently each step in the journey becomes more complicated and arguably more useful as the capability and complexity of the analytics increases. Chart 1: The advanced analytics journey 5» What if these trends continue? What s the best that can happen? What will happen next? Predictive modelling Optimisation Forecasts Standard reports Ad hoc reports Query drill down What happened? Alerts Statistical analysis Why is this happening? What actions are needed? Where exactly is the problem? How many, how often, where? Degree of intelligence Standard reports The first step is to look at the past. What has already happened? For example an organisation may wish to know how many maintenance visits have been completed in a particular period. 1 2 Ad hoc reports Once data has been gathered from the standard reports, secondary questions may surface such as, do visits vary depending on geographical location? 5

6 3 Query drill down This stage digs deeper to discover if there are any problems emerging from the findings of the previous stages. Is there a significant difference between cost per visit in two different geographic locations? Does the first time fix rate fluctuate depending on the type of visit? 4 Alerts Based on key learnings from the previous three levels, stage 4 sets alerts when a KPI or SLA is at risk of being missed. For example, when a visit is about to be scheduled outside an agreed client SLA. 5 Statistical analysis Going beyond the what and where, this stage attempts to understand the why. Using statistical models, organisations can identify, prevent and take control of situations, which can then guide decisionmaking. For example, which service areas generate the most revenue? 6 Forecasting Stepping away from retrospective insight, this stage uses prospective quantitative forecasting. Using historical data and past trends, patterns can be identified to create future forecasts of overall behaviour. As an example, forecasting could be used for workforce planning - such as designating geographical areas and planning recruitment and training. 7 Predictive modelling This takes the forecasting concept one step further by expanding beyond timerelated forecasts. Predictive modelling looks at measurements of many records at a single point of time and uses those to generate predictions for new records. An organisation could model an increase in customer satisfaction if investments were made in certain service areas, for example. 8 Optimisation The final stage combines the insight gained from all previous steps to optimise business processes or objectives, given operational and other constraints. Optimisation answers questions such as how to optimally allocate resources subject to a set of priorities. The best performing companies are 61 % more likely to give field technicians access to personal dashboards which reflect their performance 6. 6

7 Additional benefits of analytics Increased customer retention Research by Aberdeen Group shows organisations that embrace analytics outperform their industry average figures for customer satisfaction, customer retention and service improvement. These organisations use analytics to gain a deep understanding of customer behaviour to preempt customer needs and desires without explicit interaction. Higher levels of motivation in the workforce The mobile workforce is the shop window of any service organisation. In fact some organisations are even combining the role of technician and salesperson. The technician is highly qualified in product knowledge and often in the customer space; this puts them in a unique position of knowledge and trust to be able to sell to the customer. The most forward thinking organisations are aligning their KPIs with those of their employees, giving accountability and recognition to those who deliver business success. Analytics can play a key part in this alignment by providing transparency and real time measurement to employee and employer. Organisations are even gamifying these analytics through the use of data visualisation to further motivate their employees to perform. Improved bottom line Organisations which reap the greatest rewards from business intelligence see a significantly improved bottom line. Competitive advantage By continuously analysing in-house performance figures these companies can use this insight to monitor their competitors and ensure they stay at the top of their game. The best performing service organisations are twice as likely as all others to consistently benchmark service performance against peers and top performers in other industries 8. Compared to organisations that are yet to unlock the potential of data, adopters of analytics see double the improvement in operating cash flow and twice the reduction in operating costs year-on-year 7. 7

8 Conclusion It is important to emphasise that the integration of advanced analytics requires a change in mindset from all stakeholders, but its success is dependent on leadership. To achieve the greatest business benefit, outcomes and insights need to be acted on. These actions can result in changes in organisational processes and key performance indicators (KPIs), so a sound strategy needs to be in place and understood by the entire leadership team before advanced analytics are deployed. Through actionable analytics organisations are able to shift from an intuitive decision making process to one which is driven by data. Ambiguity is removed and insight can confidently be used to transform business operations with improved efficiency, reduced costs, increased profitability and improved customer and employee engagement. Analytics give an organisation the tools to anticipate and plan for change while accurately managing and balancing risk. It must be remembered that the use of advanced analytics is a journey of continual improvement. An organisation must consistently, continually and constantly capture and analyse their data to create actionable business insight. This insight can then be used to drive decisions - but the outcome of those decisions must of course be measured thus creating a circle of continual improvement. Sources 1 Strategies for Growth 2014 Field Service Management Benchmark Survey 2 McKinsey Getting Started with Business Analytics, Insightful Decision-Making by David Roi Hardoon and Galit Shmueli

9 About Oneserve Analytics Oneserve Analytics is part of our new generation, cloud based, mobile enabled, field service management solution providing deeper data analysis and reporting across your service management activities. Configurable, interactive dashboards can be created to represent any measure of your choice, allowing you to explore trends, patterns and anomalies in data and identify ways to improve your business performance. Standard and custom reports provide greater visibility of your operations and empower you to make better business decisions. For more information or to request a free demo with a member of our team call us on or visit our website www. T: E: hello@ W: www. Oneserve Unit 4, Silverdown Office Park Fair Oak Close, Exeter EX5 2UX 9