Business Analytics in Support of an Effective KPI Program: The Importance of Data Analytics

From the results of the Strategies For GrowthSM (SFGSM) Field Service Management Benchmark Survey, updated in 2015, more than one-half (52%) of respondents cite that developing and/or improving the metrics, or KPIs, they use to measure field service performance is the top strategic action currently being taken with respect to optimising their organisation’s overall service delivery performance.

However, for Best Practices Field Services Organisations (FSOs) (i.e., services organisations that are already attaining levels of customer satisfaction at 90% or higher, and services profitability of 30% or greater) this figure increases to 61%. The percentage jumps even higher, to 64%, for UK/Europe-based services organisations; that’s right – more UK/Europe-based respondents cite their respective KPI programs as the top strategic action they are currently taking – moreso than the survey’s top-of-the-line Best Practices survey segment!

So, why is the establishment of a services KPI program so important? Mainly due to the targeted applications that most of these organisations have for using the collected, analyzed, measured and distributed data – basically for the following top reasons:

  • To improve field service
  • To make product design changes/improvements
  • To make manufacturing changes/improvements
  • To make changes to product documentation
  • To make purchasing decisions

Nearly as many respondents in the UK/Europe (i.e., 48%) also cite the use of a business intelligence/analytics solution as one of the top technology applications currently used to support their services operations – and another 39% cite knowledge management as a top-used application. However, few of them actually refer to these programs as “big data” – just, simply, business analytics!

What this proves is that, for most FSOs, data collection, analysis, measurement and sharing is not conducted merely for the sake of doing so – but, rather to:

  • Build, maintain and apply these data to a formal services KPI program
  • Distribute/share the collected and analysed data with the appropriate departments and individuals within the organisation
  • Establish and maintain an enterprise-wide knowledgebase from which all facets of services operations can benefit from – and build upon
  • Share the database/knowledgebase with all components of the enterprise (i.e., manufacturing/production, warranty management, forward and reverse logistics, etc. – rather than simply “holding the data hostage” within the FSM or Service Lifecycle Management (SLM) areas of the business
  • Use the data, and resultant database, knowledgebase (or, for the largest of organisations, data lake) to foster a more collaborative relationship between and among the key departments/divisions that ultimately have an impact on supporting the customer

But how big does your data really need to be in order to support each of these functions? The required size of the database, or knowledgebase, will depend largely on the size of the organisation, the volume of field service activity conducted on a regular basis, and other key measures of throughput that characterize the overall “size” of the organisation and its requisite data analytics needs. Similar types of organisations, with similar characteristics, but with order-of-magnitude differences in one or more key throughput factors may find themselves with totally different needs for data; big, small or otherwise.

The one thing to remember is that all services organisations need a minimum of data to support their respective operations. Call it what you will, but they will still need the analytical support contributed by a formal Key Performance Indicator (KPI), or metrics, program; the structure of a formal service call data activity repository; a Customer Relationship Management (CRM) database; accessibility to a centralized database, or knowledge bank to support management decision making; and all of the performance metrics and measurements required to evaluate and assess the organisation’s performance over time.

An effective business analytics program is what most organisations need – not big data, data lakes, or the construction of overly-sophisticated, cumbersome and highly inefficient knowledgebases. It should never be primarily a matter of how much data needs to be collected; but, rather, the ability to collect enough data to support the organisation’s overall business analytics goals, objectives and targets.

[Our thanks to Astea UK for commissioning this Blog on Data Analytics. For more information, directly from Astea, please visit their Website at www.Astea.com.

You may also wish to visit the Astea UK booth at Copperberg’s 2016 Field Service Summit in Oxford, UK, 12 April, 2016. For more information on the Summit, please visit the conference information Webpage at www.fieldserviceexcellence.co.uk.]

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