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Case Study: Vertex


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Vertex is a business process outsourcing (BPO) company, with particular expertise in customer management outsourcing (CMO). Core skill is managing end-to-end customer service operations on behalf of our clients - covers all front and back office activities.

Vertex is the UK´s leading CRM outsourcing company with £350M turnover, manage over 34 million customer accounts, handle over 210m customer contacts, print and send over 65 million bills and documents, process 97 million customer transactions and collect £6 billion on behalf of our clients. Vertex is in 28 UK sites, 3 in Canada and 1 in India.


WITNESS simulation in Vertex was introduced in September 2002 and models built so far

  • 5 call centres
  • Scan, index and process Housing Benefit claims
  • Printing and enveloping machines
  • Conversion strategy customer flows


The background of the Case Study

A contact centre for Utility client with 7 different call types by homeworkers with a second site support for one call type and some dual-skilling of agents, ringfenced inbound calls and document handling.
 

The Issues Faced were:

  • Service Level below target
  • Abandon rate above target
  • Two calls types ringfenced (stand alone areas)
  • Shifts optimised within constraints
  • Cost constraints

The potential Solutions contemplated were:

  • Extra staff with multi-skill agents.
  • Overflow into document handling.
  • Blend with ringfenced call types with a network skill sets for homeworkers.
  • Second site.


WITNESS simulation was used due to the complexities that cannot be modelled using Erlang and Excel (multi-skilling, blending and overflows) and the need of forecast of performance required and the comparison scenarios.

The simulation allows the comparison of scenarios with extra staff, multi- skilling benefit, overflow rules, blending rules and staffing, call duration, call volumes, and network skill sets.

The conclusions of the Case Study were:
to use a combination of extra staff and multi-skilling, only overflow with 30 agents available, strive to reduce duration and volume and limited benefit in investment in network skill sets.



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