720492Demand and Resource Modelling to Predict SLA Performance for Complex Back Office ProcessesClosedGRD Development of PrototypeInnovate UKSoftware to support ‘Back-office Workforce Optimisation’ is a new market. Current solutions provide very limited forecasting, planning and scheduling capabilities. Furthermore, they do not enable an organisation to anticipate, in real-time, how the Service Level Agreements (SLAs) that must be supported by the organisation are threatened, over a wide range of timescales, by variation in the workforce’s performance and fluctuating demand. Enterprise-scale workforce systems are complex and so a new generation of forecasting, planning and scheduling analysis tools is required. The ‘Demand and Resource Modelling to Predict SLA Performance for Complex Back-Office Processes’ project will develop and evaluate a prototype demonstrator of this new generation of analysis tools. The innovation of this project is through the development of new and novel business processing modelling techniques to: a) Provide the real-time SLA Monitoring & Compliance violation detection capability through the comparison of the monitored and the predicted performance; b) Enable an appropriate ‘What If’ scenario prediction capability. This will help managers to design the appropriate forecasts, plans and schedules constrained by the organisation’s SLAs; c) Publish the forecast plans to local operational managers to support the optimal business execution in-line with the forecast. The key benefits that will accrue to the users of the new system are: a) The SLA Compliance monitoring capability will be able to improve quality of service while optimising the workforce activities and associated costs. This is particularly important when remedial planning and scheduling must be established and deployed in real-time; b) The forecasting and scheduling capability will recommend/suggest changes to the planning activity due to the availability of a ‘what if…’ analysis. This will enable an organisation to minimise its vulnerability to unexpected events thereby improving the quality of service delivery.