Akeso were engaged by a National Genomics Service to help understand demand and workforce requirements over a 10 year timeframe through the development of a Strategic Planning Model that forecast demand and capacity requirements, net of likely improvements in productivity & tech / AI.
Insight
A workforce demand and capacity model was developed for the NGS team, designed to support ‘what-if’ analysis and building the evidence base for future changes. Various demand and capacity scenarios across a 10 year horizon can be modelled reflecting potential changes to operating model. Importantly, adjustable workforce efficiency levers were built into the model for each service unit and workforce group allowing staff efficiency to be changed in-line with various efficiency opportunities identified during the current-state assessment.
Action
Recognising emerging operating models, the current state assessment aligned to the three pillars of the NHS Long-Term Workforce Plan: Train, Retain, Reform. To further facilitate decision-making and adoption of workforce improvements and efficiencies a quantitative opportunity assessment was conducted generating an opportunity prioritisation matrix based on assessment of impact on people, organisation, quality of service and future proofing, as well as implementation time, resource investment, non-pay costs and barriers to success.
We conducted an in-depth current state assessment with 55 interview sessions, an information request, and led a forum with over 150 stakeholders in attendance. The current state provided a comprehensive understanding of current workforce challenges across the service, as well short, medium, and long-term improvement opportunities and efficiency incentives.
Managing staff across the service were thoroughly trained on the functionality of the workforce model prior to handover.
Results
We have successfully deployed this approach with clients, delivering transformation within budget, such as in our Workforce Profiling for the NGS. Here, we were asked to design a future state model based on predicted demand and capacity across 24 laboratories and 17 clinical service lines.