1. Demand Forecasting & Demand Management Stephen Simpkin Zenith McIntyre-Allen Organisational Intelligence 30 th January LARIA East meeting

2. Essex County Council’s strategy for Transformation: “Commissioning outcomes based on evidence, in order to protect the most vulnerable, enable the economy to grow and promote quality of life for Essex residents.” ~ Joanna Killian, Chief Executive Organisational Intelligence

3. Why? We believe that there will be increased demand for many of our services We know that with our current approach we cannot afford to continue to fund services at the same level We need the evidence to determine how we prioritise our spending We will have a consistent approach to visualising the future in Essex Organisational Intelligence

4. 4 Demand Forecasting Population now Future population Translate into service take-up Consider demographic, policy and technological changes Demand Management Target Preventative Services Target Early Interventions What works / Best Practice Design innovative interventions Redirecting / Saying no Predicting Future Demand & Potential Stressors in Provision Plans to mitigate demand AnalysePlan

5. Conventional Wisdom Gather clear robust evidence that backs-up (or dispels) myths or ‘what we think we know’. Organisational Intelligence 420,00 babies will be born International migration will account for 6% of population growth compares to internal UK migration, 72% Population will grow by 20% Number of over 85s will grow by 175% Working age population will grow by 5% compared to 40% growth among non-working age 2m people will migrate to Essex Over the next 25 years in Essex… Uttlesford to grow at the fastest rate, 32% Over 65s to account for 1/3 of the population

6. Adult Social Care forecasts Demand Forecasting application Organisational Intelligence

7. Adult Social Care – Conventional Wisdom “Older people population is growing – our services will not be able to cope with the anticipated increase!” Organisational Intelligence

8. Adult Social Care – Conventional Wisdom AIM: Gather clear robust evidence that backs-up (or dispels) myths or ‘what we think we know’ Organisational Intelligence

9. Reasons for revising forecasts Committed to ongoing refresh of forecasts (due to changing environment, health needs, policies, etc) As more data (and research) becomes available we can continually fine-tune forecasts Attempt a consistent approach to demand forecasting Confidence in forecasted growth rates Start from the most informed position possible Organisational Intelligence

10. Methodology Historically demand forecasting models are either ‘Prevalence’ based or ‘Trend’ based We created a composite model for 4 cohort of Adult Social Care service use (Older People, Mental Health, Learning Disability and Physical and Sensory Impairment) Population baseline > Projections > Turning projections into needs groups > Turning needs groups into service use > Informing MTRS and other demand management activities Organisational Intelligence

11. Impact Revised forecasts broadly reflective of previous forecasts Able to identify key growth areas/cohorts Clear and consistent methodology used (which can be easily updated) Using revised methodology we determined that we were previously potentially overestimating the growth of TWO Adult Social Care cohorts Adopting revised forecasts into budget tool reduced forecasted spend Organisational Intelligence

13. Crossover with Demand Management Once future service demand is estimated, there may be scope to attempt to mitigate this demand. Demand management may be possible through: Changes to existing initiatives (such as targeting preventative services to the cohorts/geographies that will benefit most); Early intervention identification (using information available to us to implement interventions before it is too late); Best practice learning (what is working elsewhere and can this be replicated), or; Design of innovative interventions. Organisational Intelligence

14. Next steps Applying this approach to other areas of Essex County Council activity, e.g. forecasting pupil numbers, aspects of health/social care integration, place issues such as housing, etc. Potential areas for Demand Forecasting/Management: Organisational Intelligence