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Capital Intelligence HR Metrics Database

Capital Intelligence HR Metrics Database. Presentation to Heads of HR March 2008. HR Metrics Database. What are we trying to achieve? Background to the project Progress to date Examples . Objectives . Collect data across London Boroughs more efficiently and effectively

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Capital Intelligence HR Metrics Database

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  1. Capital Intelligence HR Metrics Database Presentation to Heads of HR March 2008

  2. HR Metrics Database • What are we trying to achieve? • Background to the project • Progress to date • Examples

  3. Objectives • Collect data across London Boroughs more efficiently and effectively • More emphasis on using the data than generating reports • Benchmarking tool with ability to drilldown into detail • Longer term – Produce standard London workforce scorecard

  4. Background • Workforce Information Group project to look at standard KPI’s and definitions • Information is still “top level” • Does not support workforce planning • Unable to “drill down” or benchmark • Still reliant on informal networking, surveys and e-mails to other councils

  5. Progress so far • First pilot database with Merton, Waltham Forest & Haringey data last year • Defined file layouts and built data transformation scripts • Data loaded into single database – one row per person per period • Standard formulas applied • Transformed into a data warehouse using Merton’s software (Cognos Transformer)

  6. Progress so far (2) • Further work via Workforce Intelligence group to revise layouts & documentation • Agreed two additional partner boroughs • Current line-up – Sutton, Haringey, Waltham Forest, RBKC, RBK & Merton

  7. Dimensions Time Organisation Gender Ethnicity Age Band Length of Service Salary Band Employee Group Measures FTE / Headcount Gross Pay (Total / Avg.) Average Age Sick Days Sickness Cost Sick Days per FTE Turnover Rate Starter / Leaver Count Measures & Dimensions

  8. Standard Reports – Age Profile

  9. Age Profile – Employees with Disabilities

  10. Age Profile – Social Workers

  11. Analysis over time - Turnover

  12. Analysis over time - Absence

  13. Using Multiple Dimensions

  14. Worked Example – Absence Cost by Age Band

  15. The Challenge… • Management Information should be the “lifeblood” of workforce planning • Make better use of current investment • Raising the profile of HR – Talk the same language, use the same tools as Finance • We need to be aiming to make the information more accessible for line managers

  16. Any Questions?

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