HR Metrics Database
Presentation to WIG
HR Metrics Database
• Background
• Progress Report
• Examples
• Next Steps
Background
• HR Metrics Report
• How can we collect the data more efficiently?
• How can we make more use of the data?
• Explore the possibility of of creating a basic HR datamart
• Waltham Forest & Haringey volunteered to provide data and expertise
Progress Report
• Visits to sunny Waltham Forest & Haringey over the summer & collected sets of data
• Defined file layouts and built data transformation scripts
• Data loaded into Access – one row per person per period
• Standard formulas applied • Transformed into OLAP cube using Cognos
Transformer
Examples
• Unable to set-up live demo
• Slides produced using data provided by Leon & Tessa
• Cognos Powerplay used as reporting layer
• Still some issues with the data and work still to be done on adding to the dimensions and measures
Measures & Dimensions
• 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
0.00%
4.00%
8.00%
12.00%
16.00%
20.00%
24.00%
28.00%
Below 10K10K to 15K
15K to 20K20K to 25K
25K to 30K30K to 35K
35K to 40K40K to 45K
45K to 50K50K to 60K
60K to 70K70K to 80K
80K to 90K90K to 100K
Over100K2008/Jul
HeadcountLegend
All Boroughs
Waltham ForestHaringeyMerton
Next Steps
• Firm up the process• Add Absence reasons, top 5% flag and
occupational groups• More checking & testing • Document process • Collect data from more boroughs• Look at options for software
The Challenge… (a personal view)
• Management Information will be the lifeblood of workforce planning
• We need to see the possibilities of what it can provide. Spend more time using the data than designing reports.
• We need to be aiming to make the information more accessible for line managers – this means simpler and more standardisation
Any Questions?
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