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Diversity Analysis in the Department for Transport In House Analytical Consultancy Support HR through Analysis Equality Monitoring Performance Management.

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Presentation on theme: "Diversity Analysis in the Department for Transport In House Analytical Consultancy Support HR through Analysis Equality Monitoring Performance Management."— Presentation transcript:

1 Diversity Analysis in the Department for Transport In House Analytical Consultancy Support HR through Analysis Equality Monitoring Performance Management in DfT(C) Equal Pay DfT(C) Reorganisation in DfT(C) Resource simulation modelling DfT(C) Pulse Survey

2 In House Analytical Consultancy Government Operational Research Service IHAC – 10 staff (9.7 FTE) Split site – London/Hastings Skills: –Problem Solving/Analysis –Spreadsheets/Databases/GIS Analytical Support for DfT(C) and its Agencies –DSA, VOSA, MCA and DVLA

3 Overall Approach "I could have done it in a much more complicated way, said the Red Queen Lewis Carroll Everything should be as simple as it can be, but not simpler Albert Einstein? Louis Zukofsky? Roger Sessions? William of Ockham? Anonymous?

4 Overall Approach Staff have multiple characteristics Avoid analysing one characteristic at a time (i.e. multiple univariate testing) –male/female –white/BME –non-disabled/disabled Multivariate analysis of staff characteristics One record per person – analyse then summarise! Data is encoded Mix of binary, real, integer and class variables E.g.1,56,1,7,1,3,17,0,1.0,(1,0,0),(1,0,0),(0,1,0),(1,0,0),0,2

5 Staff Data – what do we know? …as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns - the ones we don't know we don't know. Donald Rumsfeld – February 2002

6 The Known Knowns Gender – male, female (1) Age – in years (56) Working pattern – full time or part-time (1) Pay band (7) Agency – VOSA, DVLA etc (1) Work Location – Bristol, Swansea, Hastings etc (3) Job type – coastguard, office admin, driving examiner, vehicle inspector etc (17) Claimed Overtime (0) Booked Sickness Absence in days (1)

7 Partially Known Knowns Race – white, BME or unknown (1,0,0) Disabled status – non-disabled, disabled, unknown (1,0,0) Religion or Belief – Holds a belief, no belief, unknown (0,1,0) Sexual Orientation – Heterosexual, LGB, unknown (1,0,0) Booked Learning & Development in days (0) Agreed Performance Mark (2)

8 Known Unknowns Qualifications Skills External commitments Motivation Attitude Amount of home working Job content Ambition and expectations Engagement

9 Unknown unknowns….

10 Equality Monitoring Coverage Staff in Post by location and pay band –a snap shot - 31 st March 2012 Performance – April/July Recruitment Cessations Discipline Cases Grievance Cases Learning and Development Sickness Absence

11 Diversity Characteristics by Agency Proportion of staff in post with known… DfT(C)DSADVLAGCDAHAMCAVCAVOSAAll DfT Sex100.0% Race79.6%91.8%98.1%98.9%84.6%88.3%100.0%91.7%91.2% Disabled status85.4%92.2%88.4%100.0%78.4%75.2%100.0%94.6%86.8% Religion and belief52.4%40.1%13.9%61.8%53.1%13.2%0.0% 27.9% Sexual orientation56.3%45.4%21.2%61.2%65.4%61.6%0.0% 37.1% Age100.0%

12 Proportion of staff by minority group Minority proportions of staff in post with known… DfT(C)DSADVLAGCDAHAMCAVCAVOSAAll DfT SexFemale36.4%29.3%62.2%9.0%28.4%31.4%27.9%27.7%40.9% RaceBME16.1%4.9%2.5%18.2%8.8%3.5%6.8%4.3%5.7% Disabled statusDisabled5.4%11.0%16.7%2.2%6.5%10.9%4.1%4.6%10.6% Religion and beliefNo Religion30.5%19.1%22.7%24.5%9.9%2.1%N/A 18.0% Sexual orientatio nLGB4.9%3.0% 1.8%2.4%1.2%N/A 2.9% Age60+5.1%16.1%4.8%19.7%7.6%11.3%8.8%10.9%8.5%

13 Prime Minority Groups By Job Type

14 Cluster Analysis by Job Type

15 Prime Minority Groups By Grade

16 Performance Factors by Agency

17 Other Characteristics Length of Service in –Civil Service –Department/Agency –Pay Band Diversity Characteristics of Line Manager –Sex –Race –Disability Status

18 Performance in DfT(C) 2011/12

19 Other Significant Results Two thirds of DfT are 40+ Fewer than 3% under 25 years old Part-time staff likely to be 40+, female and in lower pay bands Males and U40s more likely to be involved in Discipline cases Disabled staff more likely to raise a Grievance case Disabled, Part-time, U40s, females and staff in lower pay bands more likely to take S/A

20 Conclusions Need to think of staff in terms of multiple characteristics Beware of Proxy Indicators Job Types vary considerable – e.g. skills required Job Types have different diversity mixes Minority groups are underrepresented in higher pay bands Some minority groups receive relatively lower performance marks but no proof of bias - need more information – e.g. what do staff do? Pace of change is slow Maintain pressure on staff to declare their characteristics


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