HR Capacity Analysis THE FIRST FORUM OF THE TERRITORIAL MANAGERS AND THE TRAINING INSTITUTES TARGETING THE LOCAL AUTHORITIES IN AFRICA HUMAN RESOURCES OF AFRICAN LOCAL GOVERNMENTS " KINGDOM OF MOROCCO, INTERNATIONAL UNIVERSITY OF RABAT (IUR), SEPT 18-21, 2017
HR Capacity Benchmarking Preliminary Toolkit
Target Countries & Cities Dire Dawa
Mekelle
Entebbe
Hoima
Ghana
Fort Portal
Tororo
Ethiopia
Uganda
Sunyani
Jinja
Kumasi Mozambique
Tamale
Bolga Tete
Nacala
Nampula
Arua
Gulu
Benchmarks
Model built incrementally on a series of information layers
Layer 1
International norms & ratios
Staffing and cadre reviews (determine average staffing levels)
Layer 2
Stretch the norm to cater to low intensity & lower quality services
Stress the norm to cater to high pop growth, rapid area expansion, partial and degraded networks, low technology
Layer 3
Derive benchmark
Variation analysis
Managerial & Tech Staff Ratio per 1,000 pop 3,500
Population ('000s)
3,000
Ethiopia, 590,332
0.4
2,500 2,000 1,500 1,000 500
0.4 1.4
0.4
0 Ghana, 2,665,798
Mozambique, 1,000,125
Uganda, 562,982
TargetCities Populationineachcountry
Ethiopia
Mozambique
Uganda
Ghana
# Managerial and technical staff per 1000 pop in target cities in each country *The Analysis doesn’t include the Support Staff/operational staff deployed by the ULB or contracted out for SWM & Sanitation and uses effective area for Ghana
Existing Capacity & FunctionalGhana Distribution (Mgmt/tech) 0
86
62
258
Uganda
Ghana 15
939
290
15 9
243
48 9
Uganda
242
Finance
Mozambique
Planning
PWD
Revenue
SWM & Sanitation
Street Lighting
0
146
Ghana
42
0
135
Mozambique
Finance
377
Revenue
Planning
12
SWM & Sanitation Street Lighting 60
Ethiopia
258
Ethiopia
92
PWD
90
48
811
243 123
361
0
200
400
600
800
62
290
17
208
*The Analysis doesn’t include the Support Staff/operational staff deployed by the ULB or contracted out for SWM & Sanitation and uses effective area for Ghana Finance Planning PWD Revenue
86
Finance PWD
Planning Revenue
SWM & Sanitation
Street Lighting
1000 SWM & Sanitation
Street Lighting
Target Capacity & Functional Distribution Ghana 136
497
600
384
Ghana
Uganda 3755 1147
991
97
258
146
Uganda
1113
214
Finance
Mozambique
137
188
261
Planning
PWD
Revenue
SWM & Sanitation
Street Lighting
405
Ghana
241
Mozambique
EthiopiaPWD
Planning
Revenue
SWM & Sanitation Street Lighting
1877
0
232
Finance
375
258
108
243
1487 258 135
500
1000 Finance
1500 PWD
Planning
290
657
222
0
62
436
107
Ethiopia
86
2000 2500Street Lighting 3000 SWM & Sanitation
Revenue
*The Analysis doesn’t include the Support Staff/operational staff deployed by the ULB or contracted out for SWM & Sanitation and uses effective area for Ghana
3500
4000
Finance PWD
Planning Revenue
SWM & Sanitation
Street Lighting
Staffing Gap by Function Excess
Shortfall
Ghana
2816
Uganda
871 Country
Mozambique
Ethiopia
-200
Ethiopia Mozambique Uganda Ghana Overall (weighted average)
1500
676
300 Finance
800 Planning
PWD
1300 Revenue
1800 SWM& Sanitation
2300 StreetLighting
2800
%age shortage w.r.t Benchmarks 45% 80% 78% 75% 73%
Staffing Gap by City 3000
2840
2500
2000
1500 1075 1000
767
720 545
500
360
266
489
442 232
59
86
135 15
106 33
39 87
162 55
Tororo
Jinja
274
358 228
223
26
126 16
58
Gulu
Arua
Hoima
279 65
278 157
0 Dire Dawa
Mekelle
Ethiopia
Tete
Nacala
Nampula
Entebbe Fort Porta
Mozambique
Uganda Total Current Manpower
Total Model Manpower
*The Analysis doesn’t include the Support Staff/operational staff deployed by the ULB or contracted out for SWM & Sanitation and uses effective area for Ghana
Kumasi
Tamale
Bolga
Ghana
Sunyani
Staffing Gap by Function City wise Excess
Shortfall
Ghana
Sunyani
121
Bolga
214
Tamale
130
Kumasi
2351
Hoima
165
Arua
110
Uganda
Gulu
248
Jinja
107
Tororo
48
FortPorta
73
Mozambique
Nampula
Ethiopia
Entebbe
Mekelle
-200
120 843
Nacala
356
Tete
301 175
DireDawa
501 0
200
400
600 Finance
800 Planning
1000 PWD
Revenue
1200 Sanitation& SWM
1400
1600
StreetLighting
1800
2000
2200
2400
Staffing Qualifications 1400 1200
No of Staffs
1000 800 600 400 200 0 DireDawa Mekelle Ethiopia
Tete
Nacala
Nampula
Entebbe FortPortal
Tororo
Mozambique
Jinja Uganda
Degree+diploma
Certificates
Gulu
Arua
Hoima
Tamale
Sunyani
Ghana
Others*
*Others Include staffs with secondary education & lower, any support staff and staff provided by concessionaire # Data not available for Bolga and Kumasi
City Level Analysis Sheet 45 120
Top Management
29
Dire Dawa 277000 29.24 Ethiopia
Middle Management
Hierarchy
City Population Area (Km2) Country
245
1145
Support staff
Current Manpower
704
DireDawa
Model Manpower
1200
Number of Employees
7%
Degree+diploma Certificates Others*
Staffing Qualification Distribution
350% 300%
1000
1%
92%
313%
250%
800
200% 600 150%
101%
400
100%
61% 200
50%
14%
13%
11%
0
0% Planning
Revenue
Current Manpower
Finance Model Manpower
PWD
Street Lighting
SWM & Sanitation
Current Manpower as %age of Model Manpower
Annual Salary Comparison Ghana (Eng & Planners)
Monthly Salary Comparison Uganda (Eng & Planners
Current Tools Input Questionnaire
Output Analysis Present current staffing against benchmark adjusted on generic lines cities.
City: area, pop, infra network Service characteristics Employee no, qualif, status
Static analysis
Hierarchy Information:
l ua n Ma
k Lin Manual collation of data from questionnaire,
Issues: Generic questions don’t capture local nuance Generic levels in hierarchy Error prone data capture & time consuming at scale No data validation or user feedback in real time
Proposed Tools
Output Analysis
Central Data store U
Input Questionnaire City and Service Info. Sig on sheet/ in cell instructions Answers validated e.g. text, Integer, % . Commentary to capture nuance. Additional questions to refine benchmarks.
Deeper more insightful analysis 3,500
Breakeven Analysis
8,000
3,000
7,000
2,500
6,000
2,000
5,000
1,500
4,000
1,000
3,000
500
2,000
0 -500
100 Full Cycle NPV Capex (US$M)
1,000 200
300
400
0 500
Linking of data for single entry, Validation and additional commentary
Di
k Lin t r ec
Enhancements: Use full Excel capabilities to reduce error, increase completeness. Automate data storage for error free recovery. Direct link to benchmarks to allow applicant to see comparisons in real time.
Options for Deeper Analysis with Tools such as PowerBI for interactive graphics and add data combinations
Enhancements: Interactive data to analysis displays on city performance Ranking and interrogation of the analysis of more cities to highlight areas for best in class models and the sharing of best practice.
Way Forward
Validation of model (consultations and site visits)
Fine tuning to examine impacts of
technology/ design and service delivery parameters
service delivery models (out-sourcing, management contracts, concessions)
Increase sample size to next range of cities
Introduce new benchmarks
Examine recruitment options, implications and affordability
Training options, implications and costs
Real remuneration incentives and gaps
Develop alternative service models