UNITRANS Staffing Dashboard

Overview

Group-wide key performance indicators

Total Employees

7,642

Across all divisions and countries

Operating Staff

6,812

89.1% of total workforce

Support Staff

830

10.9% of total workforce

Drivers

3,770

Largest single staff category

Operational Sites

393

Cost centres across all divisions

Countries

9

Pan-African operations

Head Office Staff

270

7 support service divisions

Expat Staff

21

Deployed to cross-border operations

Divisions

Staff composition across all six divisions

Staff Composition by Division

Breakdown of drivers, operators, and support staff across all six divisions

Drivers
Operators
Support Staff

Freight

2,044employees

Operating 90.1%Admin 9.9%

1,368

Drivers

13

Operators

663

Support

Passenger

1,907employees

Operating 95.3%Admin 4.7%

1,270

Drivers

0

Operators

637

Support

Consumer

1,607employees

Operating 93%Admin 7%

720

Drivers

167

Operators

720

Support

Agriculture

1,389employees

Operating 88%Admin 12%

255

Drivers

141

Operators

993

Support

Mining

425employees

Operating 96.2%Admin 3.8%

157

Drivers

110

Operators

158

Support

Administration (HO)

270employees

Operating 14.4%Admin 85.6%

0

Drivers

0

Operators

270

Support

Top Sites

Largest operational sites by headcount

Top 20 Sites by Headcount

The largest operational sites across all divisions. Click column headers to sort.

Site	Division	Country	Total	Operating	Admin	Op %
MEX01 - Mega Express	Passenger	South Africa	338	324	14	95.9%
MBC07 - Mega Bus Secunda	Passenger	South Africa	315	307	8	97.5%
STK001A - Kil Cane	Agriculture	Tanzania	293	274	19	93.5%
MBC15 - Mega Bus Kuruman	Passenger	South Africa	228	222	6	97.4%
BAP01 - Bapotrans	Passenger	South Africa	222	216	6	97.3%
MBC16 - Mega Bus Kloof	Passenger	South Africa	173	169	4	97.7%
FFNRBMHMC - RBM HMC	Mining	South Africa	159	155	4	97.5%
SOX999Z - Moz Admin	Agriculture	Mozambique	152	123	29	80.9%
MBC12 - Mega Bus JHB	Passenger	South Africa	143	139	4	97.2%
MBC11 - Mega Bus Virginia	Passenger	South Africa	126	123	3	97.6%
SMN001B - Nchalo Infield	Agriculture	Malawi	112	103	9	92%
CSM008B - RCL Malelane	Agriculture	South Africa	100	95	5	95%
SOF999Z - Moz Admin	Agriculture	Mozambique	91	79	12	86.8%
CBL500A - Khoemacau	Mining	Botswana	89	86	3	96.6%
CIS460A - Isanti Pallets	Consumer	South Africa	87	85	2	97.7%
FGTOTAL - Total Alrode	Freight	South Africa	86	84	2	97.7%
CNH043B - Rainbow Ham.	Consumer	South Africa	80	78	2	97.5%
XMSDAT-260 - Distell GP	Consumer	South Africa	77	74	3	96.1%
CHLNGD200 - N3 Route 2	Freight	South Africa	75	74	1	98.7%
MBC22 - Mega Bus Kathu	Passenger	South Africa	75	73	2	97.3%

Showing 20 of 20 sites

Head Office

Support service divisions and key roles

Head Office — 270 Staff

The Administration division provides shared services and strategic direction from South Africa. Seven support service business units are represented.

Finance

Human Resources

Admin / Corporate

Digital & IT

Growth / Marketing

Technical & Procurement

SHEQ

Includes the CFO and full creditors, debtors, payroll and financial reporting functions.

Key Roles

Creditors Clerk14
Payroll Administrator10
Bookkeeper8
Financial Manager7
Cashbook Clerk6
Finance Officer6

Group Ratios

Support function ratios across the group

Support vs. Operating Staff

For every 1 support staff member, there are 8.2 operating staff. The group is operationally dominant.

Operating — 6,812 (89.1%)Support — 830 (10.9%)

89.1%

10.9%

Operating Staff

Support Staff

Ratio

1 : 8.2

Support : Operating

Finance : Total Staff

1 : 33.7

227 staff2.97%

One Finance professional per 34 employees across the group.

HR : Total Staff

1 : 34.6

221 staff2.89%

One HR professional per 35 employees. Includes embedded divisional HR.

ICT : Total Staff

1 : 127.4

60 staff0.79%

Lean, centralised ICT function. 83% of ICT staff are in Head Office.

Business Dev : Total Staff

1 : 186.4

41 staff0.54%

Decentralised BD function embedded within operational divisions.

Function Staff Distribution by Division

Select a support function to see how staff are distributed across divisions.

Geography

Pan-African footprint across 9 countries

Geographic Distribution

UNITRANS operates across 9 African nations. South Africa accounts for 74.1% of the total workforce.

Country	Headcount	Share	Primary Divisions
South Africa	5,665	74.1%	Freight, Passenger, Consumer, Admin
Tanzania	434	5.7%	Agriculture
Mozambique	433	5.7%	Agriculture, Freight
Botswana	405	5.3%	Freight, Mining
Eswatini	257	3.4%	Freight, Agriculture
Malawi	216	2.8%	Agriculture
Namibia	111	1.5%	Freight
Madagascar	100	1.3%	Mining
Zambia	21	0.3%	Agriculture

Expatriate Deployment

21 staff on permanent expat contracts, deployed exclusively to cross-border operations in management and technical roles.

Malawi

Agriculture

8

Mozambique

Agriculture / Freight / Passenger

7

Madagascar

Mining

4

Tanzania

Agriculture

1

Eswatini

Freight

1

Grade Structure

Job grade distribution and span of control

Job Grade Distribution

A classic pyramidal structure — 60% of the workforce is in the Semi-Skilled to Operational bands (GG3–GG6).

Executive & Senior Exec58

0.76%

Senior & Middle Mgmt319

4.17%

Supervisory / Specialist592

7.75%

Skilled / Ops / Semi-Skilled5,986

78.3%

Entry Level687

8.99%

Avg Direct Reports

11.4

Per manager across the group

Managers with 20+ Reports

69

Predominantly in Passenger & Freight

Max Span of Control

228

Single depot manager (Passenger div.)

Workforce Mix

Contract types and employment arrangements

Workforce Mix — Contract Types

88% of the workforce holds permanent contracts. Seasonal workers (371) are concentrated in the Agriculture division.

Permanent6,727 (88%)

Fixed-Term380 (5%)

Seasonal371 (4.9%)

Learnership45 (0.6%)

Expat (Permanent)21 (0.3%)

Disability Benefit20 (0.3%)

Other78 (1%)

Seasonal Workers — 371

Concentrated in the Agriculture division, primarily at Kil Cane (Tanzania) and Tambankulu (Eswatini). Reflects a cyclical operational model tied to harvesting seasons.

Learnerships — 45

40 learnerships are based in Head Office (Administration division), indicating a strong central graduate and trainee pipeline. 5 are in the Passenger division.

HR Automation & AI

Automation potential, cost savings, and 3-year impact model

HR Automation & AI Impact

Analysis of automation potential, 3-year cost trajectory, and effort reallocation for the UNITRANS HR function. Benchmarks: APQC 2024/25 · Gartner 2025 · Deloitte 2025 · McKinsey Sep 2024 · Infeedo.ai · WonderBotz

👥Total HR Staff

221

Current (2025)

🤖Automatable FTEs

114

52% of function

📉Net Attrition FTEs

39

Over 3 years, no retrenchments

🔄Redeployed FTEs

75

To HRBP / COE / Analytics

💰Cumulative Saving

R24.6m

By Year 3 (net of tech investment)

📊HR Cost / Employee

R11 778

vs R14 277 today (↓17.6%)

Automation Potential by HR Role Category

Solid bars = current FTEs | Hatched bars = estimated automatable FTEs (3–5 year horizon)

Current FTEs
Automatable FTEs

Role Category	Current FTEs	Automation %	Automatable FTEs	Annual Saving (R)
HR Admin & Records	80	65%	52.0	R10.28m
Payroll & Benefits Admin	25	60%	15.0	R2.96m
HR Query Handling (HRSS)	20	70%	14.0	R2.77m
Recruitment & Onboarding	15	50%	7.5	R1.48m
People Dev & Training Admin	35	40%	14.0	R2.77m
IR / ER Support & Docs	18	30%	5.4	R1.07m
HR Reporting & Analytics	8	45%	3.6	R0.71m
Strategic HR / HRBP / OD	12	15%	1.8	R0.36m
Management & Executive	8	10%	0.8	R0.16m
TOTAL	221	52%	114.1	R22.55m

Annual saving assumes 40% of automatable FTEs result in net headcount reduction via natural attrition at avg HR CTC R380K + 30% on-costs = R494K per FTE.

Data Sources & Benchmarks: APQC HR Automation Assessment 2024/25 (top-quartile orgs automate 40–60% of recurring HR tasks) · Gartner 2025 (50% of HR activities AI-automated by 2030) · Deloitte 2025 (40% reduction in time-to-hire, 70% decrease in cost-per-hire) · McKinsey Sep 2024 (15–20% reduction in HR query volume via digital deflection in logistics) · Infeedo.ai Dec 2025 (automation cuts 70% of manual HR tasks) · WonderBotz case study (AI agent reduces onboarding time by 75%) · Paycom Jan 2026 (HCM productivity gains up to 64%) · SHRM Oct 2025 (job transformation more likely than elimination)

Fleet Utilisation

Vehicle utilisation rates, contract analysis, and staffing impact — February 2026

Vehicle Utilisation & Staffing Impact

February 2026 · 2,135 assets · 255 contracts · 5 operational divisions. Analysis of how fleet utilisation rates drive staffing requirements and cost.

Mining

93.1%

96 vehicles · 3 505 avg km

Freight

81.5%

912 vehicles · 6 889 avg km

Agriculture

72.2%

275 vehicles · 4 918 avg km

Consumer

72.0%

517 vehicles · 5 977 avg km

Passenger

0.4% ⚠

232 vehicles · 58 avg km

⚠ Data anomaly — investigate

Fleet Utilisation Rate vs. Industry Benchmark — February 2026

Actual KM ÷ Budget KM per division. Benchmark = transport sector median for each fleet type. Passenger division data is anomalous and requires investigation.

Actual Util %
Benchmark %

Fleet Summary by Division

Division	Vehicles	Avg KM / Vehicle	Actual Util %	Benchmark	vs Benchmark	Status
Mining	96	3 505	93.1%	87.5%	+5.6pp	Excellent
Freight	912	6 889	81.5%	82.5%	-1.0pp	Healthy
Agriculture	275	4 918	72.2%	75.0%	-2.8pp	Monitor
Consumer	517	5 977	72.0%	77.5%	-5.5pp	Monitor
Passenger	232	58 ⚠	0.4% ⚠	75.0%	N/A	Data Anomaly

Supervisory Layers

Span of control benchmarking, rationalisation scenarios, and combined savings waterfall

Supervisory Layer & Cost Optimisation

Analysis of 849 staff across GG9-10 and GG11-12 bands · Span of control benchmarking · Rationalisation scenarios · Combined savings waterfall (R239m potential).

Critical Finding: UNITRANS has 849 staff in GG9-10 and GG11-12 bands at spans of control of 2.3–2.4:1. The industry median is 8.5:1 and best-practice operators achieve 12:1. UNITRANS has approximately 3.5–4× more supervisors per frontline worker than the industry norm.

Supervisory Span of Control vs. Industry Benchmarks

Subordinates per manager at the supervisory/middle management layer.

UNITRANS Grade Band Structure — Full Detail

Grade Band	Role Level	Headcount	% of Workforce	Span to Layer Below	Status
GG18-20	C-Suite / Executive	9	0.1%	5.4:1	Normal
GG15-17	Senior Executive	49	0.6%	1.3:1	Monitor
GG13-14	Senior Management	62	0.8%	4.1:1	Normal
GG11-12	Middle Management	257	3.4%	2.3:1	Critical Gap
GG9-10	Supervisory / Specialist	592	7.7%	2.4:1	Critical Gap
GG7-8	Skilled / Senior Ops	1 413	18.5%	1.7:1	Normal
GG5-6	Operational	2 412	31.6%	—	Normal
GG3-4	Semi-Skilled	2 160	28.3%	—	Normal
GG1-2	Entry Level	687	9%	—	Normal
TOTAL		7,641	100%	—	—

Recommendations

25 prioritised recommendations across 7 areas — filterable, with financial impact and implementation timeline

Recommendations

25 prioritised recommendations across 7 areas, derived from the full benchmarking, HR structure, fleet utilisation, supervisory layer, IT, and business development analyses. Combined 3-year net return: R393.5 million.

Total Recommendations

25

Critical Priority

9

FTE Net Reduction

−343

Annual Net Saving

R239.4m

3-Year Net Return

R393.5m

Investment Required

R94.2m

Filter Recommendations

Area

Priority

Timeline

Showing 25 of 25 recommendations

Transformation Programme

The case for change, 5 workstreams, financial profile, 36-month roadmap, governance, risks, and key decisions

Transformation Programme

Five workstreams · 39 actions · 36-month horizon · R758m+ 3-year net return

The Diagnosis

▸Operationally best-in-class: 89.1% operational staff, 8.2:1 operating ratio — top quartile globally
▸Supervisory layers 3.5–4× denser than industry benchmarks — costing R152m above norm annually
▸Only 22.5% of fleet contracts operate in the healthy 75–85% utilisation band
▸IT function 2.3× below sector median (0.79 vs 1.80 per 100 employees)
▸Business Development 1.9× below sector median (0.54 vs 1.00 per 100 employees)
▸HR model not yet aligned to Business Partner standard (2.4/5 vs peer average 3.4/5)

The Opportunity

R239m

Annual cost savings — without forced retrenchments

R455m

Annual revenue uplift — from BD & IT investment

R758m+

3-year net return — after all investment

R14,277 → R11,778

HR cost per employee — by Year 3

457 FTEs

FTE reductions — via attrition & redeployment

20–40%

IT capability improvement — operational improvement potential

The Approach

▸5 workstreams, 39 specific actions, 36-month implementation horizon
▸No forced retrenchments — achieved through natural attrition and redeployment
▸Self-funding from Year 2 onwards — Year 1 investment recovered by Month 14
▸Governed by Transformation Steering Committee (CEO + CFO + all DGMs)
▸Independent benchmark review at Month 18 and Month 36

R239m

Annual Cost Savings

R455m

Annual Revenue Uplift

R758m+

3-Year Net Return

457 FTEs

Reductions (no forced retrenchments)

5 Workstreams

39 Actions · 36 Months