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Business area digitalisation analysis

Digitalisation of fleet and equipment management

How to better manage asset availability, maintenance, fuel, documents, safety and total cost of ownership

Digital maturity

Typical digital maturity

Shows the level of technological and process digitalisation at which companies in the sector or business area typically operate today.

A typical market situation is assessed, not the most advanced companies.

The assessment consists of five equally weighted dimensions:

Core system usage
Whether ERP, CRM, WMS, MES, customer portals or other operationally important systems are widespread in companies.
Process digitalisation
How many core processes run in systems and how many are still managed manually.
Systems integration
Whether core systems exchange data between themselves or whether employees transfer information manually.
Data quality and readiness
Whether core data is structured, up-to-date, consistent and suitable for automation and analytics.
Advanced data use
Whether real-time analytics, forecasting, automated alerts, optimisation models or AI are used.

The final score is the average of the five dimensions.

1–5 scale

  • 1 very low maturity
  • 2 low maturity
  • 3 medium maturity
  • 4 high maturity
  • 5 very high maturity

A low maturity score does not necessarily indicate low potential. On the contrary, low maturity and a high level of manual work may indicate significant untapped digitalisation value.

medium
Skaitmenizacijos potencialas

Digitalisation potential

Shows how much significant business value a typical sector or business area company can create by systematically digitalising core processes.

The rating is calculated on a 100-point scale across five dimensions:

Process frequency and scale 20 %
An assessment of how frequently the digitalised processes recur and what proportion of operations they represent.
Manual work intensity 20 %
An assessment of the extent to which processes depend on email, telephone, Excel, paper documents and repeated data entry.
Impact on revenue and costs 25 %
An assessment of the potential effect on sales, margin, customer retention, administrative costs, errors, downtime or inventory.
Growth and scale potential 20 %
An assessment of whether digitalisation would enable operational capacity to be increased without expanding headcount and costs at the same rate.
Impact on decisions and risk 15 %
An assessment of the potential effect on data reliability, decision-making speed, customer experience, and the reduction of errors and operational risk.

The final score is calculated according to the assessments and weights of all dimensions.

100-point scale

  • 0–20 very low potential
  • 21–40 low potential
  • 41–60 moderate potential
  • 61–80 high potential
  • 81–100 very high potential

A high score does not mean the solution will be easy to implement. It indicates the size of the potential value, not the implementation complexity.

84/100
Biggest challenge
Asset data is fragmented across multiple systems
Biggest opportunity
Data-Driven Asset Availability

Greatest result comes not from more telematics reports, but from a single process for managing asset availability and total cost of ownership.

How fleet and equipment management works

The business area covers road transport, specialist equipment, construction, municipal and other mobile equipment fleets. The main objective is to ensure that the right assets are technically prepared, documents are valid, and usage costs are justified.

Assets physically move and operate under different conditions

Mileage, operating hours, load and environment affect maintenance needs.

Failure directly halts revenue or service

Downtime of critical assets often requires expensive replacement.

Costs are fragmented across many sources

Fuel, repairs, tyres, insurance, taxes and depreciation are analysed separately.

Document deadlines are critical

Technical inspections, insurance, permits and certificates must be controlled for each specific asset.

Market and technology context

Electrification, the abundance of telematics data, remote diagnostics and predictive maintenance are transforming fleet management. Real value emerges when technical signals are connected with maintenance tasks, the operational plan and finance.

  • Fuel and energy cost pressureMore precise comparison of drivers, vehicles and work scenarios is required.
  • ElectrificationCharging, battery condition and route suitability introduce new planning variables.
  • Remote diagnostics and telematicsThe number of technical signals is increasing, requiring conversion into specific maintenance tasks.
  • Safety and compliance requirementsDocumentation, inspections and driver or operator qualification checks must be traceable.

Typical activity chain

01

Asset acquisition and registration

Asset profile, technical data, documents and usage rules are created.

02

Allocation and usage

Assets are allocated to a department, employee, facility or task.

03

Telematics and consumption monitoring

Mileage, working hours, location, fuel, energy and usage signals are recorded.

04

Maintenance and repair

Work is planned, including breakdowns, spare parts, workshops and downtime.

05

Document and compliance control

Deadlines for inspections, insurance, permits and certificates are monitored.

06

Total cost of ownership and asset replacement decisions

Utilisation, costs, residual value and optimal replacement timing are evaluated.

Digital maturity model

0

Asset register and maintenance managed in spreadsheets

Documents, failures, fuel and repair history are fragmented, and asset availability is checked through employees.

1

Separate telematics, repair and accounting systems

Core data is captured digitally but not connected in a single asset profile.

2

Digitalised maintenance and document processes

Scheduled maintenance or document control operates, but telematics, the operational plan and costs are assessed separately.

3

Integrated asset profile and maintenance chain Typical current situation

Asset register, telematics, maintenance work, documents, fuel and availability KPIs linked across key asset groups.

4

Fleet managed by condition and cost Siektina

Maintenance schedules, asset allocation and replacement decisions adjusted based on actual condition, usage and total cost of ownership.

5

Predictable asset availability

Failure, energy and usage patterns help anticipate maintenance, asset replacement and optimal allocation.

Key finding

Fleet data often fragmented across telematics, maintenance, fuel card, accounting and document systems, leaving no single reliable view of asset condition.

Maintenance planning must consider not only calendar or mileage, but also actual condition, upcoming tasks and operational demand.

Best to start by selecting one asset group and connecting the register, telematics, maintenance tasks, document deadlines and key actual costs.

Related topics

Fleet management systemMaintenance managementAsset cost of ownership analytics
Next step

Assessing where asset availability and cost are being lost across the fleet

A review of asset register, telematics, maintenance, fuel, documents, utilisation and total cost of ownership will be conducted to help select the first phase.

Discuss the first digitalisation phase