Business Area Digitalisation Analysis

Engineering and technical consultancy: digitalisation opportunities

How to better manage requirements, models, calculations, changes, technical reviews, site data and project profitability

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.

88/100
Biggest challenge
Versions of models, drawings and documents are managed in a fragmented way
Biggest opportunity
Traceable technical solution from requirement to actual asset condition

The greatest result is delivered not by yet another model repository, but by a process in which every technical solution has a clear requirement, assumptions, version, responsible specialist and approval history.

How Engineering and Technical Consultancy Works

The business area encompasses services of different nature, but they are linked by needs analysis, design, technical calculations, coordination, change management, technical review and project supervision. Value is created through competence, reliable data, consistent delivery, quality control and a clear outcome delivered to the client.

Solution quality depends on assumptions and version

The same drawing or calculation may be valid only for a specific version of requirements, loads and other input data.

Changes have many indirect consequences

A single technical change can affect other models, disciplines, quantities, procurement, schedules and facility operation.

Professional responsibility cannot be transferred to the system

Automation can check rules and assist in analysis, but the final decision must be made by a competent specialist.

Design and facility data often become separated

Facts established during construction or operation do not always flow back into models, calculations and organisational knowledge.

Market and technology context

In engineering services, digitalisation of models and documents is already advanced, but the competitive advantage is shifting towards traceability of technical solutions, rapid change assessment, cross-disciplinary coordination and the ability to reliably utilise object data at the next stage.

  • BIM and common data environment developmentClients expect consistent control of models, documents, versions and approvals.
  • Shorter design and construction timelinesTechnical issues and changes must be assessed more quickly without sacrificing review quality.
  • Greater cross-disciplinary complexityModels, calculations and solutions must be coordinated between more specialists and external partners.
  • Use of facility data for maintenanceDevelopers and property managers expect structured factual data rather than merely an archive of final files.
  • AI assistance for design and document analysisAI can accelerate the analysis of options, requirements and non-conformities, but clear sources and expert validation are required.

Typical operating process

01

Qualification of need, facility and requirements

Project scope, initial data, applicable standards, responsibilities and risks are established.

02

Technical solution planning

Disciplines, specialists, structure of models and documents, review and coordination points are allocated.

03

Design and calculations

Models, drawings, calculations, specifications and justification of solutions are created.

04

Coordination and change management

Conflicts, client comments, impact of other disciplines and consequences of change are checked.

05

Technical review and approval

Compliance with requirements, methodologies, standards and professional control actions is verified.

06

Facility maintenance, handover and knowledge update

Actual condition, non-conformances, changes made and information for reuse are recorded.

Digital maturity model

0

Manual and fragmented process

Requirements, models, calculations and comments are stored in separate files, and the history of decisions depends on individual specialists.

1

Separate digital tools in use

Design and document tools are in use, but versions, approvals and client comments are transferred manually.

2

Core stages digitalised

Design, review or site comment stages are digitalised, but the impact and economics of changes are not yet linked.

3

Core service scenario integrated Typical current situation

A single project change scenario is managed from requirement and model object through to review, approval and new version.

4

Data-driven service Siektina

Projects are managed according to unified requirements, versions, changes, quality, capacity and margin data.

5

Predictive and safely automated operations

The system predicts conflicts, validates rules and assists in generating options, but the solution is approved by a competent specialist.

Key finding

The digitalisation potential for engineering services is very high, yet value is created not merely by storing models or documents. The critical element is the link between requirement, technical object, calculation, solution, change and professional approval.

Typically, CAD, BIM, calculation, project and document systems are already in use, yet client comments, decision rationale, impact of changes and actual site observations remain fragmented.

It is worth implementing the 'Single project change management' scenario first. Only after confirming real usage, quality control and economic benefit is it worth extending the solution to other services, clients or more advanced BIM scenarios.

Related digitalisation topics

BIM and common data environmentProject management systemsTechnical maintenance solutionsDocument and version managementEngineering knowledge management
Next step

An assessment of where the most specialist time and project margin is lost in the engineering process

The requirements, models, calculations, changes, technical reviews, site observations and project economics processes will be reviewed to help select one first phase where the benefit can be clearly measured.