Business area digitalisation analysis

Certification, inspection and laboratory services: digitalisation opportunities

How to better manage applications, samples and objects, methods, equipment, competencies, results, reviews, certificates and service 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.

92/100
Biggest challenge
The transfer history of samples, objects and evidence is insufficiently traceable
Biggest opportunity
Fully traceable process from application to certificate or test result

The greatest result is created not only by an electronic report, but by a complete reliable history of evidence and decisions, which reduces manual work whilst strengthening accreditation and quality control.

How certification, inspection and laboratory services work

The business area encompasses services of different nature, but they are linked by request qualification, competence and impartiality verification, sample or object registration, testing or inspection, review of results, decision and issuance of certificate or report. Value is created through competence, reliable data, consistent execution, quality control and a clear result delivered to the client.

Every result has a traceable origin

It is essential to know who, when, by what method, with what equipment and according to which version of the document performed the work.

Competence and impartiality are preconditions of the process

Employee qualifications, authorisations, conflicts of interest and independent decision-making must be verified before action.

A physical sample or object has a digital history

Sample collection, transport, receipt, storage, subdivision and disposal must remain traceable.

Methods and equipment have limits of validity

Method versions, calibrations, maintenance, measurement uncertainty and equipment suitability determine the reliability of the result.

Market and technology context

In compliance assessment services, clients expect a faster and more transparent process, but digitalisation cannot compromise impartiality, competence, metrological traceability and data integrity. New opportunities arise by automating evidence management, result verification and client self-service.

  • Accreditation and audit traceability requirementOrganisations must rapidly demonstrate how each result is linked to method, equipment, employee, review and decision.
  • Client expectation to see statusClients expect to submit an application, track a sample or assessment, respond to enquiries and receive documents in one place.
  • Increasing complexity of services and methodsStandard versions, specialised methods, external laboratories and international requirements are multiplying.
  • Automated capture of equipment and result dataLaboratory and measurement equipment can increasingly transmit data directly, reducing transcription risk.
  • Assessment of AI systems and other emerging technologiesNew testing and compliance services are emerging, requiring new methodologies, competencies and auditable processes.

Typical operating process

01

Request and scope qualification

The service, applicable scheme or method, object, deadline, competence requirement and possible impartiality risks are determined.

02

Planning and preparation

Staff, methods, equipment, visit or sample collection, documentation and control requirements are assigned.

03

Sample or object registration

Identity is assigned, condition, transfer history, storage and applicable requirements are recorded.

04

Testing, inspection or assessment

The specialist performs actions according to the valid methodology and records factual data and evidence.

05

Technical review and non-conformity management

Data completeness, suitability of method and equipment, calculations, exceptions and corrective actions are verified.

06

Decision, report and supervision

An independent responsible person makes the decision, a document is issued and further actions or validity control are planned.

Digital maturity model

0

Manual and fragmented process

Applications, samples, results and decisions are managed on paper and separate files, with audit history compiled manually.

1

Separate digital tools in use

Laboratory or quality systems are used, but applications, competencies and client status remain in separate tools.

2

Core stages digitalised

Sample, test or inspection stages are digitalised, but the entire chain of evidence and decision control are not yet integrated.

3

Core service scenario integrated Typical current situation

A single method or service scenario is managed from application to traceable result, technical review and final document.

4

Data-driven service

Operations are managed according to capacity, traceability, quality, timelines, equipment and service economics data.

5

Predictive and securely automated operations Siektina

The system forecasts capacity, identifies anomalies and automates standard checks, whilst professional decisions are made by competent personnel.

Key conclusion

The digitalisation potential of this business area is very high, as almost every service step must be documented, linked to a competent employee, an appropriate method, verified equipment and a traceable result.

The most common problem is not merely the absence of LIMS or a document system. Client application, assessment scope, impartiality, sample or object history, competences, methods, equipment, results and decision-making are often managed separately.

It is worth implementing the scenario 'Single method or service process from application to result' first. Only after confirming actual usage, quality control and economic benefit is it worth extending the solution to other services, clients or more advanced AI scenarios.

Related digitalisation topics

Laboratory information systemsClient application portalsQuality and non-conformance managementEquipment and calibration managementDigital certificate verification
Next step

An assessment of where the most time and traceability is lost in the assessment process

A review of applications, registration of samples or objects, competences, methods, equipment, results, technical reviews, certificates and service economics will be conducted to help select a single first version whose benefits can be clearly measured.