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
medium
Skaitmenizacijos potencialas
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
Problemos
Most common digitalisation problems
The most significant problems arise when standards, certification schemes, client objects, samples, methods, equipment, calibration data, results, non-conformities, reviews and certificates are not connected to actual work, quality control, client decisions and service economics.
The transfer history of samples, objects and evidence is insufficiently traceable
Critical
Sample collection, transport, receipt, division, storage and disposal are recorded using different means.
Consequences
The risk of sample confusion, improper storage and result disputes increases.
The suitability of the method, equipment and calibration is checked too late
Critical
Method versions, measurement limits, calibration validity, maintenance and equipment reservation are not linked to a specific task.
Consequences
A test may be performed with unsuitable or invalid equipment, and the task must be repeated.
Technical review and decision separation are managed inconsistently
Critical
Mandatory checks, exceptions, non-conformities and decision independence depend on local processes and employee habits.
Consequences
The risk of inconsistent quality, incorrect decisions and accreditation non-conformity increases.
Client request and assessment scope are formed manually
High
Standards, schemes, object properties, methods, deadlines, locations and previous history are collected from different documents and conversations.
Consequences
Proposals are prepared slowly, necessary competences or methods are missed, and scope changes during execution.
Competence and impartiality checks are performed in a fragmented manner
High
Staff authorisations, method competence, conflicts of interest and decision independence are checked in spreadsheets or separate registers.
Consequences
An unsuitable employee may be assigned to a task, and evidence of control is difficult to reconstruct later.
Results and equipment data are transcribed manually
High
Measurement results, calculations and metadata are transferred from equipment, files or paper forms into reports.
Consequences
The risk of transcription errors, version mismatches and data integrity issues increases.
Non-conformities and corrective actions are not linked to the entire process
Medium
Client, sample, method, equipment or audit non-conformities are recorded in separate spreadsheets and documents.
Consequences
The same root causes recur, corrective actions are delayed, and their effectiveness is difficult to assess.
The client does not see a single application, sample or certification status
Medium
Enquiries, missing documents, visits, review of results and certificate issuance are communicated by email.
Consequences
Status enquiries multiply, client responses are delayed, and final result delivery is postponed.
Service, method and client profitability is visible too late
Medium
Proposal scope, employee time, equipment usage, reagents, external services and invoices are not linked.
Consequences
Loss-making methods or services are noticed after the fact, and capacity and pricing decisions remain approximate.
Opportunities
Greatest digitalisation opportunities
Single method or service process from application to resultVery high impactFor one frequent method, inspection type or certification scheme, connect the application, scope, sample or object registration, competence and equipment verification, results, technical review and final document.Shorter qualification and client response cycle
Integrated laboratory or inspection workflowVery high impactConnect the order, sample or object, method, employee, equipment, actual results, review and report.More reliable execution and less manual work
Digital chain of custody for samples and evidenceVery high impactUse unified identification, timestamps, transfer confirmations, storage conditions and complete status history.Lower risk to sample and evidence integrity
Competence, authorisation and impartiality rules engineVery high impactAutomatically verify staff competence, method scope, conflicts of interest and decision independence before work commences.Lower accreditation risk
Method, equipment and calibration managementHigh impactLink method versions, equipment suitability, calibration, maintenance, reservation and specific job results.Fewer repeat tests and inappropriate equipment use
Result verification, review and decision workflowVery high impactAutomatically check completeness, limits, calculations, exceptions and ensure separated technical review and decision roles.Faster document issuance and more consistent quality
Capacity, lead time and service economics analyticsHigh impactLink job flow, method workload, equipment utilisation, staff time, reagent or subcontractor costs and revenue.More accurate planning and pricing
Biggest opportunity
Fully traceable process from application to certificate or test result
Linking assessment scope, impartiality and competence verification, sample or object identity, method, equipment, result, technical review, non-conformities and final decision.
Shorter service delivery time
Less manual data re-entry
More reliable chain of custody for samples and evidence
More consistent competence and impartiality control
Faster technical review and certificate issuance
Lower accreditation and data integrity risk
More accurate profitability analysis of services, methods and equipment
Expected business impact and financial result
Shorter service cycleAutomatic checks, clear statuses and reduced data re-entry accelerate work from application to document.
More reliable traceabilityEach sample, object, method, equipment, employee and result has a single integrated history.
Lower accreditation riskCompetences, impartiality, reviews, validity of methods and equipment are verified during the process.
Greater staff and equipment capacityLess time spent on data searching, re-entry and repetitive administrative checks.
Better client experienceThe client sees missing actions, sample or assessment status, documents and validity.
More accurate service economicsStaff, equipment, reagent, external service and rework costs are linked to the service.
Sprendimai
How to solve these problems
Solution directions linked to specific business area problems they address.
Problema
Customer application and assessment scope are formed manually
→
Sprendimo kryptis
Customer application and results portal
Enables the customer to select a service, submit object or sample information, documents, view status, answer questions and receive final documents.
Problema
Customer cannot see the status of a single application, sample or certification
→
Sprendimo kryptis
Customer application and results portal
Enables the customer to select a service, submit object or sample information, documents, view status, answer questions and receive final documents.
Problema
Transfer history of samples, objects and evidence is insufficiently traceable
→
Sprendimo kryptis
Customer application and results portal
Enables the customer to select a service, submit object or sample information, documents, view status, answer questions and receive final documents.
Problema
Transfer history of samples, objects and evidence is insufficiently traceable
→
Sprendimo kryptis
LIMS or inspection work management platform
Links order, sample or object, method, employee, equipment, results, evidence, review and report.
Problema
Results and equipment data are re-entered manually
→
Sprendimo kryptis
LIMS or inspection work management platform
Links order, sample or object, method, employee, equipment, results, evidence, review and report.
Problema
Technical review and decision separation are managed inconsistently
The risk of inconsistent quality, incorrect decisions and accreditation non-conformity increases.
→
Sprendimo kryptis
LIMS or inspection work management platform
Links order, sample or object, method, employee, equipment, results, evidence, review and report.
Recommended digital solutions
Solutions must maintain an unbroken link between application, sample or object, method, equipment, competency, result, review and final decision.
Customer application and results portal
Enables the customer to select a service, submit object or sample information, documents, view status, answer questions and receive final documents.
LIMS or inspection work management platform
Links order, sample or object, method, employee, equipment, results, evidence, review and report.
Sample and evidence chain of custody system
Uses unique identifiers, labels, transfer confirmations, storage conditions and full sample or evidence history.
Competence, authorisation and impartiality management system
Automatically verifies employee competence, method scope, conflicts of interest, separation of review and decision-making roles.
Method, equipment and calibration management platform
Manages method versions, equipment suitability, calibration, maintenance, reservations and link to specific result.
Quality, non-conformance and corrective action system
Integrates technical reviews, deviations, customer complaints, internal non-conformances, root cause analysis, corrective actions and effectiveness verification.
Service capacity and profitability analytics platform
Integrates order flow, staff and equipment utilisation, deadlines, material and subcontracting costs, invoices and margin.
When the investment is justified
Investment justified
Application scope is regularly clarified through multiple emails
Sample transfer and storage history is maintained on paper or spreadsheets
Results are manually transcribed from equipment or files
Competences, authorisations and calibrations are checked in different registers
Technical review and certification decision lack a single status history
Clients frequently enquire about the status of samples, visits or certificates
There is one frequent method or service type suitable for a pilot
Reikia atsargumo
There are no unified identifiers for samples, objects and results
Method and equipment data lack clear ownership
There is an attempt to digitalise all accreditation areas in one stage
The first version is planned as a document repository without workflow
There is no clear separation between technical review and decision-making roles
Automated decision-making is considered an opportunity to reduce professional review
Ideal first version
The first version should be limited to a 'single method or service process from enquiry to result' scenario with real pilot users. It must cover the entire path to an approved result, not just an isolated form or integration.
Structured client request
The client selects the service, submits object or sample data, documents and deadline.
Sample or object registration
A unique identifier is assigned and the transfer and status history is recorded.
Competence, method and equipment verification
Before work begins, employee authorisations, method version and equipment validity are verified.
Results registration and automatic checks
Data is obtained from equipment or entered via controlled form, and the system verifies completeness and limits.
Technical review and decision workflow
Execution, review and final decision roles are clearly separated.
Client status and final document
The client sees process progress, responds to questions and receives only the approved document.
Quality and process KPIs
Cycle, rewriting, review returns, rework, deadlines and margin are measured.
Kam pirmiausiaClient representatives · Enquiry and sample reception staff · Laboratory specialists or inspectors · Technical reviewers · Certification decision-makers · Quality managers
What not to include in the first versionSupport for all methods and certification schemes · Replacement of all existing LIMS or quality systems · Automatic final certification decision · Integration of all laboratory equipment · Migration of all historical samples · Complete DI systems testing services module
Investment priorities
Single method or service process from application to resultThe scenario 'Single method or service process from application to result' allows the process time, quality and economic outcome to be measured with minimal managed scope before scaling the solution.
Standardise application, sample, object and result identifiersEstablish core data objects, owners, statuses and audit history.
Implement competency, equipment and impartiality controlsMandatory checks to be performed before work, not only during audit.
Automate result acquisition and quality checksReduce re-entry, link equipment data to sample and route exceptions to specialist.
Only then expand AI and new conformity assessment servicesDeploy advanced scenarios once reliable data, validated methodologies and clear professional accountability are in place.
Key implementation conditions
Sample or object identity cannot change between systems
Label, register, equipment result, report and invoice must use the same identifier.
Method and standard versions must be linked to the work
It must be clear which version was used for the assessment and when it was valid.
Competence verification must take place before assigning work
The system must evaluate employee authorisation for a specific method, business area and role.
Technical review and decision must remain separated when required
Automation cannot eliminate independent human decision-making and separation of roles.
Equipment data integration must preserve the original source
Result changes, recalculations and imports must have a clear audit history.
Recommended implementation sequence
01
Current process and data diagnostics
Establish how application qualification, competence and impartiality verification, sample or object registration, testing or inspection, results review, decision and certificate or report issuance occur today; identify where manual work, waiting, errors and multiple versions of information arise.
Process and responsibilities map
Systems and integrations map
Master data owners
List of most common exceptions
Baseline KPI values
02
First scenario boundaries
Define the users, boundaries, data, integrations, control rules and pilot success criteria for the 'Single method or service process from application to result' scenario.
Target users and pilot clients
Functional and integration boundaries
Data and rules preparation plan
Security and quality controls
Pilot success criteria
03
Creation of a single assessment process
Create a working 'Single method or service process from application to result' scenario with core statuses, integrations, approvals, exception handling and selected KPIs.
Structured client application
Sample or object registration
Competence, method and equipment verification
Results recording and automated checks
Technical review and decision workflow
Client status and final document
04
Pilot use
Test the scenario 'Single method or service process from application to result' in real work, eliminate the most frequent exceptions and compare the result with the baseline.
User and client onboarding
Usage and error monitoring
Exception and incident workflow
KPI comparison with baseline
Refined development plan
05
Development and advanced automation
Expand the proven certification, inspection and laboratory service model to other services or clients, and use the accumulated reliable data for analytics, forecasting and safely managed AI.
Development of additional processes and integrations
Centralised performance and profitability analytics
Reuse of knowledge and methodologies
Advanced automation pilots
AI quality, risk and human control rules
Recommended KPIs
Time from application to confirmed scoped.
Measure the speed of the qualification process.
Proportion of fully traceable samples or objects%
Measure the quality of the chain of evidence.
Proportion of results automatically obtained from equipment%
Monitor the reduction in transcription.
Proportion of work using valid equipment and method%
Measure method and equipment control.
Technical review durationh.
Assess the efficiency of the review process.
Proportion of services delivered within the agreed timeframe%
Assess the fulfilment of the promise given to the client.
Gross margin by service or method%
Measure the economic outcome.
Key risks
Digitalisation creates gaps in the audit trailData is transferred between systems without a clear record of source, changes and responsible employee.Kaip suvaldyti Design immutable audit logs, common identifiers and mandatory version control.
Sample label becomes separated from electronic recordPhysical sample and system data may be confused during transfer or sharing.Kaip suvaldyti Use reliable labels, scanning at every critical point, and discrepancy blocking.
Automated verification replaces professional reviewThe system may miss an unusual but significant case.Kaip suvaldyti Automate standard rules, whilst leaving professional exceptions and final decision to competent staff.
First stage includes too many methods and schemesDifferent rules and exceptions expand the project and delay actual use.Kaip suvaldyti Start with one frequently used method or service type and clear KPIs.
Client sees unconfirmed resultsInterim data may be understood as final conclusion and used incorrectly.Kaip suvaldyti Clearly separate internal, under review, and confirmed statuses from external visibility.
Inovacijos
Advanced digital innovations
Automated checks and AI can help detect exceptions, but must not eliminate the requirements for technical review, impartiality and competent decision-making.
Already applied in the sector2
Automated validation of results and metadata
Highly urgent
Rules verify measurement limits, mandatory fields, control samples, calculations, units and method requirements.
How it is applied Used before technical review so that the specialist can focus on significant exceptions.
What value can be created
Fewer manual checks
Earlier detection of errors
Shorter review
What is needed for this to work
Structured results
Validated method rules
Confirmation of exceptions
Short-term perspectiveCommercial solutions are available
Direct equipment data transfer
Highly urgent
Results and metadata are automatically obtained from laboratory or measurement equipment, maintaining the source link.
How it is applied Suitable for frequently used equipment, where manual transcription creates significant error and labour risks.
What value can be created
Less transcription
Greater data integrity
Faster result preparation
What is needed for this to work
Equipment interfaces
Unified sample identifiers
Data validation
Short-term perspectiveCommercial solutions are available
Market expansion2
Image analysis for standardised inspection tasks
Relevant
AI helps detect visible defects, non-conformities, labelling or assembly discrepancies.
How it is applied Used for clearly defined and sufficiently frequent inspections, with the final decision made by the inspector.
What value can be created
More consistent inspections
Faster evidence assessment
Greater inspection coverage
What is needed for this to work
Quality image samples
Clear defect classes
Inspector confirmation
Medium-termApplied in practice
Verifiable digital certificates and reports
Relevant
The authenticity, validity, version and status of a document can be verified online using a unique identifier.
How it is applied Used by clients, institutions and partners to quickly verify issued results.
What value can be created
Lower risk of forgery
Faster verification
Fewer administrative enquiries
What is needed for this to work
Centralised document register
Validity statuses
Secure public verification mechanism
Short-term perspectiveCommercial solutions are available
Early stage1
AI system testing and compliance assessment services
Relevant
Methodologies are developed to evaluate AI model performance, data quality, reliability, bias and governance processes.
How it is applied This is a new service area for organisations with the necessary technical competencies and a clearly defined assessment scope.
What value can be created
New revenue
Higher-value expert services
Utilisation of new competencies
What is needed for this to work
Validated methodologies
AI and statistics competence
Impartiality and accountability model
Medium-termApplied in practice
D.U.K.
Frequently asked questions
Where to start with the digitalisation of certification, inspection or laboratory services?
Select one frequent method, inspection type or certification scheme and connect the entire process from application to validated result. The key is to maintain traceability, competence and review control.
Does the laboratory information management system (LIMS) or quality system in use need to be replaced?
Most often not. First, it is worth assessing whether the existing system can be a reliable source of samples, results or documents, whilst a client portal, workflows and additional integrations can be built around it.
What should the first version of the project be?
One service scenario: application, scope, registration of sample or object, verification of competences and equipment, recording of results, technical review and final document.
How to ensure sample traceability?
Use one unique identifier, scanning at each transfer point, statuses, storage conditions and an immutable audit history.
How to assess the return on investment of the project?
Measure application qualification time, manual re-entry, technical review duration, repeat tests, client enquiries, equipment utilisation, service deadline and margin.
How does digitalisation fit with accreditation requirements?
It can strengthen control if the system clearly manages competences, validity of methods and equipment, impartiality, audit history and separation of roles. The process must be designed together with the quality manager.
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.