Business area digitalisation analysis

Digitalisation of higher and vocational education institutions

How to connect admissions, programmes, LMS, internships, competencies and graduate journey

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.

80/100
Biggest challenge
Student data does not form a single view
Biggest opportunity
Integrated student, programme and competence data model

An institution becomes more flexible when a programme is managed as a data-linked path of competences and the student journey.

Higher and vocational education institution operating model

Operations connect admissions, programmes, timetables, learning, placements, assessment, support and qualification issuance.

Complex programme structure

Programmes consist of modules, credits and placements.

Large number of systems

Student, LMS, library and finance systems must be aligned.

Academic autonomy

Processes must leave room for programme specificity.

Connection with the labour market

Programme value depends on real competencies.

Market and technology context

The market is moving towards modular pathways, microcredentials, digital badges and responsibly managed AI.

  • MicrocredentialsShorter and comparable learning outcomes are encouraged.
  • Skills evolutionProgrammes need to be updated more quickly.
  • Student retentionThe importance of early support is growing.
  • Generative AINew assessment and academic integrity rules are required.

Typical business process

01

Programmes and admission

Published programmes and requirements.

02

Application and decision

Documents and prior attainment are verified.

03

Study plan

The student is registered for subjects and groups.

04

Learning and practice

Lectures, assignments and practice take place.

05

Assessment and support

Achievements and support actions are recorded.

06

Qualification

Documents and competency evidence are issued.

Business area digital maturity model

0

Manual and disconnected study processes

Admissions, programme, learning, placement, support and qualification data are managed in separate systems, files and email.

1

Separate administration and content tools

Registration, documents, content, assessment and communication are managed with different tools.

2

Digital standard process

Core registration, content delivery and some communication take place digitally, but exceptions remain manual.

3

Key processes of a single programme are connected Typical current situation

In selected programmes, admission, curriculum, learning, practical training, assessment and support data are transferred automatically, but coverage is not yet consistent across the institution.

4

Data-driven study and competencies system Siektina

Programme, student progress, practical training, resource and qualification data are used for timely decisions, but not all departments and processes have reached the same maturity.

5

Adaptive and reliably automated ecosystem

Content, support and administration are individualised, and AI and competency data are managed transparently.

Key conclusion

The critical priority is to connect the entire student and competency journey.

The biggest gap is between programme, learning, internship and support data.

The first priority is one complete student process with visible progress and support.

Related digitalisation topics

Student lifecycle systemStudent support analyticsPractical training portalMicro-credentials platform
Next step

Assessing where the most data is lost along the student journey

Admissions, programmes, LMS, timetables, placements and support can be analysed.