A leading academic institution approached Marketways to test a new programme before committing facilities, faculty and support capacity. Expressions of interest did not show whether learners would enrol, complete or find the programme valuable. We connected demand and feasibility evidence to the timetable, workforce and learner services required for stable delivery.
The engagement objective
Through the initial discovery, Marketways defined the objective: connect demand, feasibility, faculty, timetable and learner support.
How Marketways translated the problem
We began with a practical question: Which programme, location, intake and price can be sustained? The first analysis used applicant, demographic, employer, competitor, price, capacity and regulation.
That evidence could not be read in isolation. Expressions of interest do not establish enrolment, completion or placement demand. Credentials, discipline, supervision and research obligations limit interchangeability.
Stated interest was not treated as enrolment, completion or value. We used each measure for the question it could support and carried the remaining uncertainty into the capacity and investment decision.
We did not judge each component by its isolated KPI. We examined how people, assets, decisions and constraints affected one another, then used the evidence to test whether an apparent improvement would strengthen the complete system or merely move cost, pressure or risk elsewhere.
How the engagement developed
The initial work on programme and campus demand feasibility exposed dependencies with faculty and skills workforce plan, timetable, room and teaching capacity, learner experience and service redesign. Treating them as separate recommendations would have left the operating trade-offs unresolved.
- Programme and campus demand feasibility: Define expansion around credible learner and employer demand.
- Faculty and skills workforce plan: Prepare recruitment and development before shortages constrain delivery.
- Timetable, room and teaching capacity: Improve access to required learning without unsustainable overload.
- Learner experience and service redesign: Make services easier to navigate and resolve.
Evidence we examined
- Applicant, demographic, employer, competitor, price, capacity and regulation.
- Portfolio, workload, skills, contracts, attrition, hiring and development.
- Curriculum, enrolment, rooms, faculty, availability, placements and rules.
- Journeys, contacts, complaints, cases, service levels and student context.
Industry conditions we accounted for
- Expressions of interest do not establish enrolment, completion or placement demand.
- Credentials, discipline, supervision and research obligations limit interchangeability.
- Specialist rooms, shared modules and clinical placements create linked constraints.
- Students encounter one institution while academic and administrative ownership is fragmented.
How our engagement contributed to business impact
We connected every method to a decision and a business measure. The organisation could assess the engagement through operating results as well as model performance.
- Programme and campus demand feasibility
- Method: Research & Evidence Collection, Statistics & Econometrics.
- Evidence: Applicant, demographic, employer, competitor, price, capacity and regulation.
- Decision supported: Define expansion around credible learner and employer demand.
- Impact measure: Enrolment quality, viable intake, capacity and employment relevance.
- Faculty and skills workforce plan
- Method: Forecasting, Risk & Optimisation, Data Foundations & Business Intelligence.
- Evidence: Portfolio, workload, skills, contracts, attrition, hiring and development.
- Decision supported: Prepare recruitment and development before shortages constrain delivery.
- Impact measure: Coverage, vacancy lead time, workload and capability readiness.
- Timetable, room and teaching capacity
- Method: Forecasting, Risk & Optimisation, Process, Workflow & Systems.
- Evidence: Curriculum, enrolment, rooms, faculty, availability, placements and rules.
- Decision supported: Improve access to required learning without unsustainable overload.
- Impact measure: Schedule feasibility, utilisation, conflicts and workload.
- Learner experience and service redesign
- Method: Process, Workflow & Systems, Market, Customer & Behavioural Analytics.
- Evidence: Journeys, contacts, complaints, cases, service levels and student context.
- Decision supported: Make services easier to navigate and resolve.
- Impact measure: Resolution, effort, repeat contact and trust.
Implementation
The engagement was structured as pre-investment through first cohorts. We connected the analysis to the decisions, operating constraints and measures that the organisation would continue to use.
How success was assessed
The overall assessment considered viable intake, quality, capacity and learner outcome. The supporting measures included:
- Enrolment quality, viable intake, capacity and employment relevance.
- Coverage, vacancy lead time, workload and capability readiness.
- Schedule feasibility, utilisation, conflicts and workload.
- Resolution, effort, repeat contact and trust.
Services and methods used
Services: Business Feasibility Study, Market Research & Demand Assessment, Workforce Planning & Capacity, Workforce Performance & Capability Assessment, Operational Performance Diagnostic, Customer Satisfaction & Experience Research, Process & Workflow Analysis & Redesign.
Methods: Research & Evidence Collection, Statistics & Econometrics, Forecasting, Risk & Optimisation, Data Foundations & Business Intelligence, Process, Workflow & Systems, Market, Customer & Behavioural Analytics.