Admissions Review (2023–2024)

Crushing a 4,400+ application backlog with automation + analytics

Client

Murdoch University (Admissions and Information Technology Services)

Delivery model

A cross-functional fusion team spanning Admissions, CRM, Integration, Advanced Analytics, and Student Systems, working in short delivery cycles to stabilise performance fast and then embed sustainable improvements.

Timeframe

Late 2023 to mid-2024, with rapid stabilisation followed by scalable uplift.

Lane8 role

Bart Kuiper (Lane8 Consulting), working in partnership with Elaine Nagajek (Lane8 Consulting), led the CRM-related components, working alongside Murdoch University delivery teams as part of the Admissions Review fusion delivery.

Recognition

This work was recognised as a 2024 CAUDIT Award winner in the Operational Excellence category (Admissions Review Fusion Delivery, Murdoch University).

The challenge: a crisis-sized backlog that threatened revenue and experience

By November 2023, Murdoch University faced an admissions processing backlog large enough to become an executive-level operational risk. More than 4,500 applications were awaiting processing and the average time to process an application had blown out to over a month.

This was not a simple “more applications than usual” problem. The backlog was a symptom of a workflow that forced skilled Admissions Officers into repetitive, low-value steps - opening every application, checking basic completeness, chasing missing information, and manually determining whether an application was even assessable.

The backlog profile made the risk sharper. Over 4,400 applications were in the queue and 88% were international. The initial assessment stage was averaging 40 days, meaning applicants waited far too long to learn whether their submission was complete or what additional evidence was required.

From an applicant’s perspective, this delay undermined confidence at the exact moment intent is highest. From a university perspective, it constrained conversion and created reputational harm. The Vice Chancellor’s testimonial is direct about the consequences - Murdoch was missing opportunities to capitalise on prospective students keen to study, and the experience for those who endured the process fell below the university’s own expectations.

Murdoch needed speed, but also needed control. Clearing a backlog once is not the same as preventing the next one. The real requirement was a scalable operating model that could handle peaks without consuming ever more staff effort.

The approach: from manual triage to an automated operating model

Murdoch launched an Admissions Review initiative with a simple objective - optimise triage and assessment so processing times reduced dramatically and the backlog could be eliminated. The target was explicit: reduce overall processing time from 40 days to 7 days across triage, assessment and offer stages.

A “fusion team” built around the work, not the org chart

Instead of treating the issue as a single system upgrade, Murdoch formed a blended delivery team bringing together the capabilities needed to solve the end-to-end problem:

• Admissions Product Owner and subject matter experts
• CRM delivery capability
• Integration delivery capability
• Advanced analytics and reporting capability
• Student systems capability

The team ran two-week sprints, delivering enhancements iteratively to maximise value in the shortest timeframe. This mattered because the backlog was a moving target - every day spent on prolonged design cycles would have been paid for in applicant churn and staff burnout.

The core insight: reduce effort by removing waste at the front door

The backlog had a hidden multiplier - a significant portion of the work was avoidable. Many submissions were incomplete or ineligible, yet the operating model required Admissions Officers to manually open and review each one to determine next steps.

Murdoch’s strategy focused on three linked capabilities that changed the cost curve:

1. Automated triage - identify and divert low-quality or not-ready submissions without requiring manual handling.
2. Automated missing-document checks - detect missing mandatory documents immediately and notify applicants with clear next actions, while keeping incomplete applications out of the assessment queue.
3. Operational reporting and analytics - provide visibility of volumes, exceptions and throughput so leaders could actively manage flow and sustain performance over time.

This approach was deliberately pragmatic. It aimed to deliver measurable outcomes without waiting for a full platform replacement, and without placing additional burden on already stretched operational teams.

What was delivered: automation, rules and rapid feedback loops

1) Automated completeness screening and missing mandatory document nudges

A decisive improvement was transforming missing-document checking from a manual process into an automated one.

In the first month alone, 761 new applications were screened. Of these, 182 applications - 23.9% - were missing at least one mandatory document. Under the old model, each of these would have required an Admissions Officer to open the application, inspect the attachment set, identify what was missing, and then send follow-up communication. That work would then repeat if the applicant responded with incomplete information or attached the wrong file.

The automated process changed the loop:

• Missing mandatory documents were detected automatically.
• Applicants received automated, immediate communication detailing what was missing.
• Applications were set aside until they became assessment-ready, rather than clogging the assessment queue.

This removed friction for both applicants and staff. Applicants received fast, unambiguous next steps. Admissions staff stopped wasting time on checking and chasing.

The time saving was also quantified early. The automated missing-document process saved 45.5 hours in the first month, forecasting to 546 hours per year. That translates to meaningful capacity returned to the business without adding headcount - capacity that could be redirected to high-value assessment and applicant support.

2) A document rules capability to industrialise decisioning

Automation is only scalable if it is maintainable. Hard-coded logic becomes brittle and slow to adjust when policy changes, when different cohorts require different documents, or when programs adjust their requirements.

To address this, Murdoch implemented a document rules system that automated assessment of applications against mandatory document requirements, supported by a maintainable rules repository (using Microsoft Dataverse) and automated nudges to applicants where documents were missing.

This is an important shift in operating maturity. It moves the university from “tribal knowledge and manual checking” to “rules-driven processing”, and it creates a sustainable pathway for continuous improvement because rule changes can be governed and applied without reworking the entire workflow.

3) Automated triage to protect Admissions Officer capacity

The Admissions Review work was intentionally designed to stop the system from spending expert time on low-quality work. The goal was to allow Admissions Officers to focus exclusively on eligible, complete applications.

This kind of triage improvement is easy to underestimate, but it is one of the most effective levers for backlog reduction. When the process requires manual handling of every item, even a small increase in volume creates a compounding queue. By automating triage and separating not-ready applications from assessable ones, throughput improves without simply “working harder”.

4) Reporting and analytics that made performance manageable

Backlog elimination is not sustainable without operational visibility. Even strong process improvements can drift if leaders cannot see where volume is building, which document types are causing friction, or whether particular cohorts are disproportionately affected.

The fusion team embedded reporting and analytics as part of the solution, improving transparency and enabling leaders to manage flow proactively rather than reactively.

This capability helped shift the model from crisis response to a repeatable management rhythm - understanding intake, understanding readiness, and controlling throughput.

5) Faster applicant feedback that increased momentum in the pipeline

One of the most practical benefits of automation was speed of response to applicants.

The solution enabled applicants to receive missing-document requests within two hours of submission in cases where mandatory documents were absent. The executive testimonial describes a similar improvement, noting that initial application reviews and requests for additional information were handled automatically, enabling responses within 24 hours.

Regardless of the specific window (two hours for targeted missing-doc nudges versus a broader 24-hour response standard), the outcome was clear - applicants received timely communication, which reduced uncertainty and improved the likelihood they completed their submissions quickly.

Results: from 4,500+ backlog to under 200 and processing time slashed

The outcomes were significant, concrete, and visible at the executive level.

Backlog reduction

The Vice Chancellor stated the backlog was reduced from over 4,500 to under 200 over a small number of months.

This is the kind of operational turnaround that materially reduces risk. It restores service levels, protects intake, and relieves staff pressure.

Processing time reduction

The program’s explicit target was to reduce processing time from 40 days to 7 days. The initiative reports that processing times were slashed from 40 days to 7 days through the delivered changes.

That shift is not incremental - it is a transformation in operating performance. It changes applicant experience, reduces churn, and supports stronger enrolment conversion in competitive markets.

Efficiency gains and capacity reclaimed

Beyond the headline backlog reduction, the work returned measurable staff capacity:

• 45.5 hours saved in the first month from automated missing-document checking, with a forecast of 546 hours saved per year.

The Chief Experience Officer summarised the impact in operational terms - by radically streamlining processes, Murdoch could give students a better experience, with Admissions Officers able to focus on processing complete applications and providing value-add human support.

Applicant experience uplift

The executive narrative emphasises that applicants received automated responses where submissions required additional information, improving the experience and setting clearer expectations.

This matters because admissions is a defining moment in the student lifecycle - it is one of the first high-stakes service experiences a student has with a university. Improving responsiveness and clarity at this stage has downstream benefits for trust, satisfaction, and ultimately enrolment.

Why it worked: the decisions that changed the curve

1) Removing waste at the front of the process

The first month metric tells the story. If 23.9% of new applications are missing mandatory documents, and every one requires manual handling, the system will accumulate debt.
Automated checks and nudges broke that compounding effect.

2) Separating “not ready” from “ready to assess”

By setting aside incomplete applications until they were assessment-ready, the program protected throughput and reduced repeated touches by staff.
This is a classic lean move applied in a digital context - reduce rework and keep the assessment stage flowing.

3) Agile delivery with measurable outcomes

Two-week sprints allowed Murdoch to deliver working improvements quickly, learn from real operational behaviour, and prioritise what mattered most.
This rhythm is critical in operational recovery because it reduces time-to-value and avoids over-engineering.

4) Making the solution maintainable through rules

The document rules system (supported through Dataverse) enabled mandatory document requirements to be managed as a governed capability, rather than buried in process workarounds.
That is what makes the shift scalable - the university can adapt without rebuilding from scratch.

5) Building operational visibility into the solution

Analytics and reporting were embedded, enabling leaders to manage performance and keep the improvements sustainable.
In practice, this turns “a project” into “an operating model”.

The Lane8 angle: crisis recovery without a full platform replacement

This case demonstrates how a university can achieve executive-level operational outcomes by combining process redesign, automation, and analytics - without relying on a multi-year platform replacement program.

The improvement came from:

• Automating the steps that created the most waste (manual triage and manual document checking).
• Introducing a maintainable rules capability for mandatory document requirements.
• Delivering through a cross-functional fusion team that aligned Admissions outcomes with CRM, integration and analytics delivery.

The result was a shift from crisis backlog to a scalable operating model - a model where applicants receive faster guidance, staff effort is concentrated on value-adding decisions, and leaders have the reporting to prevent a return to backlog conditions.

Key outcomes at a glance

• Backlog reduced from 4,500+ to under 200 within months.
• Processing time reduced from 40 days to 7 days.
• Automated missing-doc screening found 23.9% of new applications missing mandatory documents (182 of 761 in the first month).
• Efficiency gain quantified at 45.5 hours saved in the first month, forecasting 546 hours per year.
• Applicants received missing-document requests within two hours for mandatory document gaps (and within 24 hours as described in executive testimonial for initial requests).

If you want, I can also tighten the opening section further so it reads less like a formal submission and more like a Lane8-style narrative, while keeping all the same metrics and proof points.

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