By working with the other teams, you can help improve student and staff experiences by improving retention, free up staff and room resource constraints, help create a consistent student experience, and use that to drive the next level of understanding around how to improve the learning content and student experience further. Presenter: Matthew Rudd, Director Business Analytics, Swinburne University of Technology

1. P U B L I C S E C T O R
S U M M I T
Canberra, ACT

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P U B L I C S E C T O R
S U M M I T
Deriving Value from Data Analytics:
Perspectives from Swinburne's Journey
Matthew Rudd
Director, Business Analytics
Swinburne University of Technology

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P U B L I C S E C T O R
S U M M I T
Harnessing the capabilities of a unique team
• Centrally located team
supporting the whole
university
• Deep technical expertise
• AWS and Tableau certified
Swinburne
Information Hub
(SIH)
Student One
Government
submissions
Executive reporting
Management reporting
Exploratory reporting
Dynamic ad-hoc
Student One – Operational
reporting
Government
reporting
Aggregated
Transactional
Analytical
Analytics University Wide
analytical models

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P U B L I C S E C T O R
S U M M I T
What was our starting point?
• Issues across the organisation
• Multiple data views creating confusion and
conflict
• No single point of reference for the university
• Lack of trust in reporting produced
• Increasing need to be faster
• Issues within business analytics
• No data repository, leveraging replicated data
files
• Requests unmanageable, unable to keep up
• Between a dumping ground and a graveyard
• Tech-specific skill set

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P U B L I C S E C T O R
S U M M I T
Proof of concept to enterprise repository
• Driven by speed and cost
we ran a PoC on AWS
• AWS provides the ability
to readily expand in
terms of capacity and
services
• We move data from
Amazon S3 to Amazon
Redshift and model,
build data sets, develop
dashboards in Tableau
and manage/train users
AWS - ap-southeast-2 (Asia Pacific (Sydney))
VPC contents
VPC subnet
Swinburne data center
Internet
gateway
virtual private
gateway
router
VPN
connection
customer
gateway
Amazon
S3
client
Internal
Sources
Internet
gateway ESB
firewall
encrypted
data
encrypted
data
SSL
Connection
SSL
Connection
Amazon
Redshift – Dev/
UAT
Amazon
Redshift - Prod
Amazon EMR

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P U B L I C S E C T O R
S U M M I T
Data standards and data quality
• Took on data standards and
data quality first
• Simple form and publish approach –
wiki for access
• Working group for business
representation and ran
forums for updates and as
motivation discussions
• Volunteers to own data sets
• Ran forums for updates and as
motivation discussions
• Simple and achievable for a
small team

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P U B L I C S E C T O R
S U M M I T
Change the what, how, and why?
• Re-launched and put
ourselves out there
• Created a brand –
DAPPER
• Deployed a host of
techniques to engage
• Engaged executives first
– 1:1 training, buy in,
and quotes

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P U B L I C S E C T O R
S U M M I T
DAPPER is utilised across the university…
Lead
Certification
Dapster
Dynamic
Designer
Enterprise
Dashboards
Download
Data sets
BYO data to
SIH
Views Filters
Simple reports
Use Intro
Save as
Publish
to folder
Web edit
Desktop
Contribute
Responsibility
Publish on
DAPPER
Building
New
capability
New
levels
of
access
&
capability

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P U B L I C S E C T O R
S U M M I T
…with information consumed in many ways
Navigation –
Landing Page
Scorecards –
Swinburne on a Page
Analysis Dashboards –
Management Reporting
Filter Based Reports –
Exploratory Reports
Build Templates –
Web Edit Functionality

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P U B L I C S E C T O R
S U M M I T
Value of sharing insights interactively
• Pre-Intake Tracking (PIT)
• Previously took enormous effort to
manually update and email to
participants
• Now discussed in interactive online
meetings by sharing filtered views
that are refreshed daily, in a
restricted and secure fashion

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P U B L I C S E C T O R
S U M M I T
Value of data democratisation
• HEIMS reports
bring together
benchmarked
enrolments
• No prior
reporting
available
• The business
sourced information
manually c/o
publications and
websites with no
enrolment counts

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P U B L I C S E C T O R
S U M M I T
Value of delivery efficiency
• Previously took
>1wk from raw QILT
data to Tableau
reports
• Now takes ~30 min to
upload data that’s
available immediately
• Austrade data
previously
significantly
underutilised
• Was delivered in excel
format making it hard to
work with

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P U B L I C S E C T O R
S U M M I T
Attrition propensity modelling
Student
life
Video and
Echo 360
CRM
(B2C)
Canvas LMS
and Blackboard
transition?
Surveys
GOS, SES,
SFS, Checkin
Commute
Intervention
cohort 1
Intervention
cohort 2
Intervention
cohort 3
Contact and record
outcomes
Statistical appraisal of
efficacy
Report outcomes and pass
embed learnings into
future interventions
Reinforcement
learning
Existing attrition propensity model Student-on-a-page (incl. attrition risk) in CRM Leverage audience/campaign in DXP
AND/OR
campaigns
direct from
CRM
Campaigns
routed via
DXP
New data will greatly enrich modelling accuracy

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P U B L I C S E C T O R
S U M M I T
Forecasting and load planning
99.58%
99.41%
99.21%
99.58%
99.49%
DecisionTreeRegressor
RandomForestRegressor
GradientBoostingRegressor
ExtraTreeRegressor
Ensemble

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P U B L I C S E C T O R
S U M M I T
Higher education resource modelling
𝑚𝑖𝑛 ෍
𝑖
𝑛
𝑥𝑖ℎ𝑖𝑐𝑖𝑤𝑖
Constraint optimisation (cost function)
𝑥𝑖 is number of unallocated class instances
ℎ𝑖 is duration of unallocated class
𝑐𝑖 is hourly cost of sessional staff for the class activity
𝑤𝑖 is the number of weeks the class runs
ABC10001
Tutorial 1/01
Monday
10:30 AM
AKD60001
Tutorial 1/01
Wednesday
9:30 AM
XBC30020
Lab 1/03
Friday
9:30 AM
ABC10001
Lecture 1/01
Tuesday
2:30 PM
XBC30020
Lab 1/02
Thursday
12:30 PM
AKD10001
Lecture 1/01
Friday
2:30 PM
XBC30020
Lab 1/01
Monday
5:30 PM
ABC10001
Tutorial 1/02
Tuesday
4:30 PM
ABC10001
Tutorial 1/03
Wednesday
3:30 PM
ABC10001
Tutorial 1/04
Thursday
4:30 PM
XBC30020
Lecture /01
Monday
2:30 PM
AKD60001
Tutorial 1/02
Wednesday
4:30 PM
1
2
3
4
5
6
7
8
9
10
11
12
Timetable
10 4
5 6
1 2
3 7 8 9
11 12
XXX60009 – Tutorial1
…
AHC20001 – Lab1
AHC10004 – Tutorial1
ABC10001 – Tutorial1
22
22
22 20 18
22
30
24 28
Enrolment headcount : 104
Max class size : 32
Existing 5 instances per week
Proposed 4 instances per week
Duration : 2 hours
Teaching period :12 weeks
Potentially free up 24 delivery hours
4
5 6
1 2 3
7 8
9 10
11 12

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P U B L I C S E C T O R
S U M M I T
Forecast labour delivery margin
• Unit
enrolment
projections
from forecast
(EFTSL and $)
• Optimised
academic and
sessional
resources
using 2018
instances
• Equals unit
labour
delivery

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P U B L I C S E C T O R
S U M M I T
HE resourcing budget initiative
• EBA
• Research allocation
• Capability matrix
• Salaries & sessional rates
• Room/capacity
• Instances (planned)
• FOE rates & pricing
• NSE EFTSL @
nFOE
• End-to-end
modelling
capability
• Adjustments to
EFTSL trigger
recalculation
• Turn around ~7
minutes
• Removes
bottlenecks, with
users able to
load and access
outputs directly

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P U B L I C S E C T O R
S U M M I T
Realising the value – estimated to exceed $3m
1,450
925
2,375h
month
99,130h
Team
51,840h
year
Survey of 230 users before
we developed DAPPER
Extrapolating effort per annum
across 800+ Dapsters less the
total resources in our team
Data prep
Reporting
~6% month

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P U B L I C S E C T O R
S U M M I T
Consolidated governed product datasets
• Developed to
uniformly
support
reporting,
accreditation,
and planning
requirements
• Bringing
together >40
metrics from 12
internal and
external data
sources
spanning ~8m
rows
Example only

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P U B L I C S E C T O R
S U M M I T
Canvas LMS reporting and learning analytics
• Assignment
schedule
planning and
weighting
analytics
• Provides
opportunities to
optimise resourcing
and balance
academic demands
on students,
improving the
experience for both

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P U B L I C S E C T O R
S U M M I T
The data experience
Bootcamp Internal Projects Internal Projects
Paid Industry
Experience
Part-time employment
Tableau
Certification
AWS
Certification
Attend Tech
Conference
Client
Presentations
“Working externally has enabled me to develop and
enhance the skills I have learnt during my time in
higher education“
“After a year of practical work
experience, I better understand
the direction I want my career to
take.”
“Fast, fun learning.”
“A great way to recognise
the importance of soft skills
and areas for
development.”
AWS CIC
or
Public Sector
Challenges
ENGAGEMENT
PERSONAL
BUSINESS
DESIGN
TECHNOLOGY
AWS
Medical Insurance
Company
Energy
Company

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P U B L I C S E C T O R
S U M M I T
Cloud innovation centre powered by AWS

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P U B L I C S E C T O R
S U M M I T
Swinburne data for social good
Digital health systems to
improve health literacy and
support across diverse
communities
HEALTH
Working with communities and
government to address Society
4.0 challenges
SOCIAL INNOVATION
Developing citizen-centric cities
through digital inclusion
SMART CITIES
UNDERPINNED BY
DATA SCIENCE