Presented at ADMA Data Week 2020

1. KATE CARUTHERS
Chief Data & Insights Officer
UNSW Sydney
Aug 2020
DAY 4: MODELLING HIGHER
EDUCATIONS FUTURE

2. Data is the world’s
most valuable resource
› COVID is forcing transformation and we
see it everywhere
› Data underpins everything to do with
these transformations
› Data is the new oil but unlike oil,
data is much more variable, it is produced
at vast quantities and can
be transported relatively easily
and cheaply
› The challenge is in the processing of it
01
Just do it now
› Digital transformation takes time
› Organisations may make it their top
priority and plan for it but now they
actually have to implement it
› Anyone who doesn’t is literally
going to die
› The challenge is that most
organisations have not moved quickly
enough
02
Finding our way
through the noise
› Today data is counted in zettabytes
and exabytes
› The trick will be working out what can be
turned into useful information
› Finding the significant and
transformational data can be expensive
› The challenge is that in selecting one data
set over another is not a neutral decision.
There’s a need to engage stakeholders
03
What is ethical?
› AI is being used to drive customer-
centric interactions
› Tests have shown that ‘anxious’
language generates more
conversations (and sales) than ‘safety’
language
› What is the ethical path for AI and
machine learning to take in driving
business outcomes
04
DATA DRIVING DIGITAL TRANSFORMATION
IN THESE TIMES OF CHANGE

3. LESSONS LEARNED
INTEGRATION
MATTERS
› Building capability is fundamental. Integration between systems
will streamline the process
› Get people out of silos. Difficult at the best of times, with COVID
it’s even harder
› Need to get analytics capabilities across the organisation. Don’t
bottle them up. Bake metrics into everything you do
› Budget constraints can help. People are less scattered, find the
importance and focus
› Digital Transformation – conscious or unconscious, seeing the
levers you have that can help make it happen
› How can we apply the learnings from COVID and apply them
when we get back into the office?

4. REQUIREMENTS OF
DATA CULTURE
1. AI and ML
To start to automate decisions
2. DATA SCIENCE
The nugget of insight that can drive interesting decisions
3. DATA ANALYTICS
Data warehousing and mobility
4. DATA OPS
Processes and tools to manage your data properly
5. DATA GOVERNANCE
What you have and how you can protect it
6. DATA INFRASTRUCTURE
Cloud based

5. REQUIREMENTS OF
DATA CULTURE
SYSTEM OF RECORDS
Where you store customer records
SYSTEMS OF IMPORTANCE
That sit on top of this
SYSTEMS OF ENGAGEMENT
On top of that
SYSTEMS OF THINGS
All the IOT devices starting to prevail
CUSTOMER
EXPERIENCE

6. REFERENCES
https://www.gartner.com/document/3891248?ref=solrAll&refval=237925299
https://blogs.cisco.com/sp/the-zettabyte-era-officially-begins-how-much-is-that
https://www.smartinsights.com/managing-digital-marketing/marketing-
innovation/6-essential-marketing-trends-for-2020/
https://www.enterpriseirregulars.com/156284/six-areas-where-ai-is-improving-
customer-experiences/