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Chris Collins
Manager, MIS Projects & Benefits Realisation
ANZ
Chris Collins Seasoned analyst – over 15 years
in analytics and 10 years in
banking
Experienced across analytics,
reporting, applications
development, process
improvement, solutions
architecture and enterprise
analytics
Myers Briggs: ENFP
Avid tweeter
…practical numbers geek!
Topics covered
What is, and why have, an enterprise
analytics strategy
How to determine what your strategy
looks like
Areas of consideration for your strategy
How to gain support and execute the
strategy
An enterprise analytics strategy is a
change roadmap that underpins your
business and advances the organisation
beyond ‘coincidental’ success.
It identifies what you need to change and
how you should change it.
What is, and why have, an enterprise
analytics strategy
1. Set the foundations
Organise a great team Across all business areas
Across all levels of seniority
Treat it like a programme of projects
That can instil a sense of purpose
Can influence others
Decide on an execution/delivery model Flexible enough to work on technology, people and process
change
Is measurable and repeatable
Copes with ambiguity and abstraction
Tech
ProcessPeople
Business need
People
Process
Regulatory considerations
Cross-industry considerations
Growth
Retention & loyalty
Corporate branding
Application provision
Tools
Data
Touch points
Mobility
Penetration
Core TechnologyServices
GovernanceDevice
management
Security,, Access & Risk
Services and Integration
Development processes
2. Consider your needBusiness is responsible for the delivery of results
and so must drive the discussion on capability.
3. Quantify the value of change:
Sell the dream and gain funding
Recognise the value of analytics. Identify
improvements to existing and new sources of
revenue.
Gain awareness of emerging growth opportunities
Create efficiencies through the organisation
Capitalise opportunity into tangible values - $$$
Define the implementation roadmap that
demonstrates ROI
4. Deliver excellently
Plan – Communicate – Refine – Execute – Monitor – Optimise
Align the strategy with implementation/execution roadmap(s)
Own the issues
Empower your staff
Maintain progress
Gain trust & commitment
Communicate & Collaborate
Feedback
Acceptance and adoption of the strategy and its deliverables is
critical to ensuring success
Benchmark Develop Integrate MeasureAnalyse Deploy Adopt
Technology Data Process Skills
Unstructured Web/desktop tools Excel/CSV Undefined, not
shared
Associated to person
only
Structured Common
desktop/web tools
Excel/CSV on
shared drives
Weakly defined,
locally shared
Skills sometimes re-
used
Team Common
server/client
Data marts on
shared drives
Easy to record are
strongly defined;
others not so much
Skills defined by
team. Some career
progression
available
Department Service orientated
environments
Cross-function data
marts
Processes generally
well defined,
operational
refinement effective
Skills becoming
softer; less reliance
on technical
knowledge
Enterprise Common enterprise
SOA
Data exists in
multiple parts and
sharing BAU
Well defined and
interactions and
impacts known
‘Generalism is the
new specialism’.
Person tool agnostic,
differentiated by
business
need/outcome
Current State
Benchmark Develop Integrate MeasureAnalyse Deploy Adopt
Technology BI
Reporting
Delivery
Modelling
Delivery
Analytics
Delivery
Research
Delivery
environment
Benchmark Develop Integrate MeasureAnalyse Deploy Adopt
Modelling
Environment
Automation
environment
Visualisation environment
Information
Environment
Information sharing protocols
Future State
Benchmark Develop Integrate MeasureAnalyse Deploy Adopt
Integrate Separate
Technology - Increased complexity (for now and
future)
- Wider spectrum of failure
- Slower implementation time
- Acceptance criteria harder to define
- Likely will be part of a larger chain of
dependencies
- Increased need for specialist teams
- Increased risk of poor vendor support
- Accountability to ‘get it right’
- Likely need to update ‘incidental’ systems,
such as O/S, storage, networks etc.
- Risk of disruption to existing systems
Business - Increased implementation cost
- Less freedom to adapt technologies
- Risk of more items being ‘out of
scope’
- Accountability on Technology to ‘get it right’
- Harder to reconcile between old/new systems
- Acceptance testing more complex
- Handling of legacy data
- Harder governance
The benefits and implications for each aspect should be discussed and
outcome decided by Business and sponsors
Benchmark Develop Integrate MeasureAnalyse Deploy Adopt
Identified change
What was to change
Change process
How did you get to the objective state
Support process
How you manage the transition
Outcome received
The results you achieved
Demonstrate the benefit of the change the business has
undertaken. Prove it was worth it!
Enterprise Analytics Strategy –
Recap
1. Assemble a great team
2. Decide upon a repeatable delivery model
3. Consider your business requirements and any subsequent infrastructure need
4. Define the value upfront
5. Create and tell a great story
6. Ensure exceptional delivery
7. Manage the change
8. Confirm the value
Further reading
