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The chief data officer management hanbook - Coggle Diagram
The chief data officer management hanbook
1. Understand
your organisation
Implicit
data governance
models
Centralistic :check:
Assuming the head office knows best
Democratic
Trying to make most people happy
Liberal
Giving total freedom to everybody
Technocratic :check:
Expecting IT to solve all the problems
Anarchistic
Denying the need for data governance
Behavorial patterns
in data matters
"Data is an IT task" :check:
IT = handling of data, not data
Importance of the
mandate
(not IT only)
A data office
needs to be a distinct team
Neutrality
is vital
"We can focus on Analytics"
data <> analytics
"It's digitalisation"
digitalisation requires proper data, but it's not the only one
Paralysis by analysis
"Digital natives know how to do it"
nope - they know how to
use
it
"Our business functions can do data on their own" :check:
=> silo thinking
"It is all good"
"Tidy up and tick the box" :explode:
Data is not seen as an asset :check:
Tactical data handing :check:
Data is considered as a competitor
2. Aspects of effective data management
Two main gaps
lack of collaboration
lack of business ownership
Subsidiarity
Data managed centrally by an empowered team?
data management left yo everybody across the organisation?
=>
none
of the two extremes :check:
Centralize data responsibilities where it makes sense
Any centralisation requires good reasons
Leave the rest to the "field"
Any delegation must involve trust and support
Business orientation
Is there a problem / an opportunity / an innovation?
Seek the dialog
hypothesis about benefits
to validate with business functions
Develop a product mindset
Product owner, not project manager
Data management is everybody's job
not an IT job
do not start with technology
it's about building bridges between business & IT
based on solid understanding of both sides
To build
Commercial orientation
Collaboration
Data Office
Clear data ownership
A decision and escalation process
A data stewardship network
Motivation
Cross functionality
Focus on organisation-wide targets, not on departmental-wide targets
Incentivize collaboration
Make the focus part of your organisation culture
Change management
Data literacy
Help employees understand data
Share knowledge
Share data
3. The data supply chain
Manage data sources
Risks
Duplicate data acquisition
Inconsistent data
Ambiguity of data
Risk of bias
To do
central function responsible for all external sources
task of the data office
Validate data on entry
synchronised with internal data (including history)
anonymised when necessary
tagged with meta data
Classify data
Documented data model
Manage data quality
Do data housekeeping
manage data retention
regular cleaning
Curate data
Centralise data storage
Centralise data logic
Have user understand the data
Give access to data
Understand and document data transformation
Document data usage
Provision of information to user
Data catalog
Web service directory
Intranet site
Use data
operations
KPIs
analytics
RPA
audit support
testing
4. Data Vision, Mission, and Strategy
Vision
Objectives
Role of data in your related business model?
What does the organisation wants to achieve through data?
What is the data handling supposed to look like in a few years from now?
What does the vision should
focus
on?
Mission
Discribes concrete targets
Critical aspects of an effective mission statement
Measurable
Comprehensive list of concrete targets
Board endorsement
Examples
define centrally governed
data handling standards
introduce cross-functional
MDM
, based on
single source of truth
ensure good
data quality
through measurement and improvement initiatives
work with
business people
to turn data into information
have all of this supported by the right
toolset
implement adequate
ethical standards
in dealing with data
train
and
connect
all entities in data matters
Strategy