Sustainable Data Governance

The First Step in Information Management
www.firstsanfranciscopartners.com
Sustainable
Data
Governance:

Adding
Value
for
the
Long
Term

Kelle
O’Neal

kelle@ﬁrstsanfranciscopartners.com

415-‐425-‐9661

@1stsanfrancisco

4
Why
We’re
Here

Purpose:

Understand
criQcal
success
factors
for
sustainability
of
a
Data

Governance
Discipline

Outcome:

§  Understanding
Data
Governance
FoundaQon

§  Understanding
how
to
make
governance
a
core
competency

§  PracQcal
knowledge
that
can
be
immediately
implemented

pg 2Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

4
Agenda

§ Level
SeTng
-‐
FSFP’s
perspecQve
on
Data
Governance

§ Obstacles
&
Challenges
to
Sustainability

§ CreaQng
Sustainable
Data
Governance

−  OrganizaQon

−  Alignment

−  Metrics
&
Measurements

−  CommunicaQon

−  Embedding
Governance

§ Ensuring
success


4
Level
SeTng


4
Data
Governance
DeﬁniQon

§  Data
Governance
is
the
organizing

framework
for
establishing
strategy,

objecQves
and
policy
for
eﬀecQvely

managing
corporate
data.

§  It
consists
of
the
processes,
policies,

organizaQon
and
technologies
required
to

manage
and
ensure
the
availability,

usability,
integrity,
consistency,
audit

ability
and
security
of
your
data.

CommunicaQon
&

Metrics

Data

Strategy

Data
Policies
and

Processes

Data

Standards

and

Modeling

A Data Governance Program consists of the
inter-workings of strategy, standards,
policies and communication.


4
Data
Governance
Framework

pg 6
•  Vision & Mission
•  Objectives & Goals
•  Alignment with Corporate
Objectives
•  Alignment with Business
Strategy
•  Guiding Principles
•  Statistics and Analysis
•  Tracking of progress
•  Monitoring of issues
•  Continuous Improvement
•  Score-carding
•  Policies & Rules
•  Processes
•  Controls
•  Data Standards & Definitions
•  Metadata, Taxonomy,
Cataloging, and Classification
•  Operating Model
•  Arbiters & Escalation points
•  Data Governance
Organization Members
•  Roles and Responsibilities
•  Data Ownership &
Accountability
•  Collaboration & Information
Life Cycle Tools
•  Data Mastering & Sharing
•  Data Architecture & Security
•  Data Quality & Stewardship
Workflow
•  Metadata Repository
•  Communication Plan
•  Mass Communication
•  Individual Updates
•  Mechanisms
•  Training Strategy
•  Business Impact & Readiness
•  IT Operations & Readiness
•  Training & Awareness
•  Stakeholder Management & Communication
•  Defining Ownership & Accountability
Change
Management
Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

4

Develop
and
execute
architectures,
policies
and
procedures
to
manage
the
full
data
lifecycle

Enterprise
Data
Management

Enterprise
Data
Management

Ensure
data
is
available,
accurate,
complete
and
secure

Data
Quality

Management

Data
Architecture

Data

RetenQon/Archiving

Master
Data

Management

Big
Data

Management

Metadata

Management

Reference
Data

Management

Privacy/Security

DATA GOVERNANCE

4
The
Big
Picture:
EIM
Framework

Provides
a
holisQc
view
of
data
in
order
to
manage
data
as
a
corporate
asset

Enterprise
InformaQon
Management

InformaQon
Strategy

Architecture
and
Technology
Enablement

Content
Delivery

Business
Intelligence

and
Performance

Management

Data
Management

InformaQon
Asset

Management

GOVERNANCE
ORGANIZATIONAL ALIGNMENT
Content
Management


4
Obstacles
&
Challenges


4
The
landscape
is
changing
…

pg 10Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential pg 10Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

4
Obstacles

§ CompeQng
prioriQes
and
lack
of
resources

§ Data
Ownership
and
other
territorial
issues

§ Lack
of
cross-‐business
unit
coordinaQon

§ Lack
of
data
governance
understanding

§ Resistance
to
change
or
transformaQon

§ Lack
of
execuQve
sponsorship
and
buy-‐in

§ Resistance
to
accountability

§ Lack
of
business
jusQﬁcaQon

§ Inexperience
with
cross-‐funcQonal
iniQaQves

§ Change
of
personnel


4
Obstacles


4
Why
is
Data
Governance
Important?

Internal
pressures:

§ Desire
to
understand
customer
at

any
Qme
from
any
channel

§ Data
Quality
issues
are
persistent

§ Balance
of
old
mainframe
systems

with
new
technologies

§ Movement
to
the
cloud
and
losing

control
of
data

§ Data
Volumes
are
increasing

§ Mobile
apps
enabling
data
to
be

created
and
accessed
anywhere

§ Project
oriented
approach
to

addressing
issues/opportuniQes

External
pressures:

§ Greater
amounts
of
new
regulaQons

§ Increasing
Customer
Demands
–
my

informaQon
anywhere
at
any
Qme

§ Technology
and
market
changes

outpacing
ability
to
respond

Ensures
the
right
people
are
involved
in

determining
standards,
usage
and
integra4on

of
data
across
projects,
subject
areas
and
lines

of
business


4
Establishing
the
OrganizaQon


4
Don’t
base
your
program
on
speciﬁc
individuals


4
Process

• How
are
decisions

made?

• Who
makes
them?

• How
are

Commihee’s
used?

Culture

• Centralized

• Decentralized

• Hybrid

OperaQng

Model
• Data
Governance

Owner

• SME’s

• Leadership

People


4
OperaQng
Model

§ Outlines
how
Data
Governance
will
operate

§ Forms
basis
for
the
Data
Governance
organizaQonal
structure
–

but
isn’t
an
org
chart

§ Ensures
proper
oversight,
escalaQon
and
decision
making

§ Ensures
the
right
people
are
involved
in
determining
standards,

usage
and
integraQon
of
data
across
projects,
subject
areas
and

lines
of
business

§ Creates
the
infrastructure
for
accountability
and
ownership

pg 17
Wikipedia:
An
OperaQng
Model
describes
the
necessary
level
of
business

process
integraQon
and
data
standardizaQon
in
the
business
and
among

trading
partners
and
guides
the
underlying
Business
and
Technical

Architecture
to
eﬀecQvely
and
eﬃciently
realize
its
Business
Model.
The

process
of
OperaQng
Model
design
is
also
part
of
business
strategy.


4
Types
of
OperaQng
Models

§ Centralized

−  Similar
to
a
top
down
project
model

§ Decentralized

−  Flat
structure,
more
virtual/grassroots
in
nature

§ Hybrid
/
Federated


4
Pros:

• Formal
Data
Governance
execuQve

posiQon

• Data
Governance
Steering

Commihee
reports
directly
to

execuQve

• Data
Czar/Lead
–
one
person
at
the

top;
easier
decision
making

• One
place
to
stop
and
shop

• Easier
to
manage
by
data
type

Cons:

• Large
OrganizaQonal
Impact

• New
roles
will
most
likely
require

Human
Resources
approval

• Formal
separaQon
of
business
and

technical
architectural
roles

Bus
/
LOBs

OperaQng
Model
-‐
Centralized

pg 19
DG

Execu<ve

Sponsor

DG

Steering

Commi@ee

Center
of
Excellence
(COE)

Data
Governance

Lead

Technical
Support

Data
Architecture
Group
Technical Data
Analysis
Group
Business
Support

Business

Analysis

Group

Data

Management

Group


4
LOB/BU

Data
Governance
Steering
Commi@ee

LOB/BU
Data
Governance
Working
Group

OperaQng
Model
-‐
Decentralized

pg 20
Data Stewards
Application
Architects
Business
Analysts
Data Analysts
Pros:

• RelaQvely
flat
organizaQon

• 
Informal
Data
Governance
bodies

• 
RelaQvely
quick
to
establish
and

implement

Cons:

• Consensus
discussions
tend
to
take

longer
than
centralized
edicts

• 
Many
parQcipants
compromise

governance
bodies

• 
May
be
difficult
to
sustain
over

Qme

• 
Provides
least
value

• 
Difficult
coordinaQon

• 
Business
as
usual

• 
Issues
around
co-‐owners
of
data

and
accountability


4
OperaQng
Model
-‐
Hybrid

pg 21
Pros:

• Centralized
structure
for
establishing

appropriate
direcQon
and
tone
at
the
top

• Formal
Data
Governance
Lead
role
serving
as
a

single
point
of
contact
and
accountability

• Data
Governance
Lead
posiQon
is
a
full
Qme,

dedicated
role
–
DG
gets
the
ahenQon
it

deserves

• Working
groups
with
broad
membership
for

facilitaQng
collaboraQon
and
consensus
building

• PotenQally
an
easier
model
to
implement

iniQally
and
sustain
over
Qme

• Pushes
down
decision
making

• Ability
to
focus
on
specific
data
enQQes

• Issues
resoluQon
without
pulling
in
the

whole
team
Cons:

• Data
Governance
Lead
posiQon
is
a
full
Qme,

dedicated
role

• Working
groups
dynamics
may
require

prioriQzaQon
of
conflicQng
business

requirements

• Too
many
layers
Data
Governance
Steering
Commihee

Data
Governance
Office

Data
Governance
Working
Group

Business
Stakeholders
IT
Enablement

Data Governance Organization

4
OperaQng
Model
-‐
Federated

Pros:

• Centralized
Enterprise
strategy
with

decentralized
execuQon
and
implementaQon

• Enterprise
Data
Governance
Lead
role
serving

as
a
single
point
of
contact
and
accountability

• “Federated”
Data
Governance
pracQces
per

Line
of
Business
(LOB)
to
empower
divisions

with
differing
requirements

• PotenQally
an
easier
model
to
implement

iniQally
and
sustain
over
Qme

• Pushes
down
decision
making

• Ability
to
focus
on
specific
data
enQQes,

divisional
challenges
or
regional
prioriQes

• Issues
resoluQon
without
pulling
in
the

whole
team
Cons:

• Too
many
layers

• Autonomy
at
the
LOB
level
can
be
challenging

to
coordinate

• Difficult
to
find
balance
between
LOB
prioriQes

and
Enterprise
prioriQes
Enterprise
Data
Governance
Steering

Commihee

Enterprise
Data
Governance
Office

Data
Governance
Groups

Data
Governance
OrganizaQon

pg 22
Business

Stakeholders

IT
Enablement

Divisional
DG

Office

Business

Stakeholders

IT
Enablement

Divisional
DG

Office

Business

Stakeholders

IT
Enablement

Business

Stakeholders

IT
Enablement

Divisional
DG

Office


4
OperaQng
Model
Roles
and
ResponsibiliQes

§  Data
Governance
Steering
Commihee

−  Provides
overall
strategic
vision

−  Approves
funding,
budget
and
resource
allocaQon
for
strategic
data
projects

−  Establishes
annual
discreQonary
spend
allocaQon
for
data
projects

−  Adjudicates
intractable
issues
that
are
escalated

−  Ensures
strategic
alignment
with
corporate
objecQves
and
other
business
unit
iniQaQves

§  Data
Governance
Office

−  Chairs
the
Data
Governance
Steering
Commihee
and
Data
Governance
Working
Group

−  Acts
as
the
glue
between
the
Data
Governance
Steering
Group
and
the
Working
Commihee

−  Defines
the
standards,
metrics
and
processes
for
data
quality
checks,
invesQgaQons,
and
resoluQon

−  Advises
business
and
technical
resources
on
data
standards
and
ensures
technical
designs
adhere
to

data
architectural
best
pracQces
to
ensure
data
quality

−  Adjudicates
where
necessary,
creates
training
plans,
communicaQon
plans
etc

§  Data
Governance
Working
Group

−  Governing
body
comprised
of
data
owners
across
Business
and
IT
funcQons
that
own
data
definiQons

and
provide
guidance
&
enforcement
to
drive
change
in
use
and
maintenance
of
data
by
the
business

−  Validates
data
quality
rules
and
prioriQze
data
quality
issue
resoluQon
across
the
funcQonal
areas

−  Trains,
educates,
and
creates
awareness
for
members
in
their
respecQve
funcQonal
areas

−  Implements
data
business
processes
and
are
accountable
to
decisions
that
are
made


4
Typical
DG
Oﬃce
Deliverables

§ Some
Typical
Deliverables:

§  Documented
DG
Strategy,
Vision,
Mission,
ObjecQves

§  Documented
DG
Guiding
Principles

§  Documented
roles
&
responsibiliQes
of
the
various
members

§  Up
to
date
OperaQng
Model

§  RACI
matrices

§  Templates
for
Policies
and
Processes

§  Templates
for
capturing
metrics
and
measurement
requirements

§  Templates
for
steering
commihee
meeQngs

§  Training
Plans

§  CommunicaQon
Plans

§  Template
for
regular
DG
communicaQon

§  Templates
for
logging
issues
needing
escalaQon
and
eventual
resoluQon

§  Templates
for
new
DG
service
requests

§  Checklists
for
new
projects
to
ensure
adherence
to
DG
standards


4
Typical
Roles

§ Business
Steward

§ Data
Owner

§ Data
Steward

§ Data
Quality
Analyst

§ Business
Analyst

§ Data
Architect

§ Technical
Leads
(MDM,
Metadata,
Reference
Data,
App)


4
Sample
Data
Governance
OperaQng
Model

Direc<on

TBD

Execu<ve
Sponsor

Business
and
IT

Business
Steward
Leads

Service
Order
Management

Finance
FP&A
Sales

Market
Strategy

Analy<cs

Data
Governance
Steering

Commi@ee

Finance

(CFO)

InternaQonal

(President)

Global

Services

(COO)

IT

(CIO)

MarkeQng

(CMO)

Data
Governance
Oﬃce

Data
Governance
Leads

Business
and
IT

Data
Governance
Coordinator

Management

Provides
budget
and

resource
approvals.

Forum
for
issue

escalaQon

Craps
the
enterprise
data

strategy,
including
polices,

processes
and
standards

to
ensure
that
data
is

managed
as
an
asset

Execu<ve
Level

Management

Level

Stewards
data
within

their

BU
to
ensure
that

the
enterprise
policies

are
applied

Tac<cal

Level

Strategic
Level

Provides
overall
strategic

direcQon,
budget
and

resource
approvals

forum
for
issue

escalaQon

Execu<on

Data
Management
IT
Support
Group

Data
Quality
Lead
Metadata
Lead

Data
Architect

BI
Delivery

Opera<ons
External

Repor<ng

DGWG

Enterprise

Architect

BA

Data
Analyst

IT
Security

Privacy

Legal

Data
Stewards

Risk

Centralized
Data
Steward
Pool

Accoun<ng


4
Data
Governance
Leadership
Team

Sample
MulQ-‐Domain
OperaQng
Model

Program
Oversight
&
DirecQon

ExecuQve
Sponsor

Program
Management

DG
Working
Group

Data
Governance
Program
Management
Team

DG
Program
Manager

DG
Coordinator

Program
ExecuQon

IT
Manager

Data Domain Owners
Business
Data
Leads

Data
AcquisiQon

Data
Stewardship

IT
Enablement

Supply
Chain
InternaQonal
Sales
HR
Finance
IT
MarkeQng

Customer
Product
Employee
Vendor
Supplier

DG
Data
Quality
Manager


4
Principle
Descrip<on

Be
clear
on
purpose
Build
governance
to
guide
and
oversee
the
strategic
and
enterprise
mission

Enterprise
thinking
Provide
consistency
and
coordinaQon
for
cross
funcQonal
iniQaQves.

Maintain
an
enterprise
perspecQve
on
data

Be
flexible
If
you
make

it
too
difficult,
and
people
will
circumvent
it.

Make
it

customizable
(within
guidelines),
and
people
will
get
a
sense
of
ownership

Simplicity
and
usability
are

the
keys
to
acceptance

Adopt
a
simple
governance
model
people
can
use.

A
complicated
and

inefficient
governance
structure
will
result
in
the
business
circumvenQng
the

process

Be
deliberate
on

par<cipa<on
and
process

Select
sponsors
and
parQcipants.
Do
not
apply
governance
bureaucracy

solely
to
build
consensus
or
to
saQsfy
momentary
poliQcal
interest

Enterprise
wide
alignment

and
goal
congruence

Maintain
alignment
with
both
enterprise
and
local
business
needs.
Guide

prioriQzaQon
and
alignment
of
iniQaQves
to
enterprise
goals

Establish
policies
with

proper
mandate
and
ensure

compliance

Clearly
define
and
publicize
policies,
processes
and
standards.
Ensure

compliance
through
tracking
and
audit

Communicate,

Communicate,

Communicate!

Frequent,
directed
communicaQon
will

provide
a
mechanism
for
gauging

when
to

“course
correct”,
manage
stakeholder
and
effecQveness
of

the

program

Data
Governance
Design
Principles


4
Keys
to
a
Successful
DG
OrganizaQon

§  Governance
team
must
contain
members
from
mulQple
lines
of
business

§  Ensures
cross
funcQonal
buy-‐in
and
ownership

§  Key
lines
of
business
must
be
represented

§  Team
members
must
represent
both
business
and
IT

§  IT
needs
to
be
able
to
implement
per
the
governance
policies
and
the
business
needs
to
be
aware

of
IT
limitaQons…

§  Team
needs
to
meet
on
a
regular
basis

§  Business
is
constantly
changing

§  Discuss
new
and
emerging
programs

§  Current
IT
acQviQes
and
their
effect
on
the
data

§  Review
policies
and
study
measurement
output

§  Agreed
upon
fundamentals
that
serve
as
the
Guiding
Principles

§  If
this
doesn’t
exist,
the
first
mandate
is
to
create
this

§  Standards
are
mechanisms
for
Qe-‐breaking

§  Clear
lines
of
communicaQon

§  Regular
interacQon
with
execuQve
management

§  Ensure
communicaQon
methods
to
enforce
policies
at
the
steward
and
stakeholder
level

§  Invite
stewards,
project
managers,
stakeholders
etc
to
provide
status
updates
on
criQcal
iniQaQves

that
affect
the
data

§  Ensure
the
Opera<ng
Model
fits
the
culture
of
the
company


4
Exercise:
CreaQng
an
OperaQng
Model

§ Part
One:
10
minutes

§ Describe
your
current
organizaQonal
structure

§ Is
your
organizaQon
centralized
or
decentralized?

§ How
are
decisions
made
in
your
organizaQon?
Consensus?
Fiat?

§ Are
there
any
decision
making
bodies
or
commihees?
If
yes:

−  What
is
their
structure?

−  Who
is
part
of
it?

−  What
is
their
mandate?

−  What
are
their
current
roles
and
responsibiliQes?

§ Share
and
discuss


4
Exercise
Workspace

§ Describe
your
current
organizaQonal
structure

§ Is
your
organizaQon
centralized
or
decentralized?

§ How
are
decisions
made
in
your
organizaQon?
Consensus?
Fiat?

§ Are
there
any
decision
making
bodies
or
commihees?
If
yes:

−  What
is
their
structure?

−  Who
is
part
of
it?

−  What
is
their
mandate?

−  What
are
their
current
roles
and
responsibiliQes?


4
Exercise:
CreaQng
an
OperaQng
Model

§ Part
Two:
10
minutes

§ IdenQfy
which
OperaQng
Model
best
ﬁts
your
organizaQon

§ Why
do
you
think
it’s
the
best
ﬁt?

§ IdenQfy
possible
exisQng
commihees
that
can
be
leveraged
to

create
the
DG
Steering
Commihee

−  What
are
their
current
roles
and
responsibiliQes?

−  Who
currently
sits
on
that
Commihee?

−  Who
else
would
need
to
parQcipate
if
it
was
used
for
DG
decisions?

−  Is
there
anyone
on
the
Commihee
that
doesn’t
need
to
be
involved
in
DG

decisions?

§ Share
and
discuss


4
Exercise
Workspace

§ IdenQfy
which
OperaQng
Model
best
ﬁts
your
organizaQon

§ Why
do
you
think
it’s
the
best
ﬁt?

§ IdenQfy
possible
exisQng
commihees
that
can
be
leveraged
to

create
the
DG
Steering
Commihee

−  What
are
their
current
roles
and
responsibiliQes?

−  Who
currently
sits
on
that
Commihee?

−  Who
else
would
need
to
parQcipate
if
it
was
used
for
DG
decisions?

−  Is
there
anyone
on
the
Commihee
that
doesn’t
need
to
be
involved
in
DG

decisions?


4
Alignment


4
Random
House
DicQonary:
a
state
of
agreement
or
cooperaQon

among
persons,
groups,
naQons,
etc.,
with
a
common
cause
or

viewpoint.

Wikipedia:
Alignment
is
the
adjustment
of
an
object
in
relaQon

with
other
objects,
or
a
staQc
orientaQon
of
some
object
or
set

of
objects
in
relaQon
to
others.

Understanding
a
process
from
the
perspec4ve
of
others

Working
individually
towards
a
common
goal

DeﬁniQon
of
Alignment


4
Impact
on
Governance
Programs

Sources
of
mis-‐alignment

§ Lack
of
understanding

−  Of
how
an
individual’s
role
fits
into

Corporate
ObjecQves

−  Of
other
jobs,
roles,
experiences,

objecQves

§ ConflicQng/
compeQng
objecQves

§ PoliQcs

§ CommunicaQon
styles

§ Personality
conflicts

Importance
of
Alignment

§ Creates
a
conQnual
“buy-‐in”
process

with
all
Stakeholders

§ Helps
organizaQons
“think
globally

and
act
locally”

§ OpQmizes
resources
to
manage

costs

§ Work
towards
a
common
goal

§ Minimizes
risk


4
Alignment
Process

• Why
is
this

important?

• Why
should
we

care?

Value

• Who
cares?

• Why
should

they
care?

Stakeholders

• How
does
the

value
beneﬁt

the

stakeholders?

Linkage


4
IdenQfy
and
Align
Values

pg 39
Value
of
DG
to
Business
Value
of
DG
to
IT


4
IdenQfy
Stakeholders

§ Who
are
the
Stakeholders?

§  IT

§  OperaQons

§  Compliance

§  Line
of
Business

§ What
are
their
drivers?

§  What
are
their
key
goals?

§  What
are
their
concerns?

§  What
are
they
trying
to
avoid?

§ What
are
their
prioriQes?

§  Which
goals
are
criQcal?

§  What
happens
if
those
goals
aren’t
achieved?


4
pg 41

Proprietary & Confidential
Stakeholder
Map

Value
of
DG
to

Business

Value
of
DG
to

IT


4
Linkage
is
the
tacQcal
process
of
mapping
your
delivery
to
the

issues
important
to
the
stakeholder.

•  Per
Stakeholder,
idenQfy
what
is
important
to
them
and

why.

§  What
happens
if
they
don’t
achieve
their
goal?

•  List
elements
of
DG
soluQon

•  Choose
Top
3

•  Choose
up
to
3
elements
of
the
DG
soluQon
and

arQculate
how
those
deliverables
can
help
that
person

achieve
their
goals

§  ConQnually
ask
yourself,
So
What?

Linkage
delivers
Alignment

Create
Linkage


4
PotenQal
Deliverables

§ Consistency
of
customer/product/employee
data

§ Improve
data
quality

§ Improve
data
consumpQon
and
appropriate
usage

§ Create
and
understand
data
lineage

§ Create
a
data
plasorm
to
support
a
single
face
to
the
Customer

§ Facilitate
the
concept
of
“Single
Sourcing”
of
data
to
the
Data

Warehouse
and
Business
ApplicaQons

§ Create
and
implement
common
enterprise
systems/tools
and

processes
for
selected
data


4
DG
Program

Sales/MarkeQng

Improve
Understanding
of

Customers

Improve
SegmentaQon

Understand
Risk

IT

Improved
ProducQvity

ProacQvely
support
business

Lower
TCO

Improved
Data

Quality

Single
Repository
of

Customer
Data

Create
Data

Lineage

ArQculate
Linkage

The
Single
Repository
of
Customer
data

will
improve
my
understanding
of

customers
by
providing
me
a
trusted

source
of
Qmely,
accurate
and
perQnent

data
from
which
to
execute
analyQcs,

segmentaQon
and
risk
assessment.

CreaQng
and
understanding
Data
Lineage

will
improve
IT
producQvity
by
reducing

the
Qme
spent
searching
for
data,
ensure

the
appropriate
data
is
used
and

validaQng
the
data.
Data
Lineage
that
is

created
and
understood
by
both
IT
and

business
will
facilitate
a
common

language
and
enable
IT
to
beher
support

the
business
growth
and
expansion.


4
•  Per
Stakeholder,
idenQfy
what
is
important
to
them
and
why.

§  What
happens
if
they
don’t
achieve
their
goal?

•  List
elements
of
DG
soluQon

•  Choose
Top
3

•  Choose
up
to
3
elements
of
the
DG
soluQon
and
arQculate
how

those
deliverables
can
help
that
person
achieve
their
goals

§  ConQnually
ask
yourself,
So
What?

§  10
minutes

§  Share
and
discuss

Exercise


4
Exercise
Workspace

Stakeholder
Deliverable
Linkage
Statement


4
Linkage
creates
Alignment


4
Metrics
&
Measurement


4
Why
are
Metrics
Important?

Alignment

Relevance

Value


4
DefiniQon

§ Metric

−  A
metric
is
any
standard
of
measurement

§  Number
of
business
requests
logged

§  Number
of
data
owners
idenQfied

§  Percentage
business
requests
resolved
within
agreed
SLA,
etc.

§ Key
Performance
Indicator
(KPI)

−  A
Key
Performance
Indicator
(KPI)
is
a
quanQfiable
metric
that
the
DG

Program
has
chosen
that
will
give
an
indicaQon
of
DG
program

performance.

−  A
KPI
can
be
used
as
a
driver
for
improvement
and
reflects
the
criQcal

success
factors
for
the
DG
Program

§ A
metric
is
not
necessarily
a
KPI


4
Metrics/KPIs
examples

pg 51
People

§  #
of
DGWG
decisions
backed
up
by
the
steering
commihee

§  #
of
approved
projects
from
the
DGWG

§  #
of
issues
escalated
to
DGP
and
resolved

§  #
of
data
owners
idenQfied

§  #
of
data
managers
idenQfied

§  DG
adop4on
rate
by
company
personnel
(Survey)

Process

§  #
of
data
consolidated
processes

§  #
of
approved
and
implemented
standards,
policies,
and
processes

§  #
of
consistent
data
definiQons

§  Existence
of
and
adherence
to
a
business
request
escalaQon
process
to
manage
disputes
regarding
data

§  Integra4on
into
the
project
lifecycle
process
to
ensure
DG
oversight
of
key
ini4a4ves

Technology

§  #
of
consolidated
data
sources
consolidated

§  #
of
data
targets
using
mastered
data

§  Address
accuracy
for
mailing/shipping

§  Data
integrity
across
systems

§  Records/data
aged
past
target

§  Presence and usage of a unique identifier(s)


4
Aligning
Benefit
to
Value

Benefits
of
Data
Governance

• Data
lineage
and
auditability

• Improved
data
transparency
and
quality

• Repeatable
processes
and
reusable

arQfacts

• Consistent
definiQons

• Appropriate
use
of
informaQon

• CollaboraQon
among
teams,
business

units,
etc..

• Accountability
for
informaQon
use

• Quality
of
all
data
types

• Easier
sharing
of
informaQon

• Visibility
into
the
enterprise
via
data

• InformaQon
security

Content
property
of
IMCue
and
FSFP,
Copyright
2013

ReproducQon
prohibited


4
CreaQng
Metrics


4
Process
to
Establish
Metrics

pg 54
Issues

• What
are
the

issues
in
your

group?

• What
do
you

mean
by
that?

• Why
is
it

important?

• What
are
your

objecQves?

Goals

• What
is
the

change
you
would

like
to
see?
What

acQon?

• How
will
that

change
impact

you?

• What
is
the

impact
if
those

objecQves
aren’t

met?

Metrics/KPI’s

• What
processes

are
involved
in

that
change?

• How
is

informaQon
used

in
that
process?

• What
informaQon

is
used?
What

data?

• What
data

improvements

are
needed?

Impact

• PosiQve
change

created
by

addressing
issues

• Beneﬁt
of

improving
data
to

impact
objecQve


4
GeTng
to
Data
Change
Metrics

Issues/
Objec<ves

Goals
Informa<on
Data
Data
Change
Addi<onal

Ac<on

Report
Quality

and
Accuracy

Improve
Data

Understanding

Accounts
Client

InformaQon

Reduce

duplicaQon
of

client
data

Improve
Data

Transparency

Increase

completeness

of
record

Reduce
Manual

RemediaQon

Track
data

lineage

Ensure

thoroughness

of
data
sources

Products

owned

Increase

Completeness

of
record

Ensure

thoroughness

of
data
sources

Households
RelaQonship

Groups


4
Sample
Data
Metrics

Data
Change
Measurement
Target
Frequency

Reduce
DuplicaQon
of

Client
Data

%
DuplicaQon
99%
Daily

Increase
Completeness
of

Client
Record

%
Completeness
of
key
ﬁelds
99%
Daily

Track
Data
Lineage
Completeness
of
lineage
diagram
99%
Monthly

Ensure
Thoroughness
of

Client
Data
Sources

Review
of
data
acquisiQon
and
ETL
process
Business

consensus

Quarterly

Increase
Completeness
of

Products
Owned

%
Completeness
of
key
ﬁelds
99%
Weekly

Ensure
Thoroughness
of

Product
Data
Sources

Review
of
data
acquisiQon
and
ETL
process

Business

consensus

Quarterly


4
GeTng
to
Business
Change
/
Impact
Metrics

pg 57
Goal
Measurement
Target
Frequency

Improve
Data

Understanding

Completeness
of
Business
Glossary

%
of
Business
Users
Trained

100%

100%

Monthly

Monthly

Improve
Data

Transparency

Completeness
of
Lineage
80%
Monthly

Reduce
Manual

RemediaQon

Time
to
complete
report
process
(baseline

is
6
days)

1
Day
Monthly

Increase
Report
Quality

and
Accuracy

Improved
Business
Stakeholder

SaQsfacQon
Survey

Reduced
Issue
Requests

Business

Approval

10%
drop

Quarterly

Monthly

This
is
your
KPI


4
Sample
Metrics


4
ImplemenQng
Data
Governance
at
XXX
ensures
our
data
is

managed
as
an
asset
of
the
firm

§ A
Data
Governance
Office
will
be
established
to
administer

XXX’s
data
governance
policies
and
standards,
working
with
the

various
assigned
Data
Owner
and
Business
Data
Stewards
across

the
corporaQon

§ Managing
data
as
an
asset
will
enable
XXX
data
to
be:

−  Discoverable
(“I
understand
what
data
is
available
to
me
and
where
it

lives”)

−  Accessible
(“I
know
how
to
and
who
can
access
the
data”)

−  Trusted
(“I
feel
confident
in
the
quality
in
the
data”)

−  AcQonable
(“I
know
what
that
data
is
and
can
use
it
to
derive
business

value”)

§ This
will
increase
the
value
of
our
data
and
allow
us
to
beher

leverage
data
to
drive
compeQQve
advantage

59Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

4
From
Vision
to
Measurement

Data
Value

Discoverable

LocaQon

Book
of

Record

Book
of

Reference

InformaQon

Layer

Content

Ahributes

Metadata

DefiniQon

Accessible

Access
Rights

Data

ClassificaQon

Privacy

User
Role
Data
Owner

Trusted

Data
Quality

7
Dimensions

of
Quality

Reproduce-‐
able

AcQonable

Purpose
Guidelines

Meaning

DefiniQon

Metadata

Data
Change


4
Sample
Data
Metrics

Data
Change
Measurement
Target
Frequency

Uniqueness
%
Uniqueness
of
Party
99%
Daily

Completeness
%
Completeness
of
key
fields
99%
Daily

Data
DefiniQons

(Business
Metadata)

Completeness
of
DefiniQons
100%
over

Qme

Monthly

Metadata

(Technical)

Complete
accurate
Metadata

100%
over

Qme

Monthly


4
Exercise

§ ArQculate
an
Issue

−  What
is
the
issue?

−  Why
is
it
important?

§ Determine
the
Goals

−  What
is
the
change
you’d
like
to
see?

§ Deﬁne
the
Metrics

−  How
can
we
measure
the
components?

§ ArQculate
the
Impact
measure


4
Exercise
Workspace

pg 63
Issue
Goals
Metrics
Impact


4
CSIM

SCORECARD

BU
2

SCORECARD

ESIM

SCORECARD

BU
1

SCORECARD

XXX
DATA
GOVERNANCE

SCORECARD

(FUTURE
STATE)

STRATEGIC

VIEW

OPERATIONAL

SCORECARDS

CONSOLIDATED
BY

BUSINES
UNIT

SETUP

RULES
THRESHOLDS

DATA
QUALITY

DIMENSIONS

FFREQUENCY
WEIGHTING
ALL
SCORECARDS

START
WITH
A

BASELINE

Scorecard
Approach:
Show
some
vision
forward

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

ATTRIBUTE

SCORECARD

Ahribute
level
Supports

OperaQonal
Use
Case

EnQty
Level
Supports

CSC
Data
Governance

(Strategic
Value)


4
CommunicaQon
&
Stakeholder
Management


4
Why
is
CommunicaQon
Important?

pg 66
Ø Creates
Awareness

Ø Aligns
expectaQons

Ø Creates
an
opportunity
for

feedback
/
engagement

Ø ProacQvely
addresses
Change

Ø Publishes
Success

Ø Answers
the
quesQons
“Why?”
and
“What’s
in
it
for
me?”

Ø Aligns
acQviQes


4
TranslaQng
Data
Value
into
Business
Value

is
key
to
maintaining
commitment

§ The
right
metrics
help
maintain
alignment

−  Metrics
have
no
value
if
they
aren’t
aligned
to
the
interests
of
a

stakeholder

−  Ensure
there
is
some
way
of
measuring
how
the
improvement
in
data
is

helping
stakeholders
progress
toward
their
goals

−  What
informaQon
do
you
need
to
track
and
measure
to
those
goals?

§ Translate
the
value
statement
into
the
language
of
the
recipient


4
Purpose:
Increase
Stakeholder
Engagement

Using
this
framework
enables
clear
gaps
in
stakeholder

engagement
to
be
idenQﬁed
and
subsequent
change

strategies
to
be
put
in
place
to
enable
the
gaps
to
be
closed

T I M EStatus Quo Vision
COMMITMENT/ENTHUSIASM
High
Contact
I’ve heard about this
program/project
Low
I know the concepts
Awareness
I understand how
Program/project positively impacts
and benefits me and the organization
Positive Perception
This is how we do business
Institutionalization
Understanding
I understand what this means to
me and the organization as a
whole
Adoption
I am willing to work hard
to make this a success
Internalization
I’ve made this my own and will
constantly create innovative
ways to use it

4
•  Engagement
Strategy:

•  Focused
effort
must
be
given

to
high
priority
groups

•  Provide
sufficient
level
of

informaQon
to
less
influenQal

groups
to
ensure
buy-‐in

•  Move
people
and
or
groups

to
the
right
by
trying
to

increase
their
level
of

interest

•  Forms
the
foundaQon
of
your

engagement
/

communicaQon
strategy

Stakeholder
Engagement
Strategy

pg 69
Meet

Their
Needs

Key

Player

Least

Important

Show

Considera<on

Stakeholder

Influence

Stakeholder
Influence

Stakeholder
Interest


4
What
is
a
CommunicaQon
Plan?

Plan
DeﬁniQon

−  A
wrihen
document
that
helps
an
organizaQon
achieve
its
goals
using

wrihen
and
spoken
words.

−  Describes
the
What,
Why,
When,
Where,
and
How

§ Importance
of
a
CommunicaQon
Plan

−  Gives
the
working
team
a
day-‐to-‐day
work
focus

−  Helps
stakeholders
and
the
working
team
set
prioriQes

−  Provides
stakeholders
with
a
sense
of
order
and
controls

−  Provides
a
demonstraQon
of
value
to
the
stakeholders
and
the
business
in

general

−  Helps
stakeholders
to
support
the
DG
Program

−  Protects
the
DG
Program
against
last-‐minute
demands
from
stakeholders


4
CommunicaQon
Plan

§ Brings
it
all
together:

−  Who
do
we
need
to
communicate
to?

−  What
informaQon
will
be
important
to
them?

−  Metrics
that
map
to
their
professional
and
personal
goals

−  How
frequently
should
they
be
updated?

−  What
is
the
method
of
communicaQon?

−  Who
should
be
communicaQng
to
them?


4
Components
of
a
CommunicaQon
Plan

Communica<on
Plan
Stakeholder:

XXX

QualitaQve
InformaQon
Any
general
qualitaQve
informaQon
that
I
would
like

to
receive
related
to
this
deliverable

QuanQtaQve

InformaQon

Of
the
quanQtaQve
metrics
that
have
been
deﬁned,

which
are
the
ones
I
would
like
to
be
informed
about

AND
how
do
I
want
the
metric
communicated
to
me

to
make
the
message
perQnent

Frequency
How
open
do
I
want
to
be
informed
about
progress

Method
What
is
my
preferred
mechanism
of
receiving
the

informaQon


4
Item Frequency Description Purpose Audience Documentation From Date Owner Status
Meetings
First BSL Meeting One-Time
Introduction
Get explicit buy-in from the
participants and resource ask
DGWG BSLs PowerPoint PresentationJohn 8/25/11 John Complete
DGWG Core Team Kickoff MeetingOne-Time DGO kickoff and vision from IT
Sponsor
Kickoff DGWG-Core, IT
Sponsor
PowerPoint presentationJohn 9/15/11 John Complete
DGO Launch Logistics One-Time Communication announcing the DGOPlan on the best way to
communicate the DGO launch and
PR effort
DGO, SVB Corporate
Communication
Email John TBD John Complete
DGO-DGWG-Core Status Meeting Weekly DGWG accomplishments, progress
towards goals and issues
Status DGWG-Core members SharePoint Agenda &
Content
John Ongoing Flo In progress
Meeting with DGO IT Lead Weekly Planning and strategy Status/Planning DGO Chair, DGO IT
Lead and DGC
John Ongoing John
DGO & MDM alignment meetings Weekly MDM Implementation update Status MDM team, DGO Chair
& DGC
Agenda Rebecca Ongoing Rebecca
Mentoring program
(Data Stewardship Program)
Weekly Opportunity to learn from Business
Steward Leads. Best practices,
polices, processes, standards,
definitions
Enrichment DGWG Data Stewards Data Stewardship Best
practices. DGO Polices,
processes, standards,
definitions
TBD TBD TBD Not Started
Meeting with Program Sponsors Bi-Weekly? Provide DGWG accomplishments,
progress towards goals and issues
Status DGO Chair, Biz and IT
Sponsor
PowerPoint presentationJohn TBD John Not Started
DGO-DGWG Decision
(Core & Advisory) Meeting
Monthly DGWG voting meeting Vote and approve DGWG materialsDGWG members SharePoint Agenda &
Content
John Ongoing Flo In progress
DGO-DGWG - DM IT Support
Group Meeting
Monthly DGWG DM IT Support Group team
monthly update
Bring the advisory team up to
speed on status before the decision
meeting
DGWG Advisory
members
SharePoint Agenda &
Content
John TBD Flo Not Started
EIC Meeting Monthly DGWG accomplishments, progress
towards goals, issues, documents for
informational purposes only
Status, Informational EIC members PowerPoint presentationJohn Ongoing John In progress
Meeting with SAM - Fund Business
stakeholders
As needed Relationship building/Expectations/
Impact
DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started
Meeting with Purchasing
stakeholders
Impact
Meeting with Product
Implementation stakeholders
Impact
Meeting with Global Product
stakeholders
Impact
DGO Town Halls One/Year DGWG accomplishments and
progress towards goals Forum for
open discussion
Team Building All DGWG members PowerPoint presentationJohn TBD Flo Not Started
Sample
CommunicaQon
Plan

pg 73
And
these
are
just
the

meeQngs!
Also:

• 
Awareness
&

Training

• 
CommunicaQon

Vehicles

• 
Knowledge
Sharing

• ….


4
Embedding
Data
Governance


4
Ensuring
DG
is
Sustainable

•  Incorporate
DG
goals
into
other
goals,

objecQves
and
incenQves
Incorporate

•  Align
DG
with
strategic
objecQves,

programs
and
projects
Align

•  Embed
DG
into
standard
project,
change

control,
new
iniQaQve
and
operaQonal

processes

Embed

•  Focus
on
delivering
business
value
Focus


4
Incorporate
IncenQves

Carrots
SQcks

Oversight
AllocaQon


4
Align
with
ObjecQves,
Programs
and
Projects

§ Examples:

§ Alignment
with
Stakeholder
goals
(already
discussed)

§ Alignment
with
Corporate
ObjecQves

§ Alignment
with
strategic
Programs/Projects


4
Example:
Alignment
with
Corporate
ObjecQves


4
Example:
Tie
Principles
to
Corporate
ObjecQves

Corporate
Objec<ve
Principle

Client
Data
is
a
key
asset
to
our
company.
We
will
enhance
and
manage

this
asset
by
emphasizing
clear
strategies,
decisive
acQon,

innovaQon
and
results.

CapabiliQes
Business
stakeholders
will
get
informaQon
delivered
at
the
right

Qme,
locaQon
and
amount
as
efficiently
as
possible.

ExecuQon
Data
Governance
will
introduce,
support
and
drive

standardizaQon
of
enterprise
data.

Brand
Best
in
class
customer
data
quality
will
significantly
improve
both

the
internal
as
well
as
external
customer
experience.

People
Data
Governance
should
increase
producQvity
through

centralized,
streamlined
processes
and
eliminate
non-‐value
added

acQviQes.
Maximizing
automaQon
is
a
key
way
to
improve
human

resource
efficiencies
and
is
preferable
over
manual
processes.

Principles
drive
crea.on
and
execu.on
of
policies,
standards,

processes,
etc….


4
Program
/
Project
Alignment


Project

IniQaQon

Project

ExecuQon

Change

Control

OperaQonal


4
Sample:
Embed
in
Project
IniQaQon
Process

pg 82
IdenQfy

informaQon/

infrastructure

needs

Proﬁle
to
Iden<fy

data
issues

Analyze
to

Iden<fy
root

causes/
gaps

Design
solu<ons

to
root
cause

problems
/
gaps

Implement

process
&
Tech

soluQons

Sustain

Proac.vely
iden.fy
problems
and
solve
root
causes


4
Sample:

Embed
Data
Governance
Into
Your
Project
Methodology

Engage
DG,
DQ,
DA,

MDM,
Metadata

Leads

Assess
adherence
to

Guiding
Principles

Alignment

Workshop

Assess
adherence
to

Guiding
Principles

Engage
DG,
DQ,
DA,

MDM,
Metadata
Leads

Engage
DG,
DQ,
DA,

MDM,
Metadata
Leads

AddiQonal
DG,
DQ,
DA,
MDM
and
Metadata
related
deliverables
added
to
‘typical’

list:

Data
Profiling
Reports,
New/modified
Score-‐cards,
AddiQonal
Metadata,
New/
modified
Processes,
Data
Model
Reviews,
etc

Engage

DG,
DQ,

DA,
MDM,

Metadata

Leads

Engage

DG
Lead


4
Sample:

Embed
Data
Governance
with
Change
IniQators/Control

A
process
ﬂow
will
help
ensure
consistent
change

requests
related
to
data


4
Sample:
OperaQonal
Process
(Client
On-‐Boarding)

New
Client

Request

DocumentaQo
n
&
Due

Diligence

Terms

conﬁrmed

Agreement
/

Contract

Created

Create
Client

• ExisQng
or
Previous

Client
(Master
Data

Check)

• Data
Standards
and

ValidaQon

• Data
Quality
Check

• Regulatory
Checks

• RACI
/
Data
Ownership

• Data
Enrichment

• Data
ClassiﬁcaQon

• Data
RemediaQon

• Decision
Making
/

EscalaQon
Processes

• Hierarchy
/

RelaQonship
Check

• Client
SegmentaQon

• Contract

Management

• Document

Management

• Update
Master
Data

• Create
Hierarchies

• Data
Standards
and

ValidaQon

• Data
Quality
Check

• Data
Sharing,
Access
&

Use
Policy

• …

4
Ensuring
Success


4
Ensuring
Success

§ The
following
factors
are
usually
evident
in
a
successful

program:

−  First
create
a
strategy
and
then
follow
it
(agreed
on
starQng
point
&
steps

necessary)

−  Ensure
solid
alignment
between
Business
&
IT

−  Clearly
deﬁned
and
measureable
success
criteria

−  Small
iteraQons
vs.
all
or
nothing

−  ExecuQve
sponsorship
is
criQcal

−  IdenQfy
and
assess
the
importance
of
key
people
and
or
groups

−  Really
know
your
data

−  Leverage
prior
experience/work…don’t
re-‐invent
the
wheel

−  Embed
governance
into
the
operaQons
of
your
company

−  Communicate,
Communicate,
Communicate!


4
Principle
Descrip<on

Be
clear
on
purpose
Build
governance
to
guide
and
oversee
the
strategic
and
enterprise
mission

Enterprise
thinking
Provide
consistency
and
coordinaQon
for
cross
funcQonal
iniQaQves.

Maintain
an
enterprise
perspecQve
on
data

Be
flexible
If
you
make

it
too
difficult,
and
people
will
circumvent
it.

Make
it

customizable
(within
guidelines),
and
people
will
get
a
sense
of
ownership

Simplicity
and
usability
are
the

keys
to
acceptance

Adopt
a
simple
governance
model
people
can
use.

A
complicated
and

inefficient
governance
structure
will
result
in
the
business
circumvenQng

the
process

Be
deliberate
on
par<cipa<on
and

process

Select
sponsors
and
parQcipants.
Do
not
apply
governance
bureaucracy

solely
to
build
consensus
or
to
saQsfy
momentary
poliQcal
interest

Enterprise
wide
alignment
and

goal
congruence

Maintain
alignment
with
both
enterprise
and
local
business
needs.
Guide

prioriQzaQon
and
alignment
of
iniQaQves
to
enterprise
goals

Establish
policies
with
proper

mandate
and
ensure
compliance

Clearly
define
and
publicize
policies,
processes
and
standards.
Ensure

compliance
through
tracking
and
audit

Communicate,
Communicate,

Communicate!

Frequent,
directed
communicaQon
will

provide
a
mechanism
for
gauging

when
to

“course
correct”,
manage
stakeholder
and
effecQveness
of

the

program

Governance
Design
Principles

pg 88
Design

Principles


pg 89
Thank
you!

Kelle
O’Neal

kelle@ﬁrstsanfranciscopartners.com

415-‐425-‐9661

@1stsanfrancisco


Sustainable Data Governance

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