Top 10 Artifacts Needed For Data Governance

The First Step in Information Management

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Top 10 Artifacts Needed for Data Governance

Why We’re Here

Purpose: Review the most important and impactful artifacts and

deliverables needed to implement and sustain governance.

Outcome: Understanding of the Top 10 Data Governance Artifacts Determine how to ensure artifacts are used Practical knowledge that can be implemented immediately

© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential pg 2

Agenda

Quick Level Setting

Understanding typical Obstacles

The Top 10 Artifacts ….

pg 3 © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

Why is Data Governance Important?

Internal pressures:

Desire to understand customer at any time 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/opportunities

External pressures:

Greater amounts of new regulations

Increasing Customer Demands – my information anywhere at any time

Technology and market changes outpacing ability to respond

Data Governance Ensures the right people are involved in determining standards, usage and

integration of data across projects, subject areas and lines of business


Data Governance Definition

Data Governance is the organizing framework for establishing the strategy, objectives and policy for effectively managing corporate data.

It consists of the processes, policies, organization and technologies required to manage and ensure the availability, usability, integrity, consistency, auditability and security of your data.

Communication and 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


pg 6

Data Governance Framework

© 2016 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

• Vision & Mission

• Objectives & Goals

• Alignment with Corporate

Objectives

• Alignment with Business

Operations

• 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 & Knowledge

Management

• Data Mastering & Sharing

• Data Architecture, Security

and Lifecycle Management

• Data Quality & Stewardship

Workflow

• Metadata Repository

• Communication Plan

• Training Strategy

• Vehicles/Mechanisms

• Content

• Accountability

• Impact & Readiness Assessment

• Leadership Alignment

• Stakeholder Management

• Change Plan and Implementation Checklist

• Transition to Sustaining Plan

Change

Management

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

Retention/Archiving

Master Data Management

Big Data Management

Metadata Management Reference Data Management

Privacy/Security

DATA GOVERNANCE


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

pg 8

The Big Picture: EIM Framework


Provides a holistic view of information in order to manage information as a corporate asset

Enterprise Information Management

Information Strategy

Architecture and Technology Enablement

Content Delivery

Business Intelligence and Performance Management

Data Management Information Asset Management

GOVERNANCE

ORGANIZATIONAL ALIGNMENT

Content Management

Obstacles

Competing priorities and lack of resources

Data Ownership and other territorial issues

Lack of cross-business unit coordination

Lack of data governance understanding

Resistance to change or transformation

Lack of executive sponsorship and buy-in

Resistance to accountability

Lack of business justification

Inexperience with cross-functional initiatives

Change of personnel


Effort

Control

Obstacles


Top 10 Artifacts

Business Alignment Statement

• Articulates Priorities

Operating Model

• Roles & Responsibilities

• Escalation and Decision Making

RACI Matrix

• Accountability

Charter

• Scope and Guiding Principles

Policy

• Codification of Principles and Accountability

pg 11

Standard Processes

• Repeatable Common Activities

Change Management Plan

• Strategy to ensure traction

Measurement Dashboard

• Tracking of progress and impact

Communication and Training Plan

• Maintains Commitment

• Up-skills Resources

Business Data Glossary

• Standardized Data Definitions



Business Alignment Statement(s)

Random House Dictionary: a state of agreement or cooperation among persons, groups, nations, etc., with a common cause or viewpoint.

Wikipedia: Alignment is the adjustment of an object in relation with other objects, or a static orientation of some object or set of objects in relation to others.

Understanding a process from the perspective of others

Working individually towards a common goal

Definition of Alignment


Impact on Governance Programs

Sources of mis-alignment

Lack of understanding − Of how an individual’s role fits into

Corporate Objectives

− Of other jobs, roles, experiences, objectives

Conflicting/ competing objectives

Politics

Communication styles

Personality conflicts

Importance of Alignment

Creates a continual “buy-in” process with all Stakeholders

Helps organizations “think globally and act locally”

Optimizes resources to manage costs

Work towards a common goal

Minimizes risk


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


pg 16 Proprietary & Confidential

Stakeholder Map

Value of DG to Business

Value of DG to IT


Linkage is the tactical process of mapping your delivery to the issues important to the stakeholder.

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

What happens if they don’t achieve their goal?

• List elements of DG solution

• Choose Top 3

• Choose up to 3 elements of the DG solution and articulate how those deliverables can help that person achieve their goals

Continually ask yourself, So What?

Linkage delivers Alignment pg 17

Create Linkage


DG Program

Sales/Marketing

Improve Understanding of Customers

Improve Segmentation

Understand Risk

IT

Improved Productivity

Proactively support business

Lower TCO

Improved Data Quality

Single Repository of Customer Data

Create Data Lineage

Articulate Linkage

The Single Repository of Customer data will improve my understanding of customers by providing me a trusted source of timely, accurate and pertinent data from which to execute analytics, segmentation and risk assessment.

Creating and understanding Data Lineage will improve IT productivity by reducing the time spent searching for data, ensure the appropriate data is used and validating the data. Data Lineage that is created and understood by both IT and business will facilitate a common language and enable IT to better support the business growth and expansion.


pg 19

Business Information Requirements* *BIR’s courtesy of John Ladley



Operating Model

Operating Model

Outlines how Data Governance will operate

Forms basis for the Data Governance organizational structure – but isn’t an org chart

Ensures proper oversight, escalation and decision making

Ensures the right people are involved in determining standards, usage and integration of data across projects, subject areas and lines of business

Creates the infrastructure for accountability and ownership

pg 21

Wikipedia: An Operating Model describes the necessary level of business process integration and data standardization in the business and among trading partners and guides the underlying Business and Technical Architecture to effectively and efficiently realize its Business Model. The process of Operating Model design is also part of business strategy.


Types of Operating Models

Centralized

− Similar to a top down project model

Decentralized

− Flat structure, more virtual/grassroots in nature

Hybrid / Federated


Process

• How are decisions made?

• Who makes them?

• How are Committee’s used?

Culture

• Centralized

• Decentralized

• Hybrid

Operating Model • Data Governance

Owner

• SME’s

• Leadership

People


Pros:

• Formal Data Governance executive position

• Data Governance Steering Committee reports directly to executive

• 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 Organizational Impact

• New roles will most likely require Human Resources approval

• Formal separation of business and technical architectural roles

Bus / LOBs

pg 24

Operating Model - Centralized

DG Executive Sponsor

DG Steering

Committee

Center of Excellence (COE)

Data Governance Lead

Technical Support

Data Architecture Group

Technical Data Analysis Group

Business Support Business Analysis Group

Data Management

Group


LOB/BU Data Governance Steering Committee

LOB/BU Data Governance Working Group

pg 25

Operating Model - Decentralized

Data Stewards Application

Architects

Business

Analysts Data Analysts

Pros:

• Relatively flat organization

• Informal Data Governance bodies

• Relatively quick to establish and implement

Cons:

• Consensus discussions tend to take longer than centralized edicts

• Many participants compromise governance bodies

• May be difficult to sustain over time

• Provides least value

• Difficult coordination

• Business as usual

• Issues around co-owners of data and accountability


pg 26

Operating Model - Hybrid

Pros:

• Centralized structure for establishing appropriate direction and tone at the top

• Formal Data Governance Lead role serving as a single point of contact and accountability

• Data Governance Lead position is a full time, dedicated role – DG gets the attention it deserves

• Working groups with broad membership for facilitating collaboration and consensus building

• Potentially an easier model to implement initially and sustain over time

• Pushes down decision making

• Ability to focus on specific data entities

• Issues resolution without pulling in the whole team

Cons:

• Data Governance Lead position is a full time, dedicated role

• Working groups dynamics may require prioritization of conflicting business requirements

• Too many layers

Data Governance Steering Committee

Data Governance Office

Data Governance Working Group

Business Stakeholders IT Enablement

Data Governance Organization


pg 27

Operating Model - Federated

Pros:

• Centralized structure for establishing appropriate direction and tone at the top

• “Federated” Data Governance practices per Line of Business (LOB) to empower divisions with differing requirements

• Formal Data Governance Leads established per LOB to drive accountability

• Working Groups at the LOB level create broad membership, facilitating collaboration and consensus building

• Empowers LOBs while maintaining a level of centralized efficieny

• Pushes down decision making

• Ability to focus on LOB-specific data entities and activities

• Issues resolution at the local level

Cons:

• Too many layers

• Autonomy at the LOB level can be challenging to coordinate

• Difficult to find balance between LOB priorities and Enterprise priorities

Enterprise Data Governance Steering Committee

Enterprise Data Governance Office

Federated DG Practices

DG Office

Data Governance Organization

Working Group

DG Office

Working Group

DG Office

Working Group

DG Office

Working Group

LOB 1 LOB 2 LOB 3 LOB 4

Data Governance Council


Operating Model Roles and Responsibilities

Data Governance Steering Committee − Provides overall strategic vision − Approves funding, budget and resource allocation for strategic data projects − Establishes annual discretionary spend allocation for data projects − Adjudicates intractable issues that are escalated − Ensures strategic alignment with corporate objectives and other business unit initiatives

Data Governance Office − Chairs the Data Governance Steering Committee and Data Governance Working Group − Acts as the glue between the Data Governance Steering Group and the Working Committee − Defines the standards, metrics and processes for data quality checks, investigations, and resolution − Advises business and technical resources on data standards and ensures technical designs adhere to data architectural best practices

to ensure data quality − Adjudicates where necessary, creates training plans, communication plans etc

Data Governance Working Group − Governing body comprised of data owners across Business and IT functions that own data definitions and provide guidance &

enforcement to drive change in use and maintenance of data by the business − Validates data quality rules and prioritize data quality issue resolution across the functional areas − Trains, educates, and creates awareness for members in their respective functional areas − Implements data business processes and are accountable to decisions that are made


Typical Roles

Business Steward

Data Owner

Data Steward

Data Quality Analyst

Business Analyst

Data Architect

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


Sample Data Governance Operating Model

pg 30

Direction

TBD

Executive Sponsor Business and IT

Business Steward Leads Service Vendor Management

Finance FP&A Sales

Market Strategy

Analytics

Data Governance Steering Committee

Finance (CFO)

International (President)

Global Services (COO)

IT (CIO)

Marketing (CMO)

Data Governance Office Data Governance Leads: Business and IT

Data Governance Coordinator

Management

Provides budget and resource approvals. Forum for issue escalation

Crafts the enterprise data strategy, including polices, processes and standards to ensure that data is managed as an asset

Executive Level

Management Level

Stewards data within their BU to ensure that the enterprise policies are applied

Tactical Level

Strategic Level Provides overall strategic direction, budget and resource approvals forum for issue escalation

Execution

Data Management IT Support Group

Data Quality Lead Metadata Lead

Data Architect

BI Delivery

Operations External Reporting

DGWG

Enterprise Architect

BA

Data Analyst IT Security

Privacy

Legal

Data Stewards

Risk

Centralized Data Steward Pool

Accounting


Data Governance Leadership Team

pg 31

Sample Multi-Domain Operating Model

Program Oversight & Direction

Executive Sponsor

Program Management DG Working Group Data Governance Program Management Team

DG Program Manager

DG Coordinator

Program Execution

IT Manager

Data Domain Owners

Business Data Leads Data Acquisition

Data Stewardship

IT Enablement

Supply Chain International Sales HR Finance IT Marketing

Customer Product Employee Vendor Supplier

DG Data Quality Manager


Keys to a Successful DG Organization

Governance team must contain members from multiple lines of business Ensures cross functional 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

limitations…

Team needs to meet on a regular basis Business is constantly changing Discuss new and emerging programs Current IT activities 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 tie-breaking

Clear lines of communication Regular interaction with executive management Ensure communication methods to enforce policies at the steward and stakeholder level Invite stewards, project managers, stakeholders etc to provide status updates on critical initiatives that

affect the data

Ensure the Operating Model fits the culture of the company



RACI Matrix

Definition of a RACI

A documented articulation of ownership and accountability clarifying who does what

Responsible: Those who do work to achieve the task

Accountable: Those who are ultimately accountable to the correct and thorough completion of the task

Consulted: Those whose opinions are sought via two-way communication

Informed: Those who are kept up-to-date on progress


Purpose

Clarifies Roles and Responsibilities at a detailed level

Ensures the proper people are involved in an activity or decision

− And Ensures that people agree to who should be involved in an activity or decision

Creates Accountability where other enforcement is unavailable

Ensures decisions stick

Reduces finger pointing


Variations on a RACI

RASCI

− Support: Provides resources to complete the task

− Is a greater level of detail

ACI

− When there is little or no delineation between the people who are “Responsible“ and who are “Accountable”

− Good for flatter org structures


Tips & Tricks

Only 1 person/group can be Accountable

− Many people can be Responsible, Consulted or Informed

RACI’s should be done for the main processes within DG (but can be done for just about anything)

Be as granular and specific in the tasks as possible

Ensure there is explicit participation and buy-in from the people/groups represented on the matrix

− The “A’s” are best to help complete the matrix

If organizational groups are indicated, be sure you know who within that group to involve


Sample RACI



Charter

Charter Components

Scope Vision Mission Objectives

Guiding Principles

Success Measures

Roles & Responsibilities

Decision Making Process

Logistics


Process

Vision

Mission Statement

Objectives

Alignment to Corporate Objectives


Vision Statement

• Is an image of the desired future • Should be inspirational, rich and evocative • High level and strategic The Data Governance Program will _____, which will have______ result, and impact the business by .

“We will have a best in class client and account data capability to facilitate the achievement of the company’s strategic objectives, create sustainable positive impact, and manage the risk of the business.”


Mission Statement

Mission statement should:

• Align to Corporate Strategy

• Coordinate people, process, and technology to enable the company to manage data as an enterprise asset

• Define the Data Governance standards, roles and responsibilities

Make Decisions and

Make Decisions Stick

Company would see: • Better understanding of purpose and

goals of Data Governance • Internalization of how one participates

in Data Governance • Consistent decision making using the

guidance of the mission statement • Alignment of the organization • Greater accountability

Cre

ate

s B

usi

ne

ss

Val

ue

“Create a culture where data is recognized as a corporate asset that is essential to effectively optimize customer relationships, manage risk, increase efficiency, and contribute to the profitability and growth of our company.”


Objectives

Objectives

Objectives are tactical goals

Action oriented – starts with a verb

Objectives actualize the Vision and Mission

What are the methods to accomplish the Mission

Objectives

Identify data owners within business and technology and make them accountable

Create a culture of ownership by enabling partners to understand their role in data quality and data protection

Internalize the process through training, change management, and communication

Create a centralized business and technology organization to manage client & product data

Employ people and technology to improve data quality


Example: Alignment with Corporate Objectives


Example: Mapping Mission To Corporate Objectives

Mission: Create a culture where data is recognized as a corporate asset that is essential to effectively manage customer relationships, manage risk, increase efficiency, and contribute to the profitability and growth of the company

Drives

• Through improved speed to delivery on: Product related enhancements, address change processing, online account access, etc. and increased accuracy in reporting the easier it is for our company to do business with Clients and Partners, which drives Client Satisfaction

• Better data helps Company to analyze the market opportunity and helps with cross-selling, risk mgmt. etc. which drives the ability to focus resources on Branding

• Elimination of redundant feeds, redundant data, redundant support, redundant maintenance, etc. will enable company to Execute on "what really matters", as well as creating similar efficiencies with technology assets, thereby reducing costs and creating opportunity to apply that spend in revenue-generating ways per the regional strategic marketing plans

• Higher quality, available data will enable Company to Execute through improved ability to deliver support applications, desktop tools and other capabilities currently impossible given Company’s "legacy" environment


Principles

Principles, Policies, Processes & Standards P

rin

cip

les

A statement that articulates shared organizational values, underlies strategic vision and mission, and serves as a basis for integrated decision making

Polic

ies Guidelines to

manage the data lifecycle, access, integrity and administration that codify the governance standards and principles

Stan

dar

ds Standards consist

of specific low level mandatory controls that help enforce and support the data governance policy(s).

Pro

cess

es

Principles are more basic than policy and objectives and are meant to govern both.

Principles are the result of an internal dialectic which may or may not involve fact-based logical reasoning. For a policy to be successful, it must be based on facts and reason informed by the principles of policy makers.

Step by step activities to implement policies, including requirements and monitoring


Guiding Principles

Definition: A statement that articulates shared organizational values, underlies strategic vision and mission, and serves as a basis for integrated decision making. Principles constitute the rules, constraints, overriding criteria, and behaviors by which an organization abides in its daily activities in the long term.

This is the reference point from which all the future decisions will be made and is an important first step in creating a Data Governance program and will drive future decisions


Categories

Data as an Asset

Value

Quality

Accountability

Audit

Risk

Survivability


Example: Alignment with Corporate Objectives


pg 52

Example: Tie Principles to Corporate Objectives

Corporate Objective Principle

Client Data is a key asset to our company. We will enhance and manage this asset by emphasizing clear strategies, decisive action, innovation and results.

Capabilities Business stakeholders will get information delivered at the right time, location and amount as efficiently as possible.

Execution Data Governance will introduce, support and drive standardization 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 productivity through centralized, streamlined processes and eliminate non-value added activities. Maximizing automation is a key way to improve human resource efficiencies and is preferable over manual processes.

Principles drive creation and execution of policies, standards, processes, etc….



Policies

Policies

A method for codifying the Guiding Principles

Guidelines and standards to mange the data lifecycle, access, integrity and administration

For example:

− Data creation

− Data remediation

− Data retention

− Security and classification

− Data element definition


pg 55

Creating Policies

DGWG Lists the req’d Policies

Prioritize based on

value or BIR

Identify sub-teams and Assign

Reference the Guiding Principles

Ensure it’s measurable

Write per the Policy Standard

Monitoring

Escalation

Governance/ Oversight

Supporting Documents (Definition of Terms, Processes, Standards)


Policy Statement

Background/ policy rationale

Policy Scope

Roles & Responsibilities (RACI)

Components of a Policy

Policy Overview

Policy Statement Policy Description Intended Audience

Business Processes Impacted

Date Created

The policy statement in plain, easy to understand language

High level description Organizational Scope, target audience and user

Which business processes does this affect, existing or new

When policy was created

The new account creation policy will reduce duplicate records through a unified point of service.

All new Customer Accounts, new Customer Account records, and Customer Account updates are created by a single point of service, either a department or a data service

Sales, Marketing and Order Entry

New account creation in the CRM system; order entry for a new customer

August 18, 2015


Policy Detail

Policy Statement Policy Scope

Roles & Responsibilities Monitoring Escalation Oversight

The policy statement in plain, easy to understand language

What is covered by this policy

Identification of the roles played by everyone affected by the policy

An explanation of how compliance is monitored

An explanation of how to handle out of compliance situations

Situations under which this policy is reviewed

The new account creation policy will reduce duplicate records through a unified point of service.

All new Customer Accounts, new Customer Account records, and Customer Account updates

Sales, Marketing and Order Entry send a request to the DG group with the necessary information. DG group creates new account within 24 hours.

New account creation has been removed except for a limited number of authorized people. Turnaround time measured via audits of date stamps.

Any inquiry for additional info needs to be made within 6 hours. Any requests for new account creation outside of the policy needs approval.

Policy will be reviewed if order entry SLA is impacted.


pg 58

Policy Sample – Slide 1 of 2


pg 59

Policy Sample – Slide 2 of 2


pg 60

Sample Policy – Slide 1 of 2


pg 61

Sample Policy – Slide 2 of 2



Standard Processes

Processes

Tasks to implement the Policies

Are not Procedures or system specific

Can be “fine-tuned” per different lines of business

For Example:

− Exception/Duplicate Handling

− Issues escalation and resolution

− New/Update Data Element

− Data Reconciliation

− Data Synchronization

− Project/PMO Adherence

− Company Merger


pg 64

Creating Processes

DGWG Lists the req’d Processes

Prioritize based on Policies

Identify Sub-teams and Assign

Reference the Policies

Ensure it’s measurable

Write per the Process

Standard

Monitoring

Escalation

Governance/ Oversight

Supporting Documents (Definition of Terms, Forms, Checklists, etc.)


Process Description

Background/ process rationale

Process Scope

Roles & Responsibilities (RACI)

Components of a Policy

Sample Exception Handling Process

Invalid Address, Invalid Lookup, Missing Parent, Invalid Relationship/Hierarchy, Invalid data type, Data length error etc


pg 66

Sample Data Governance Intake Model (Front Door)


Functional Rep

Go to Rep On

DGWG

Functional Teams

Qualification Process

Project(s) Project(s) Project SDLC

Project(s) Project(s)

Maintenance Releases

(Bugs, Quick Wins and Minor Enhancements)

Support & Maintenance Track

Quarterly Releases**

Quarterly/Major releases

Intake All requests

to be entered into Case Management Solution

Enhancements or

Ideas

Production Issues (Helpdesk)

Business Strategy

Drivers

Sales/Sales Operations

Channel Sales / Partner Ops

Strategic Alliances

Sales Strategy / M&A

Emerging Products

Finance/Finance Ops

Customer Service

IT Partnership

Submission Qualification/Prioritization Execution

Project Track

Establish Frequency

Establish Frequency Project Prioritization with Leadership/ Communication back to Business


Change Management Plan

Data Governance Means Change

Successful DG means a change to the information management culture, processes and policies

Changing that culture means that you are asking people to think and behave differently about how data is accessed and used

You need an organized and systematic way to manage and sustain those changes – or there is marginal likelihood of success


Two Sides to Change Management

WHO? WHAT? WHEN? WHERE? WHY?

Something old stops, and something new starts

Relatively easy to plan for and anticipate

SITUATIONAL

It’s important to help affected individuals let go of the old situation and get comfortable with the new way

Everyone processes at a different rate and are rarely aligned with the milestones of the implementation plan

REORIENTATION PEOPLE GO THROUGH AS THEY COME TO TERMS WITH THEIR NEW

SITUATION

PSYCHOLOGICAL


It’s important to help affected individuals let go of the old situation and get comfortable with the new way

Everyone processes at a different rate and are rarely aligned with the milestones of the implementation plan

For change to be successful, BOTH sides need to be addressed

pg 69

Getting People through Change Successfully Requires….

Clear definition of what is changing

− Make sure the new behaviors, skills and attitudes are clearly defined and communicated

− Provide examples, training and allow time for practice

Attention to feedback:

− What are people saying and how are you addressing it?

− You must respond to feedback; be sure and attach the actions you take to the feedback you received so that associates know you are listening

Some reward or recognition structure to encourage new behaviors

Measurement and performance management


Change Management Phases

Implementing/ Sustaining

Change

Managing Change

Planning for

Change

Organizational alignment implemented Structure Jobs/people Policies/procedures Incentives Performance management

Change integration/adoption assessment

Communication plan execution Training development and delivery Feedback and analysis of results Leadership alignment checkpoint Measurement approach & metrics Organizational impact analysis Resistance management Implementation checklist development

Information gathering and analysis Stakeholder Analysis Sponsorship development Change plan development Leadership alignment checkpoint Communications planning Training needs assessment and planning


Meet with Program/Project Manager, and lay out CM Approach for the Program/Project

Monitor & Refine Extend

Change Management Alignment to DG Phases


****Communication Launch

Information Gathering and Analysis

Stakeholder Analysis/Loss Analysis

Change Readiness Assessment

Leadership Alignment

Sponsorship Development: Assessment and Road Map

Detailed Change Planning

Communication Plan

Operationalize Implement Strategize & Plan Assess & Align

Project

Initiation

Planning for Change

****Collect, Analyze and Report on Feedback

Implementation Checklist

More Leadership Alignment

Metrics and measurement

Org Impact Analysis: structure, jobs, training, policies

Managing Change

****Lesson Learned Assessment

Organizational Alignment Action Plan

Change Integration Checklist

Transitioning to the Business

Implementing/ Sustaining Change

pg 72


Measurement Dashboard

Why are Metrics Important?

Alignment

Rele-vance

Value


pg 75

Aligning Benefit to Value

Benefits of Data Governance

• Data lineage and auditability

• Improved data transparency and quality

• Repeatable processes and reusable artifacts

• Consistent definitions

• Appropriate use of information

• Collaboration among teams, business units, etc..

• Accountability for information use

• Quality of all data types

• Easier sharing of information

• Visibility into the enterprise via data

• Information security

Content property of IMCue and FSFP, Copyright 2013 Reproduction prohibited © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

pg 76

Impact Determines Success

Issues

• Report Quality and Accuracy

• Low Productivity

• Regulatory Compliance / Audit Response

Goals

• Improve data’s usability

• Improve efficiency and productivity

• Reduce compliance / audit cost

Metrics/KPI’s

• Data Quality

• Data remediation time

• Effort to comply

Impact

• Improve client relationships

• Address new markets

• Improve productivity

• Improve analysis & decision making

Content property of IMCue and FSFP, Copyright 2013 Reproduction prohibited © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

Definition

Metric

− A metric is any standard of measurement

Number of business requests logged

Number of data owners identified

Percentage business requests resolved within agreed SLA, etc.

Key Performance Indicator (KPI)

− A Key Performance Indicator (KPI) is a quantifiable metric that the DG Program has chosen that will give an indication of DG program performance.

− A KPI can be used as a driver for improvement and reflects the critical success factors for the DG Program

A metric is not necessarily a KPI


pg 78

Metrics/KPIs examples

People

# of DGWG decisions backed up by the steering committee # of approved projects from the DGWG # of issues escalated to DGP and resolved # of data owners identified # of data managers identified DG adoption rate by company personnel (Survey)

Process

# of data consolidated processes # of approved and implemented standards, policies, and processes # of consistent data definitions Existence of and adherence to a business request escalation process to manage disputes regarding data Integration into the project lifecycle process to ensure DG oversight of key initiatives

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)



Creating Metrics

Process to Establish Metrics

pg 80

Issues

• What are the issues in your group?

• What do you mean by that?

• Why is it important?

• What are your objectives?

Goals

• What is the change you would like to see? What action?

• How will that change impact you?

• What is the impact if those objectives aren’t met?

Metrics/KPI’s • What processes are

involved in that change?

• How is information used in that process?

• What information is used? What data?

• What data improvements are needed?

Impact

• Positive change created by addressing issues

• Benefit of improving data to impact objective


Getting to Data Change Metrics

Issues/Objectives

Goals Information Data Data Change Additional Action

Report Quality and Accuracy

Improve Data Understanding

Accounts Client Information Reduce duplication of client data

Improve Data Transparency

Increase completeness of record

Reduce Manual Remediation

Track data lineage Ensure thoroughness of data sources

Products owned

Increase Completeness of record

Ensure thoroughness of data sources

Households Relationship

Groups


Sample Data Metrics

Data Change Measurement Target Frequency

Reduce Duplication of Client Data

% Duplication 1% Daily

Increase Completeness of Client Record

% Completeness of key fields 99% Daily

Track Data Lineage Completeness of lineage in metadata

99% Monthly

Ensure Thoroughness of Client Data Sources

Review of data acquisition 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 acquisition and ETL process

Business consensus

Quarterly

pg 82

Data Understanding

Data Transparency

Reduce Manual Remediation


Getting to Business Change / Impact Metrics

pg 83

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 Remediation Time to complete report process (baseline is 6 days) 1 Day Monthly

Increase Report Quality and Accuracy

Improved Business Stakeholder Satisfaction Survey Reduced Issue Requests

Business Approval 10% drop

Quarterly Monthly

This is your KPI © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential

BU 2 SCORECARD

BU 4 SCORECARD

BU 1 SCORECARD

BU 3 SCORECARD

DATA GOVERNANCE SCORECARD

(FUTURE STATE) STRATEGIC VIEW

OPERATIONAL SCORECARDS

CONSOLIDATED BY BUSINES UNIT

SE

TU

P

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

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Attribute level Supports Operational Use Case

Entity Level Supports Company Data Governance

(Strategic Value)



Communication & Training Plan

Why is Communication Important?

pg 86

Creates Awareness

Aligns expectations

Creates an opportunity for feedback / engagement

Proactively addresses Change

Publishes Success

Answers the questions “Why?” and “What’s in it for me?”

Aligns activities


Translating Data Value into Business Value

Communication 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 information do you need to track and measure to those goals?

Translate the value statement into the language of the recipient


• Engagement Strategy: • Focused effort must be given

to high priority groups

• Provide sufficient level of information to less influential groups to ensure buy-in

• Move people and or groups to the right by trying to increase their level of interest

• Forms the foundation of your engagement / communication strategy

pg 88

Stakeholder Engagement Strategy

Meet

Their Needs

Key

Player

Least

Important

Show

Consideration

Stakeholder Influence

Stak

eho

lder

Infl

uen

ce

Stakeholder Interest


Stakeholder Analysis Guide


What is a Communication Plan?

Communication Plan Definition

− A written document that helps an organization achieve its goals using written and spoken words.

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

Importance of a Communication Plan

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

− Helps stakeholders and the working team set priorities

− Provides stakeholders with a sense of order and controls

− Provides a demonstration 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


Communication Plan

Brings it all together:

− Who do we need to communicate to?

− What information 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 communication?

− Who should be communicating to them?


pg 92

Components of a Communication Plan

Communication Plan Stakeholder: XXX

Qualitative Information Any general qualitative information that I would like to receive related to this deliverable

Quantitative Information Of the quantitative 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 pertinent

Frequency How often do I want to be informed about progress

Method What is my preferred mechanism of receiving the information


pg 93

Sample Communication Plan 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 Presentation John 8/25/11 John Complete

DGWG Core Team Kickoff Meeting One-Time DGO kickoff and vision from IT Sponsor Kickoff DGWG-Core, IT Sponsor PowerPoint presentation John 9/15/11 John Complete

DGO Launch Logistics One-Time Communication announcing the DGO Plan 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 presentation John TBD John Not Started

DGO-DGWG Decision

(Core & Advisory) Meeting

Monthly DGWG voting meeting Vote and approve DGWG materials DGWG 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 presentation John 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 As needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started

Meeting with Product Implementation stakeholders As needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started

Meeting with Global Product stakeholders As needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started

DGO Town Halls One/Year DGWG accomplishments and progress towards goals

Forum for open discussion

Team Building All DGWG members PowerPoint presentation John TBD Flo Not Started

And these are just the meetings! Also: • Awareness & Training • Communication Vehicles • Knowledge Sharing •….


What is a Training Plan?

Training Plan Definition − A written document that helps an organization understand the requirements and

deliver the orientation, education and training needed to sustain Data Governance

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

Importance of a Training Plan − Ensures adequate attention is placed on awareness and training

− Builds the organizational understanding and skills needed to improve

− Prioritizes and assigns the work

− Articulates requirements over time to maintain the level of activity

− Gives individuals the opportunity to be successful in performing new roles and following new processes

− Creates a skilled workforce who can execute successfully DG initiatives identified

− Educates executives who understand and support managing data as an asset


Categories of Knowledge Transfer

Types Tracks

Orientation

• Understand vision, concepts and value proposition so one is visibly acting in support of a change or activity

Fundamentals • Basic, non-company specific knowledge of

topics related to and connected by DG

Education

• Ensure that the desired activity or change takes place from accountability and managerial view

EIM Program Tracks • Knowledge transfer for company version of

information management capabilities

Training • Ensure action takes place from the view of

those responsible for execution; “feet on the ground”

Work Stream Specific Tracks • Detailed knowledge transfer by roles, e.g.,

data steward


Sample DG Training Plan Level

Orientation Education Training

Class # - 1 - 2 - 3

Unit Unit # Level # Module Name Master the WHY;

Concepts & Value Master the WHY and

WHAT ; Actions, sequence, measures

Master the WHY, WHAT and HOW; Techniques,

tasks, tools

Abstract

n/a 002

1 DG Concepts Definitions, Value and

Concepts NA

2

DG Framework Principles and Standards; Best practices

NA

Data Governance Processes, Organizations

2

DG Orientation DG Road Map, Maturity levels, Policies and Measurements Framework, incl. Principles, Value and Vision

a. Audience: Business & IT Leadership b. Purpose: To present the DG program to familiarize employees c. Key Learning Objectives i. Describe DG program at the company wide and LDG levels ii. Discuss maturity levels, standard, principles

EIM Guiding Principles, Supporting Standards

EIM Principles Orientation

a. Audience: Leadership, Business line employees, IT b. Purpose: To present EIM principles and Supporting Standards within context of DG roadmap c. Key Learning Objectives i. Describe components of a standard and guiding principles ii. Discuss existing standards and guiding principles

Data Governance Processes, Organizations

3

DG Program Training DG Road Map, Specific supported initiatives,

detailed project plans and activities

a. Audience: Business & IT Leadership, business line employees, IT b. Purpose: To present the DG program to familiarize employees c. Key Learning Objectives i. Describe DG program at the company wide and local levels ii. Discuss initiatives, activities and overview of roles iii. Discuss initiatives, project plans and activities

EIM Guiding Principles, Supporting Standards

EIM Standard Training a. Audience: Council, DG functions - hands on workshop b. Purpose: To present an overview of standards and guiding principles, then actually define them c. Key Learning Objectives i. Describe components of a standard and guiding principles ii. Discuss existing standards and guiding principles iii. Construct a target standard and guiding principle

Business Glossary 103 1

Overview for leadership DG Framework, incl. Principles, Value and Vision

Using the Business Glossary - this could be technical on-hands training for managers or demo

a. Audience: Business Leadership b. Purpose: To give an overview of meta data, its importance and use c. Key Learning Objectives: i. Describe the role of meta data in organization ii. Define what meta data can do for in terms of usage iii. Practice hands on tool training or Administer demo of the Business Glossary


Business Data Glossary

What is a Business Data Glossary ?

A business glossary contains

1. Data Subjects: • A group of related elements, logically grouped for presentation and analysis

2. Data Elements • A grouping of data related to each other within a subject area

• A Data Element is a concept that is a the business level, not at the level of database implementation.

• Some Data Elements are designated as Critical, have a RACI, are governed, identify variant meanings and synonyms, are measured/monitored

A Business Data Glossary enables organizations to build and manage a common business vocabulary and make it available across the enterprise.

This vocabulary delivers meaning and context.


Purpose and Uses for Business Data Glossaries

Business Data Glossaries provide the structure to organize Critical Data Elements

− Provides focus for Data Governance and Data Quality

Critical Data Elements need to be defined for key business activities and initiatives

Data Governance decides if a data element is a CDE

Data Governance maintains a list of criteria that determine if a data element is a CDE.

By comparing a data element with this list, Data Governance can determine if the data element is a CDE.


Best Practices for Data Elements / Business Glossary

Have distinct names for each meaning. Concepts in business can be ambiguous and have more than one meaning

Include definitions in the business glossary to help identify variant meanings and ensure agreement among the stakeholders

Keep it simple, starting with known concepts and relationships.

Supply Attributes when resolving disagreements over entities and their relationships

Identify Synonyms: Words with similar meanings but with different names. When the same concept can be expressed by two or more synonyms, one of these is selected as the preferred term.


Sample Business Data Glossary


pg 102

Excerpt from A DG Glossary of Terms


It’s important to also agree upon Terms across a distributed DG Organization


Ensuring Success

Principle Description

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

Enterprise thinking Provide consistency and coordination for cross functional initiatives. Maintain an enterprise perspective 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 circumventing the process

Be deliberate on participation and process

Select sponsors and participants. Do not apply governance bureaucracy solely to build consensus or to satisfy momentary political interest

Enterprise wide alignment and goal congruence

Maintain alignment with both enterprise and local business needs. Guide prioritization and alignment of initiatives 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 communication will provide a mechanism for gauging when to “course correct”, manage stakeholder and effectiveness of the program

pg 104

Data Governance Design Principles


Thank you!

Kelle O’Neal

[email protected]

415-425-9661

@1stsanfrancisco


Top 10 Artifacts Needed For Data Governance

Data & Analytics

Transcript of Top 10 Artifacts Needed For Data Governance