how to structure the data organization

Confidential and Proprietary. All rights reserved Copyright© 2015. DATUM LLC

How to Structure the Data OrganizationData Governance Winter Conference

Stacey Stewart – Johnson & Johnson Healthcare Systems Inc.David Woods – DATUM LLC


• Global Leader in Healthcare• Consist of more than 250 Operating Companies• Sell Products in over 175 Countries• 128,000 Employees Worldwide

We Proudly Serve

• Fast-Growth Solutions Company Recognized by Inc. 5000

• Named Leader in Data Governance 2.0 by Forrester• 70% of ASUG Data Governance 2014 SIG Annual Meeting

“Success Stories” are users of our Solutions


Data Organizational Challenges

The Data Governance Call-to-Action:

• Where to start …• Efficiency focus – “do more with less”• Ability to quickly scale and adapt through growth,

acquisition or divestiture• Fragmented systems, processes and data• Disparate BU’s and Regional / Local Data Teams• Increasing Focus on Big Data (unstructured)

contradicts traditional techniques and skills

Common Points of Failure:

• Project-Focused mindset (lack of a scalable model)• Inability to link the Business Value to the Program• Thinking Org Model and not Operating Model


EMDM Building Blocks and Core Components

1. Data Governance Organization

(Accountability, Discipline, Structure)

2. Data Governance Boards (Composition, Focus,

Representation)

3. Aligning the Rest of the Organization

4. Setting Expectations (For all Parties)

Business accountability for master data and appropriate Org Structures for data maintenance.

Business rules for data, accessible by providing it, and consistent across relevant business processes

Processes to ensure standards are assessed, docuemented and

managed for consistency

Tools to capture, monitor and enforce data standards and

business rules for master data

Sustainable Data

Integrity

UNDERSTANDING DATA ORGANIZATIONS


Best in Class Organizations Utilize 3 Levels of Ownership

Data Management Support

IT, Data Center of Excellence, Business Support

Operational Data GovernanceData SME - Business Data Governance Program

Leadership Data SME - IT

Business OwnershipBusiness Data Owner

(Mgmt-Level Business Owner)Operational Data Owner(Sub-Process Leadership)

“Next Level’

leadership with the

ability to make

organizational,

portfolio and funding

decisions while also

influencing projects

Manages the tactical

activities and support

requirements for data

and related processes

Strategic support for data management initiatives ensuring alignment with vision, goals and objectives

Level of organizational ownership that actively ‘owns’ and

‘manages’ the data management program and people


Partnership and Collaboration is Critical

• Define data standards• Identify business scenarios• Identify Business Rules• Define data maintenance roles • Define governance roles• Utilize the system• Prioritize focus areas• Define Business Metrics

• Infrastructure• Application configuration• Deployment• Targeted Cleansing• Metric Dashboards• Support / SLA’s

Successful programs maintain a balanced effort between the Business and IT

Technical Execution

Business Discovery/Definition/Ownership


Evaluating Data-Centric Operating Models

Organizational Data Maturity

Auto

mat

ed D

ata

Gove

rnan

ce

Process- Based Governance

Decentralized

Centralized

Distributed(Hybrid)

Resource Dependent Solution

The ideal organizational model design for ‘data’ will typically change as the organizational competencies evolve,

data governance techniques are applied, and the data IT application

capabilities mature


No Data Governance

Evaluating Data Governance Models

Data Quality and Awareness

Auto

mati

on

Error Remediation Tim

e

Predictive

Active

Process

Business Interruptions

Each of these data governance methods are valid – the ‘key’ is

ensuring that the organizational model complements (and certainly

doesn’t contradict) the data governance strategy


Ensure a Complementary Governance Strategy

Distributed / Predictive Centralized / Process

Plant 1

Plant 3Plant 2

Central HQ

Decentralized / Active• Non-critical or closely governed data

maintenance processes• Local autonomy & decision-making• MDG PoE or no governance

Ex: Create P-Req, Assign Bin

• Role(s) centralized within a BU, Plant, location or function • Critical data requiring expertise,

control and governance

• Ex: Transportation, Planning Data

• Role(s) centralized across all locations (impacts all)• Critical data requiring centralized

expertise, control and governance

• Ex: Maintain G/L, Payment Terms


Enterprise Data Governance Boards

Enterprise Data StewardsQ&C

IT RepresentationRegional Data

Mgmt Leadership

Business Unit Representation (Pharma, MD&D,

Consumer)

Global Process Representation

(Plan, Source, Make, Deliver, Finance)

ESTABLISHING THE OPERATING MODEL


Seizing the Opportunity

Who will provide the data?

What data is required ?

When will the data be utilized?

Where must the data be triggered?

How will the data be measured?

“How do we get there?”By understanding

(identification and visibility)“How do We Drive Business Value with Data?”

OperationalEfficiencies

Compliance Adherence

Analytical Insights


A Unified Platform is Critical

How do we effectively …• Capture actionable information from

different experts, systems, regions, functional areas and formats?

• Have a sustainable platform to establish our data governance strategy and accelerate implementation?

• Ensure sustainability after implementation?

Governance Strategy Project Execution(Tools, Processes & Procedures)

Decentralized Data Governance Knowledge

Platform for Data Governance Collaboration

Data and Implementation Teams


Operating Model ConstructionWe typically see three (3) methods of forming a Data Governance Organizations – each one has benefits and risks, which need to be carefully considered

• Net-New: Formation of an entirely new organizational entity focused on data and information governance.

• Lift & Shift: Identify existing, data-centric organizational constructs and repurpose them into a formal governance operating model.

• Leverage Existing: Augment an existing organizational governance model to include data and information governance.

DataGovernance

Operating Model


Two Paths to Development

Data managed at business unit,

regional, and local levels

Data managed at business unit,

regional, and local levels

Critical data aligned and

centrally governed across the enterprise

Align on a vision, execution strategy, priorities, ownership, accountability, tools and coordinate

efforts across all organizations and projects

Local data managed regionally (following enterprise

model)

Align on a vision and organizational construct, but allow the model to evolve through individual

deployments, disparate approaches and indirect ownership of priorities and execution strategy

Alternative Approach• Program Based• Direct• Deliberate• Measured• Purposeful

Traditional Approach• Evolution Based• Indirect• Reactive• Tacit• Function Driven


Defining the Data Steward Role

Data Steward Primary Responsibilities: Ownership for the development and

Implementation of Data Standards, Business Rules, Policies and Procedures

Driving Strategic Master Data Initiatives across the Enterprise in Collaboration with Business & IT Leadership

Monitoring Performance Measures & DQ Metrics

Managing the Demand / Approval for Changes to Existing Governance Procedures

Developing and Coordinating Strategic Training Plans and Training Materials

Supporting business functions to ensure Data Quality Procedures are being followed

Data Stewards are NOT responsible for… Day-to-Day Master Data Maintenance Activities Mass Creation or Change Requests Execution of Data Quality Reports Performing Ad Hoc Data Clean-up Tasks

ALIGNING THE ORGANIZATION


4. How Many?3. How?2. Who?

Operating Model Alignment Key Points

Who should perform these tasks?

• Ownership• Business vs IT• Roles• Contextual Knowledge•Maturity of tools for

automation

How should the operating model be aligned to best support these activities?

• Central, Distributed, Hybrid, Decentralized• Cultural Challenges• Funding/Costs• SLA’s & Plant needs

How many resources are required?

• Data Volumes• # of Reqs• SLAs• Complexity• Tool Maturity

1. What?

What are the tasks and activities we manage?

• Data Maintenance• Data Governance• Data Quality• Other


Understanding Your Company Culture

Organizational Charts drawing by Manu Cornet, http://www.bonkersworld.net

http://www.bonkersworld.net/


Operating Model

Enterprise Data Steward (EMDM)

Enterprise Data Stewards exist for the Material, Customer, Supplier and Finance Domains

Regional Data Management Leaders are defined as a Central POC for each Region (cross business unit responsibility)

Regional Data Management coordinates across data department SME’s


Data Management Leadership


The business needs to change, but so do we…

As your program continues to evolve, your organization will not only need to develop new competencies, but an entirely new perspective

Improve your Business Skills

Focus on Business Value not

Application Value

Create a Business Model for your Data Management Organization

Apply New Tools and Innovate

(Disruptive Innovation)

Think Business Architecture,

Not Data Architecture and Develop those Skills


Stacey StewartWorldwide Director, Enterprise Data ManagementJohnson & Johnson Healthcare Systems [email protected] (m)

David WoodsPrincipal Partner, EIM StrategyDATUM [email protected] (m)

Thank You & Questions

mailto:[email protected]

mailto:[email protected]