Successful Strategies for Establishing &
Sustaining Global HR Data Governance
Melissa Vogel, Workforce Data & Analytics
General Mills
Brian Regan, Principal Consultant
DMR
September 17, 2015
Agenda
 Introductions
 Company Overviews
 General Mills HR Landscape: Where We Started
 HR Information Strategy: Where We Want To Go
 Project Profile: What We Did
 HR Information Strategy: What’s Next
 Wrap Up
Introductions
Melissa Vogel
Brian Regan
Sr. Manager – Workforce Data & Analytics
Principal Consultant
With over 15 years of experience in HR, HR Shared
Services, and HR Technology, Melissa works closely with
clients at all levels of the business to build the
capabilities required for HCM insights and data quality.
Previous roles have included the global implementation
of SAP® HR in over 40 markets and the evolution of HR
Service Center to a Global Shared Service Organization.
Data management professional with over 15 years
experience in data governance, conversion, architecture
and program management. Supports large-scale
organizations with enterprise data strategy, legacy
system consolidation, data quality systems, and
business intelligence.
melissa.vogel@genmills.com
brian.regan@datamigrationresources.com
About DMR
Expertise:
•
•
Founded by industry experts 100% focused on data
governance, data quality & migration at large organizations
Decades of experience in large global HCM deployments
Methodology:
• Developed by data management leaders
• Focused on enterprise scale migration & governance
• Faster deployment, higher data quality
Technology:
• Proven experience with leading ETL, EIM and Governance tools
• DMR accelerators for profiling, construction, validation
4
General Mills at a Glance
• One of the world’s largest food companies
• Products marketed in more than
100 countries on six continents
• 42,000 employees
• $17.6 billion in fiscal 2015 net sales*
*Consolidated net sales excludes $1.1 billion of joint venture sales
General Mills Brands
Our Brands
Agenda
 Introductions
 Company Overviews
 General Mills HR Landscape: Where We Started
 HR Information Strategy: Where We Want To Go
 Project Profile: What We Did
 HR Information Strategy: What’s Next
 Wrap Up
Our Journey with HR Technology
Initial Focus Areas:
 Domestic
 Administrative processing
 Focus on data integrity
Implemented SAP HR – focus on
compensation, benefit and payroll
processing , organization hierarchy
(US & Canada Salary)
SAP Enterprise
Compensation
SAP
Rollout of Basic
SAP HR Globally –
Employee Master
Data
2000 2001 2002 2006 2007 2009 2010 2011
Integration of Pillsbury
organization and
employee data
Added
Canada Wage
Employee Data
SAP HR Succession:
Global Succession
Planning
2012 2013 2014 2015
SAP eLearning: Global
Learning Catalog
Rollout G&Me –
SAP eRecruting:
General Mills Portal:
Early Employee &
Manager Self-service
Applicant Tracking &
Candidate Portal
Going Forward




SaaS
Talent Focus
Information & Knowledge
Direct Access
• Domestic
• Global
• Payroll/Benefits
• Talent, Analytics, Insights
• HR Process Support
• Permeates Organization
• HR is the Consumer
• Business Is Consumer
• Typical “Employee”
• Human Capital
• Transactional HR
• Business Partner
SAP® Data Challenges: A Decade Later
Global Data Not Trusted



International markets not entering transactions timely
High frequency of retroactive transactions
Very little trust in global headcount reporting
Cross-System Inconsistencies



HR data used in many downstream systems
Highly complex system landscape
Data out of sync across key GMI systems
Transaction Processing Inconsistencies



Inconsistent maintenance of Talent appraisals
Identification of payroll overpayments or inaccuracies
Local data inconsistently maintained by countries
Agenda
 Introductions
 Company Overviews
 General Mills HR Landscape: Where We Started
 HR Information Strategy: Where We Want To Go
 Project Profile: What We Did
 HR Information Strategy: What’s Next
 Wrap Up
GMI HR Information Strategy
Ensure accurate, globally consistent information
needed to make strategic and differential decisions
while mitigating risk of legal & regulatory exposure
Establish
HCM Data
Governance
Scale HR
Data for
Broader
Workforce
Improve Data
Definitions
Protect
Confidential
Employee
Data
Manage
Dissemination
of HR
Information
Roadmap
Data Quality
(foundation)
F14-15
 HCM Governance
Framework
 Improve Data Quality
 Risk Mitigation
Reporting
(static)
Dashboards
(dynamic)
F15
 HR Reporting Optimization
 Executive Scorecards
 Enterprise Data Access
 Business Data Glossary
 Landscape Mapping
Analytics
(predictive)
F16+
 Standard Data
Definitions
 Workforce Data
Architecture
 Reporting & Analytics
COE
Change Management
 New HCM Technology
 Support HR
Transformation
Roadmap
Data Quality
(foundation)
F14-15
 HCM Governance
Framework
 Improve Data Quality
 Risk Mitigation
Reporting
Key
(static)
Dashboards
Analytics
Drivers
for
Data
Trust
(dynamic)
(predictive)
1. Visibility &
Awareness–
F15
a. Identify the Issues
b. Decide
What’s Important
 Standard Data
 HR Reporting
Optimization
c. Socialize
Definitions
 Executive Scorecards
 Workforce Data
 2.Enterprise
Data Access
Architecture
Establish
Accountability
–
F16+
 New HCM Technology
 Support HR
Transformation
a. Data
Identify
Decision Makers
 Business
Glossary
 Reporting & Analytics
b.
c.
Formalize Governance
COEProcesses
Educate Stakeholders
 Landscape Mapping
3. Transform
Change– Management
a.
b.
Define Common Global Language
Implement Technologies for Data Quality & Information
Delivery
Agenda
 Introductions
 Company Overviews
 General Mills HR Landscape: Where We Started
 HR Information Strategy: Where We Want To Go
 Project Profile: What We Did
 HR Information Strategy: What’s Next
 Wrap Up
GMI Data Quality Solution
Technical Landscape
SAP
HCM
COE & SSC
•
Multiple live instances (SAP, AD, etc.)
•
HR data extracted into DQ system
•
Audits developed to validate data both
within SAP and across systems
AD
Business Value
COE
Workflow & Control
Data Quality Monitoring
Corp
HR
•
All audits in central solution
•
Security by role and organization
•
Violations go directly to data owners
•
Dashboards to monitor progress
Data Governance Management
Key Dashboards



System consistency
Timeliness by region
and country
Errors by country


Errors by stakeholder
Errors by business outcome
Timeliness Executive Summary
Timeliness Executive Summary Details
GMI Governance Solution: Schedule
Wave-Based Development



4 development waves
70-80 audits per wave
1 additional wave for dashboards
Wave Structure


2 weeks agile development
1 week business owner validation
Success Enablers


Iterative development model
Lightweight spec process
Data Governance Outcomes
Key Outcomes



Cost Savings
System Consistency
Legal Compliance



Payroll Processing
Global SAP Data Health
Talent Data Health
SAPHR Timeliness % by Region
New Hire & Separation Entries
New Hire Entries
AMEA
Entries Processed
Processed Late
Canada (Non-Plant)
Entries Processed
Processed Late
Europe & Australasia
Entries Processed
Processed Late
Greater China
Entries Processed
Processed Late
Latin America
Entries Processed
Processed Late
US Based Business
Entries Processed
Processed Late
Separation Entries
Baseline
F15 Q1
F15 Q2
F15 Q3
Baseline
F15 Q1
F15 Q2
F15 Q3
46.7%
83.3%
73.1%
70.8%
21.0%
47.6%
26.7%
39.4%
276
147
114
19
130
35
113
33
381
301
124
65
105
77
104
63
98.2%
100.0%
100.0%
100.0%
79.7%
88.9%
55.6%
84.2%
56
1
15
0
21
0
17
0
59
12
27
3
9
4
19
3
74.0%
86.7%
92.8%
71.4%
59.8%
70.1%
56.5%
70.8%
408
106
286
38
221
16
182
52
358
144
164
49
246
107
113
33
30.4%
43.3%
53.0%
77.5%
30.3%
61.6%
57.6%
86.1%
1148
799
356
202
370
174
315
71
792
552
268
103
314
133
317
44
75.7%
65.4%
58.2%
65.6%
46.6%
34.0%
46.6%
51.0%
173
42
104
36
98
41
61
21
234
125
94
62
88
47
98
48
99.7%
99.6%
99.8%
99.7%
61.9%
81.6%
80.8%
77.3%
1923
6
532
2
436
1
344
1
2562
975
819
151
608
117
587
133
% of entries processed within 3 days of new hire/separation (7 for HD Shops)
Red = < 80%
Yellow = 80 – 99%
Green = 100%
Project Lessons Learned
Focus on small wins

Dashboards provide high-level understanding of issues

Identify key measures, build from top down

Phase project, allow for socialization and feedback
Stabilize the audit list very early in project

300 audits is probably too many

Organization will only be able to process finite number of quality improvements

SME’s are likely core project team members – acknowledge time constraints
Governance Organization for GMI HCM
OPERATIONAL FOCUS
ENTERPRISE FOCUS
Enterprise Data Leadership Team
Sales Data
Trustee
Model
Supply Chain
Data Trustee
Model
FI Data
Trustee
Model
HCM Data
Trustee Council
Business HR Reps
HCM Data Steward Working Group
GBS HCM Data Team
Provide Authority, Goals, Sponsorship &
Accountability
Execute Strategy, Ensure Quality, Resolve Issues
and Overall Coordination
Organization framework is scalable to support Trustee models for other GMI
business units in a future state e.g., Finance, Supply Chain, Marketing, Sales, etc.
Agenda
 Introductions
 Company Overviews
 General Mills HR Landscape: Where We Started
 HR Information Strategy: Where We Want To Go
 Project Profile: What We Did
 HR Information Strategy: What’s Next
 Wrap Up
What’s Next
Select SAAS HCM Solution
HCM Information Strategy Pillars
Leverage HR Transformation Project
 Transform HR to data-driven discipline
focused on insights
 Remediate data creation processes
(shared services, payroll)
 High quality data conversion and
system consolidation
• Repository for
Data About
Data
• Data & System
Architecture
• Strategy
Oversight &
Development
• People Talking
to People
• Managing Data
• Automated
Workflow Tools
• Distribution
• Visibility To
Erroneous Data
• Data Quality
• Compliance
HR Transformation
Transform the way we do HR by implementing best in class
Core HR Applications to deliver…
STANDARDIZED
PROCESSES
• Industry defined
• Minimal exceptions
• Rapid deployment of process
globalization
•
•
•
•
Performance & Incentive
M&A Simplification
Reporting
Future Initiatives
• Simplified data management
• Vendor managed compliance
updates
•
•
•
•
INSIGHTS & ANALYTICS
Easy access to valid HR data globally
Decision-making information embedded into all processes
Shift HR focus from data validation to talent, organization, insights
Continuous visibility to talent pipeline for planning purposes
CONSUMER GRADE
USER EXPERIENCE
• Anytime, Anywhere, Any Device
• Global Employee, Manager and
HR Self Service
•
•
•
•
RIGHT WORK,
RIGHT TALENT
Minimizes HR admin tasks
Decreases HR onboarding time
Enables Regional Service Ctrs
Significant reduction in IT
landscape/resources
27
Our HR Transformational Journey
FROM
TO
•
US-Centric Approach
•
Truly Global Data & Capabilities
•
Decentralized Headcount
Control
•
Central Control & Visibility to
Spend
•
Qualitative Analysis
•
Data-Driven Decision-Making
•
US Transactional Service Center
•
Global Delivery Model
•
High-Touch Model
•
High Touch Where it Matters
•
Conditioned to Wait
•
Empowered to Lead
•
Activity Focused HR
•
Impact Obsessed HR
28
Preparing for HCM Transformation
Assess
Prepare
Global Resource
Plan
Execute
Global Team
Formation
System Selection
Future State
Architecture
Solution Scoping
Business Process
Design
Legacy System
Connectivity
System Profiling
Global
Design
Data Integration
Strategy
Data Migration
Strategy
Data Archiving
Strategy
Reporting
Strategy
Infrastructure
Deployment
Legend
Data Readiness Assessment
Organizational Assessment

Data Conversion Specific Roles

Data Role Mapping: Steady-state governance to project organization

Data Role Mapping II: Project organization to post-transformation organization
System Inventory

HCM System Inventory: 50+ systems apart from SAP HCM

System Metadata Collection: Owners, Data Objects, Contracts, Interfaces

System Impact Analysis: Conversion inventory, Interface inventory
Technology Assessment

Conversion Tools: 10 key technologies for successful data projects

Gap Analysis: Identification of key assets or holes in landscape (e.g. archiving)
Agenda
 Introductions
 Company Overviews
 General Mills HR Landscape: Where We Started
 HR Information Strategy: Where We Want To Go
 Project Profile: What We Did
 HR Information Strategy: What’s Next
 Wrap Up
Key Takeaways: Playbook
 Create awareness
 Build that awareness with technical solutions
 Build stewardship organization (educate)
 True transformation is not system replacement. It is an
overhaul of HR practices to be informed by data.
 The data is what enables the next-generation technologies to
create true transformation opportunities.
Questions