Successful Strategies for Establishing & Sustaining Global HR Data Governance

Melissa Vogel, Workforce Data & AnalyticsGeneral Mills

Brian Regan, Principal ConsultantDMR

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

Principal Consultant

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.

brian.regan@datamigrationresources.com

Introductions

Sr. Manager – Workforce Data & Analytics

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.

melissa.vogel@genmills.com

Melissa Vogel Brian Regan

4

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

About DMR

*Consolidated net sales excludes $1.1 billion of joint venture sales

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*

Our BrandsGeneral Mills 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

Added Canada Wage Employee Data

SAP Enterprise Compensation

2001 2002 2006 20072009 20102011 2012 20132000Integration of Pillsbury organization and employee data

Implemented SAP HR – focus on compensation, benefit and payroll processing , organization hierarchy (US & Canada Salary)

Initial Focus Areas: Domestic Administrative processing Focus on data integrity

Rollout G&Me – General Mills Portal: Early Employee & Manager Self-service

2014

SAP HR Succession: Global Succession Planning

Going Forward SaaS Talent Focus Information & Knowledge Direct Access

SAP eRecruting: Applicant Tracking & Candidate Portal

SAP eLearning: Global Learning Catalog

SAP

Rollout of Basic SAP HR Globally – Employee Master Data

2015

SaaS HCM

Solution2015-2017

• Domestic

• Payroll/Benefits

• HR Process Support

• HR is the Consumer

• Typical “Employee”

• Transactional HR

• Global

• Talent, Analytics, Insights

• Permeates Organization

• Business Is Consumer

• Human Capital

• Business Partner

SAP® Data Challenges: A Decade LaterGlobal 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 Governanc

e

Scale HR Data for Broader

Workforce

Improve Data

Definitions

Protect Confidential Employee

Data

Manage Disseminati

on of HR Information

Data Quality(foundation)

Reporting (static)

Dashboards (dynamic)

Analytics (predictive)

F14-15 F15 F16+

HCM Governance Framework

Improve Data Quality

Risk Mitigation

HR Reporting Optimization

Executive Scorecards

Enterprise Data Access

Business Data Glossary

Landscape Mapping

Standard Data Definitions

Workforce Data Architecture

Reporting & Analytics COE

New HCM Technology

Support HR Transformation

Change Management

Roadmap

Data Quality(foundation)

Reporting (static)

Dashboards (dynamic)

Analytics (predictive)

F14-15 F15 F16+

HCM Governance Framework

Improve Data Quality

Risk Mitigation

HR Reporting Optimization

Executive Scorecards

Enterprise Data Access

Business Data Glossary

Landscape Mapping

Standard Data Definitions

Workforce Data Architecture

Reporting & Analytics COE

New HCM Technology

Support HR Transformation

Change Management

Roadmap

Key Drivers for Data Trust 1. Visibility & Awareness–

a. Identify the Issuesb. Decide What’s Importantc. Socialize

2. Establish Accountability – a. Identify Decision Makersb. Formalize Governance Processesc. Educate Stakeholders

3. Transform – a. Define Common Global Languageb. 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• Multiple live instances (SAP, AD,

etc.)

• HR data extracted into DQ system

• Audits developed to validate data both within SAP and across systems

Business Value

• All audits in central solution

• Security by role and organization

• Violations go directly to data owners

• Dashboards to monitor progress

COE & SSC

COE Workflow & Control

Data Quality Monitoring

SAPHCM

AD

Corp HR

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 RegionNew Hire & Separation Entries

New Hire Entries Separation EntriesBaseline F15 Q1 F15 Q2 F15 Q3 Baseline F15 Q1 F15 Q2 F15 Q3

AMEA 46.7% 83.3% 73.1% 70.8% 21.0% 47.6% 26.7% 39.4% Entries Processed 276 114 130 113 381 124 105 104 Processed Late 147 19 35 33 301 65 77 63Canada (Non-Plant) 98.2% 100.0% 100.0% 100.0% 79.7% 88.9% 55.6% 84.2% Entries Processed 56 15 21 17 59 27 9 19 Processed Late 1 0 0 0 12 3 4 3Europe & Australasia 74.0% 86.7% 92.8% 71.4% 59.8% 70.1% 56.5% 70.8% Entries Processed 408 286 221 182 358 164 246 113 Processed Late 106 38 16 52 144 49 107 33Greater China 30.4% 43.3% 53.0% 77.5% 30.3% 61.6% 57.6% 86.1% Entries Processed 1148 356 370 315 792 268 314 317 Processed Late 799 202 174 71 552 103 133 44Latin America 75.7% 65.4% 58.2% 65.6% 46.6% 34.0% 46.6% 51.0% Entries Processed 173 104 98 61 234 94 88 98 Processed Late 42 36 41 21 125 62 47 48US Based Business 99.7% 99.6% 99.8% 99.7% 61.9% 81.6% 80.8% 77.3% Entries Processed 1923 532 436 344 2562 819 608 587 Processed Late 6 2 1 1 975 151 117 133

% 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

HCM Data Steward Working Group

Business HR Reps

ENTERPRISE FOCUS

Enterprise Data Leadership Team

HCM Data Trustee Council

GBS HCM Data Team

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.

FI Data Trustee Model

Supply Chain Data Trustee

Model

Sales Data Trustee Model

Execute Strategy, Ensure Quality, Resolve Issues and Overall Coordination

Provide Authority, Goals, Sponsorship & Accountability

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

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

HCM Information Strategy Pillars

POLIC

Y

GOVERNANCE

PROCESS

MONITO

RING

• 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

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

HR Transformation

27

Our HR Transformational Journey

FROM• US-Centric Approach

• Decentralized Headcount Control

• Qualitative Analysis

• US Transactional Service Center

• High-Touch Model

• Conditioned to Wait

• Activity Focused HR

TO• Truly Global Data & Capabilities

• Central Control & Visibility to Spend

• Data-Driven Decision-Making

• Global Delivery Model

• High Touch Where it Matters

• Empowered to Lead

• Impact Obsessed HR

28

Preparing for HCM Transformation

Legend

Governance Framework

Organizational Readiness

Assessment

Technical Inventory

System Selection

System Inventory

Global Resource Plan

Data Migration Strategy

Data Archiving Strategy

Reporting Strategy

Data Integration Strategy

Global Team Formation

Solution ScopingBusiness Process

Design

Legacy System Connectivity

System Profiling

Infrastructure Deployment

Assessment

Future State Architecture

Assess Prepare Execute

Global Design

Data Readiness AssessmentOrganizational 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