cdq best practice award 2017 data management goo… · cdq best practice award 2017 data management...
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CDQ Best Practice Award 2017
Data Management
at Bayer “Marketing
& Sales”
December 2017 / Alexander Watzke, Dana
Liebmann, Markus Brinkmann
Agenda
Introduction Bayer Group & Business
Services
Data Management & Quality
Management @ Marketing & Sales IT
Conclusion
/// Data Management at Bayer “Marketing & Sales” /// December 2017 2
Bayer – Company
Overview
/// Data Management at Bayer “Marketing & Sales” /// December 2017 3
The steadily growing and aging global population has
a need for new and better medicines and for an adequate
supply of safe food. Our innovations offer answers
to these challenges. We invent new molecules which can
positively influence the biochemical processes in living
organisms with the goal of improving the quality of life.
That is what our mission
“Bayer: Science For A Better Life” stands for.
Challenges of our time
Bayer is a Life Science Company
/// Data Management at Bayer “Marketing & Sales” /// December 2017 4 DeepDive
Key Locations / Regions
/// Data Management at Bayer “Marketing & Sales” /// December 2017 5
The Bayer Group is a global enterprise with companies in 91 countries.
North America
Asia / Pacific
Latin America
Europe / Middle East / Africa
/// Data Management at Bayer “Marketing & Sales” /// December 2017 6
** / *** Full year sales and R&D expenses: as of December 31, 2016 (excluding Covestro);
* Employees and Subsidiaries: as of September 30, 2017 (excluding Covestro)
99,845 Employees*
241 Subsidiaries
€34.9 billion** Full year sales
€4.4 billion*** R&D expenses
Bayer Group Structure
/// Data Management at Bayer “Marketing & Sales” /// December 2017 7
Board of Management
Marketing & Sales IT: Data Management Team
Cross-divisional Services
Consumer Health
Pharmaceuticals
Crop Science
Animal Health
Corporate Functions & Business Services
Data Architecture &
Quality Management
/// Data Management at Bayer “Marketing & Sales” /// December 2017 8
The Value we Deliver
/// Data Management at Bayer “Marketing & Sales” /// December 2017 9
Business
IT
Data Management
We substantially have improved the data quality in the
marketing & sales business processes leading to greater
reliability and higher efficiency.
We could significantly reduce implementation efforts
in IT due to more transparency in information
management, mainly targeting for Business
Intelligence.
We have a full canonical model with metadata
and business rules combined resulting in a fully
integrated approach combining data
management and data quality assurance.
Continuous improvement in Data Quality
/// Data Management at Bayer “Marketing & Sales” /// December 2017 10
Business
Rules Engine
Quality
Validation
Execution
Database
Configuration
Data*
Validation Result
Data Quality
Dashboard
Data Quality
Architect Data Steward
Defines & Adjusts
Imp
lem
en
tatio
n
Integration
Business Rules
BI CRM
ODS
Analysis
Key Roles to Enable Data Management
/// Data Management at Bayer “Marketing & Sales” /// December 2017 11
Data Quality Architect Translates business requirements into rule
definitions and sets up technical solutions
for data quality data assessment.
Data Steward Is responsible for data quality in his
organization and provides business
knowledge
Data Practitioner Changes data by order of the
Data Steward
Data Architect Translates new data requirements
into a compatible data design.
Process Expert Designing processes and sub-processes with the overall goal of process harmonization and reuse across various countries.
Global Organization Local Organization
Standard Processes for Data Management
/// Data Management at Bayer “Marketing & Sales” /// December 2017 12
Business
Requirement
Adjust
Data
Run Rule
in Live-System
Reports +
Dashboards
Review
& Refine
Rules
Drivers Initialization Requirements Engineering
Development Operations
Project
Incident
Process
Change
Define
Business Rule
Data
Requirement
Develop and
test new field
Meta Data documentation:
Attribute + Rule
In GREAT
Data Model Change
Process
Develop and test
new Business
Rule
GREAT
Metadata - Canonical Data Model
/// Data Management at Bayer “Marketing & Sales” /// December 2017 13
Business Data
Model Processes Business Rules
Solutions Data
Models
Object: “Event”
“Start Date”
“Start Time”
“End Date”
“End Time”
Process “Event
Management”
Rule “Start and End
Date are valid”
Table: “EventHeader”
STARTDATE
STARTTIME
ENDDATE
ENDTIME
Table: “DimEvent”
STARTDATE
STARTTIME
ENDDATE
ENDTIME
Table: “EM_Event_vod__c”
START_Time_vod_c
END_Time_vod_c
ODS
BI
CRM
Mapping: Business
Data Model -
Process
Mapping: Business Data Model – Business Rule
Mapping: Business Data Model - Solutions
Fully covered the “CDQ House”
/// Data Management at Bayer “Marketing & Sales” /// December 2017 14
Marketing & Sales IT Strategy, Bayer Group Corporate Enterprise Data
Management Approach
Enable Marketing & Sales Processes, Services, and Functions
BRE = Data Quality Assurance via Business Rule Engine & Data Quality
Dashboard
Data Management Roles defined
Data Management Processes & their integration into Business & IT processes
established
Data Management Architecture and (integrated) Applications implemented
GREAT = Metadata Management via Governance Repository
of Enterprise Architecture and daTa
Metadata and Data Quality – Facts & Figures
/// Data Management at Bayer “Marketing & Sales” /// December 2017 15
Statistics for Marketing & Sales (focus area: CRM)
Large-Scale Approach across various Business and IT domains illustrated via „Event“ example
Metadata Management Data Quality Management
29 Technical Solutions
~2.900 Technical Tables
~110.000 Technical fields
120 Active Users
2 Global Programs
35 countries incl. a data
steward and owner /country
90 Data Practitioners
28 Rule Scenarios
333 Business Rules
~100 Mio Rule Executions /day
99,5% mean DQ KPI across countries
65 M&S Business Processes
~290 Governance Objects
~6400 Governance Attributes
Conclusion
/// Data Management at Bayer “Marketing & Sales” /// December 2017 16
CDQ Data Excellence Model
We Cover all areas with our Approach
/// Data Management at Bayer “Marketing & Sales” /// December 2017 17
BUSINESS
VALUE
DATA
MANAGEMENT
CAPABILIT IES
DATA
STRATEGY
PEOPLE, ROLES &
RESPONSIBILIT IES
PROCESSES &
METHODS
DATA
LIFECYCLE
DATA
APPLICATIONS
DATA
ARCHITECTURE
PERFORMANCE
MANAGEMENT
BUSINESS
CAPABILIT IES
DATA
EXCELLENCE
GOALS ENABLERS RESULTS
CDQ Data Excellence Model
Goals
/// Data Management at Bayer “Marketing & Sales” /// December 2017 18
Develop strong sense of Data Ownership: Local Business users take responsibility for Data
Quality of local data records, Process Experts and IT Roles take responsibility for Metadata
documentation
Trust-building with local Business
Consider data quality issues during process design and functionality testing
Large-scale training
Acceptance (and resources to proceed) come from solving concrete data quality issues / pain
points
Align with all necessary Management and IT strategies in your company
Align with Data Management Approaches on Corporate level
Data Management as Key Enabler for IT Solutions and Business transformation for Marketing
& Sales processes, services, and functions
Data management
capabilities
Data strategy
Business
capabilities
CDQ Data Excellence Model
Enablers
/// Data Management at Bayer “Marketing & Sales” /// December 2017 19
KPIs for Metadata quality ensure adherence to the agreed development methodologies and
should be measured as data quality of operational data should be measured
Quality KPIs for operational business data generate transparency of activities in domain of the
global headquarter and raises trust in all data processing solutions
An end-to-end data model change process ensures that all involved parties from IT developer
to business analyst are aware of their tasks regarding data management
Processes for data quality management ensure an improvement of operational business data
Continuous self-assessment and improvement based on user feedback collection to avoid
administration overkill foster user engagement
Very specific role definition according to RACI
Top Management Support and Stakeholder Management is crucial and should be leveraged
to push roles into the organization
People living roles and met obligations are key for working data management
Performance
management
Processes and
methods
People, roles
and
responsibilities
CDQ Data Excellence Model
Enablers
/// Data Management at Bayer “Marketing & Sales” /// December 2017 20
Tool for Metadata Management and Data Quality is not a “stand-alone” machine but
an integrated system landscape fitting into each other.
Obtain current data maturity level with a Data Quality Dashboard in a single click with possibility
to drill down to case level.
Data
applications
Data Model is directly linked to business information requirements and descriptions.
Governance via development process integration helps to keep data model as easy
as possible.
Rules for Data Quality are based on the business model to maintain ability to execute
on different data containers.
Data
architecture
Data Management included already from project start to do the right thing from start.
Metadata also includes maintenance of retention policies.
Data lifecycle
CDQ Data Excellence Model
Results
/// Data Management at Bayer “Marketing & Sales” /// December 2017 21
Metadata KPI: Technical automatization plus active governance (reporting and organizational
measures) now ensure 100% data quality in documentation
Country Data KPI: 99.5% mean adherence to Data Quality Rules
Local Business enabled to shape and maintain their data to fit the Business Process
requirements
Cross-organization usage of data models established
Data excellence
Improved Business efficiency
Esp. in Master Data Management and BI-Reporting – more accurate and up-to date data for
Sales Reps and CRM Back office processes, Management monitoring of Marketing and Sales
activities
Faster and more (cost) efficient error analyses between Business and IT
Better functional design and testing between Business and IT
More (cost) efficient IT development processes and faster projects
Improved standing of Data Management and Quality
Business value
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Thank you!
December 2017 / Alexander Watzke, Dana Liebmann,
Markus Brinkmann