1. How Johnson Controls Mobilized Their Data Governance Program
for Big Data & MDG on HANA Chris Derra Johnson Controls &
David Woods DATUM SESSION CODE: BT581
2. Organizations struggle to balance ERP roll-outs with Data
Governance initiatives, but there is a way to integrate deployment
activities to achieve maximum value by: establishing a vision for
MDG on HANA with proven strategies and tactics for deployment
taking advantage of MDG on HANA to drive value in advance of ERP
deployment Utilizing platform capabilities to accelerate ERP
Implementations LEARNING POINTS
3. About Johnson Controls Today, there are nearly 170,000
employees and many business partners in the Johnson Controls family
delivering products and services wherever our customers live, work
and travel.
4. Our Evolving Strategies Deliberate and explicit choices
Company choices v. business unit-only choices Play to win in the
markets we choose Data-driven v. supported anecdotes What will it
take for us to be who we want to be?
5. Quick Facts about DATUM Booth 379 Fast-Growth Solutions
Company Recognized by Recognized by SmartCEO Magazine as a Future
50 rising star Named Leader in Data Governance 2.0 by Forrester -
February 2015 70% of ASUG Data Governance 2014 SIG Annual Meeting
Success Stories are users of our Solutions DATUM Customers
6. The ERP Program Challenge for Data
GovernanceInformationTrustworthiness Time ERP Data Readiness
Mobilization Point Organization Data Gov. Policy Recognition of
Lost ROI The Scramble How Could That Be? We Own It Lets Start with
Data! Migration Degradation Reliability Team Work RISK REDUCTION
VALUE CREATION Mobilize Earlier! Typical ERP program activities are
inherently designed to focus on the critical data governance
requirements until AFTER Go- Live
7. Prioritizing what we Govern Strategic Insights Information
Data KPIs / Measures The foundation of the governance program is
set based on the ERP program, but will expand based on the data and
information that is most important to the business (processes and
analytics)
8. How weve Organized for Success Enterprise BPOs OTC FTP / PTD
PTP RTR PLM Business Data Architect Customer Data Steward Direct
Material Data Steward Indirect Material Data Steward Vendor Data
Steward Finance Data Steward CROSS PROCESS STREAM INTEGRATION
Secondary Primary MinorMinor
9. Governance Model Evolution Governance Model Standards and
Business Rules drive design and build activities and are
iteratively identified and evaluated as part of Unity Program
Governance Model will be formalized as part of the Unity Program
during DD (e.g. BPDs, Build, Testing, ..) focused on SAP (Unity);
reviewing and approving standards & rules Governance Roster
largely represented by Unity Program Team (business
representatives) Data Standard and Business Rule Ownership
(business ownership) still transitional Targeted external
communication of proposed standards and business rules Project Mode
(Design, Build, Test, Deploy) Standards and Business Rules approved
and managed as part of the deployed system Governance Model
implemented to support deployed sites, pending deployments (and
targeted legacy sites) SAP and non-SAP focus Standards and Business
Rules driving Unity benefits (operations, analytics, compliance, )
Governance Roster represented by key Business Owners taking
ownership of the system(s) Data Standard and Business Rule
Ownership transitioned to end-state Business Owners Broad
communication of approved standards and business rules Steady-State
(Sustain / Optimize) Process People Data Governance Model needs to
be established during the ERP Program
10. BluePrint (Design) Think Governance Data Object List
Customer Master Credit Master Customer Master Info Record Billing
Document DesignActivities Business Data Dictionary (Customer
Example) Customer Name (KNA1-KUNNR) Account Group (KNA1-KTOKD)
Industry Code 1 (KNA1-BRAN1) Ref Acct Group (KNA1-KTOCD) Data
Design Required, Optional, Not Used List of Allowed Value Settings
Security Data Standards Business Usage Business Owner System of
Record Allowed Values Business Rules (DQ) Scenario Specific Rules
(e.g. Acount Group rules for Sold To, Ship To, Payer, and
Hierarchy) Data Conversion Baseline for Wave System Mappings
Conversion Rules Data Construction Rules
11. Process Definitions What about Data ? Does not clearly
define the data process within a business process context Business
stage gates are not clear and/or not defined Documentation is
driven from IT or founded on technical specifications Insufficient
documentation providing required data to support the process (and
impact) Lack of consistent process documentation existed or
adherence in the current state
12. MDG-enabled, Optimized Data Processes Roles/Tasks now
clearly align and roll-up to support business processes Business
process driven stage gates defined and managed via workflow
Optimized process enables a Just In Time (JIT) data collection
process that aligns to enable business processes and support
critical milestones Leveraging our process documentation and
complementary tools provides scalable, standardized, and governed
processes
13. Establishing a Repeatable Data Governance Framework Is
there Compliance, Financial or Operational Impact? Where should we
govern?How should we govern? (Point of Entry, Passively, None?)
Frequency of change? Impact? Risk/Benefits EXAMPLE: We need to add
a commodity code for Lead/Cores supporting compliance and
analytical requirements. Who has decision rights? Governance
decisions for every data element are evaluated and determined
independently, but always follow the same methodology and
approach
14. Importance of a Data Governance Framework
15. Linking the Data Governance Framework Business Data
Glossary (BDG) Business Data Dictionary (BDD) Governance Rules
(Scenario Based) Process Decomposition (L1 L5) Level 1 Process
Level 2 Sub-Process Level 3 Activities Level 4 Process Steps Level
5 Data Elements Data Glossary and Dictionary Link to Governance
Model Governance Rules and Standards on Process Steps and Data
Elements Data Standards Repository Measures & Metrics
Definitions Data Governance Framework
16. Synchronizing Process, Data and Rules Overview of Planning
Item and Finished Good Global Workflows Version 1.1 September 27,
2013 QuEST Activity Brief Approved Marketing Request Planning Item
0 days3 Material Master LDA Create New Planning Item/ ZREP 1 days2
Pricing LDA Populate Planning Price 4 days0 This Database Waiting
for IR Approval 5 days0 Marketing Update New Finished Good Request
0 days2 Sales & IT Services Update Classifications 1.1 days2
Demand Planning Update Classifications 1.2 days2 LDAs Update FG
Setup and MOE & Classifications 2 days2 R&D QA Populate
Shelf Life Data 4.2 days2 R&D SST Populate Dimensions and
Weights 4.1 days0 Workflow Awaiting Packaging Specs to be moved to
Pending 3 days2 LDAs Create PKI and PKI Det Rules and Activate the
FG 5 End of FG Global WF days2 R&D SST Populate Declared Weight
2.2 days2 Demand Planning Populate Classifications 2.3 Workflow
triggers Pricing Workflow to circulate. days2 Material Master LDA
Populate MOEs and Classifications 3 QuEST Investment Reco Approved
Approve Waiting for IR Step Marketing End of Planning WF Planning
Item Workflow Finished Good Global Workflow days2 Sales & IT
Services Populate Classifications 2.4 days2 Ops Planners Assign
Production Plant 2.1 Workflow sends email notification to Sales
Planning, Demand Planners, Ops Planners & Replen (only for
non-seasonal) Workflow sends email notification to Sales Planning,
Demand Planners, Ops Planners & Replen
______________________________________________________________________________________
Business Process Flows Process Overview List Governance Rule
Composer Governance Rule # Field Level Details List Process Stage
Gates Rule Reference # Enabling MetaData Process Flows Standards,
Rules and Metrics Business Process Flows import and remain synced
with the data and business rules required to operationalize and
govern them 1 to many 1 to many many to many
17. Rules before Tools ! Rule Readiness dictates Tool Readiness
how well the organization is positioned to develop governance rules
will dictate solution and initiative success.
18. Rules will support both ERP and MDG Activities Leveraging
Governance Rules Assess Data in order to Validate Governance Rules
Determine if site data is ready for Deployment Define timing &
staffing required for for cleansing & enrichment Cleansing
& Enrichment Goals Only cleanse & enrich data required
required for migration Ensure process is intuitive & driven by
by business (not IT) Cutover Pre-Mock Load Testing against target
target configuration Multiple Mock Loads (SIT, UAT, SIM) Reduce
timing of outage window Example Ingest data - 111k records De- Dupe
1200 records Execute Relevancy Rules 17k records *Narrow down the
data to whats relevant to the business. Auto Cleanse 1300 records
*Address Standardization, etc. Manual Cleansing *Data Construction,
Data Enrichment, Duplicate selection, Data Corrections
19. Operationalizing Business Knowledge for MDG JCI Data
Governance Framework Information Value Management (IVM) SAP MDG SAP
Information Steward Existing docs Business knowledge System Config
Business Metrics Rule Extract (Func. Spec)Load Template1 2 3
20. Step 1: Establish Data Governance Framework Interview Data
Stewards, BPO, IT and SME roles to determine critical governance
and MDG configuration inputs Configure Rule Composer to reflect
JCIs Data Governance Framework Produce standardized templates to
capture existing business rules Rule Load Template Required MDG
Inputs1
21. Step 2: Define Data Stds & Business Rules Existing docs
& processes Tacit knowledge System Config Governance Template
Capture existing rules and transform into JCI Data Governance
Framework Complete Rule Definitions for specific intended
Governance Strategy JCI Data Governance Framework Information Value
Management (IVM) 2
22. Measure Rule Readiness for MDG 105 Rules 75.4% MDG based
governance requires robust rule definitions
23. Targeting Rule Definition Gaps By establishing and
following a structured governance framework, we can easily define
GAPS within each business rule that are required functional inputs
for MDG
24. Ensuring a Complete Functional Design Ready for
Execution
25. Step 3: Functional Extract Ready for Build Functional Spec.
Extract for MDG 3
26. Competing with ERP objectives, timelines and deliverables
can often impede Data Governance objectives Ensuring that Data
Governance is actively part of (not informed by) the ERP program is
critical Establishing and following a structured, repeatable Data
Governance Framework ensures relevancy and success Early
identification, capture and measurement of critical MDG-specific
inputs is the only way to avoid delays and successful deliver KEY
LEARNINGS
27. Questions David Woods Principal Partner DATUM LLC
[email protected] 610.812.5476 Chris Derra Director
Enterprise MDM & BI Governance Johnson Controls - Corporate
[email protected] 414.312.1522
28. STAY INFORMED Follow the ASUGNews team: Tom Wailgum:
@twailgum Chris Kanaracus: @chriskanaracus Craig Powers:
@Powers_ASUG
29. THANK YOU FOR PARTICIPATING Please provide feedback on this
session by completing a short survey via the event mobile
application. SESSION CODE: BT581 For ongoing education on this area
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