1. Sample Assessment & Governance Results
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2. Summary of Findings
Summarisation of Issues identified during Interviews
Duplicated and low-quality Master Data
Lack of data rules implemented and no method of validating the data against those rules
Duplicate records across multiple systems and low-quality master data
Lack of, or unclear Master Data Field ownership and accountability
Need for training, education and role definition
Insufficient Data Quality reporting
Lack of process and role definition and understanding – need to streamline processes
Summary of the Pain Points identified from the Survey
Consistent re-work or manual adjustments SAP
Lack of procedures or inconsistent application thereof
The system is tedious and not very user friendly
Lack of relevant reporting
Lack of education of what SAP is capable of in my Job Role

3. 1. Master Data Management Quick Win
Objectives
Control Point-of-Entry
Apply rules to data field values
Validations and Derivations where possible
Workflow implementation
Business Benefits
Accurate data for better decisions
Reduce overall organisational risk
Digital transformation programs are launched on the back of accurate data
Increased efficiencies
Reduce labour costs
Increase profit
Improve service
Improve customer satisfaction
Pre-requisites / Dependencies
Software licenses for MDG
Minimal time from business experts – rules workshops and UAT
Transports
Recommended SAP Applications
SAP SDM
SAP MDG
Time
Effort

4. 2. Master Data Clean Up Objectives
Put mandatory fields in place to ensure completeness of data
Build de-duplication solutions
Implement a clean-up process with status tracking
Standards to keep data clean
Implement Sprint Solutions with proactive dashboard alerts to manage the cleansing process
Implement Agile Methodology in data cleansing
SAP DS - Integration to third party applications
Business Benefits
Accurate data for better decisions
Reduce overall organisational risk
Digital transformation programs are launched on the back of accurate data
Increased efficiencies
Reduce labour costs
Increase profit
Improve service
Improve customer satisfaction
Pre-requisites / Dependencies
Business input - rules workshops and UAT
Business users clean up of data
Recommended SAP Applications
SAP SDM
SAP IS
SAP DS
SAP MDG*
Time
Effort

5. 3. Formalisation of Data Governance Framework
Objectives
Data organogram - Data Owners with KPI with correct authority
Setup Data Council
RACI (Responsible, Accountable, Consulted, Informed)
Role definitions
Domains are a good starting point - allows ownership & clarity
Business Benefits
Accurate data for better decisions
Reduce overall organisational risk
Digital transformation programs are launched on the back of accurate data
Increased efficiencies
Reduce labour costs
Increase profit
Improve service
Improve customer satisfaction
Pre-requisites / Dependencies
Minimal time from business experts – rules workshops and UAT
Recommended SAP Applications NA
Time
Effort

6. 4. Training & Documentation
Objectives
Document and train roles and responsibilities
Document and train processes and Data org structure
Internal communications between departments to allow better customer service and supplier information
Staff need to know what SAP is capable of
Business Benefits
Accurate data for better decisions
Reduce overall organisational risk
Digital transformation programs are launched on the back of accurate data
Increased efficiencies
Reduce labour costs
Increase profit
Improve service
Improve customer satisfaction
Pre-requisites / Dependencies
Minimal time from business experts – rules workshops and UAT
Recommended SAP Applications NA
Time
Effort

7. 5. Reporting & Enhancements
Objectives
Analysis of reports and ABAP code that related to master data maintenance
Assess what can be done in Dashboards and run project activities to deliver reports
Build custom reports where required
Allow greater detail and analysis of the data
Business Benefits
Accurate data for better decisions
Reduce overall organisational risk
Digital transformation programs are launched on the back of accurate data
Increased efficiencies
Reduce labour costs
Increase profit
Improve service
Improve customer satisfaction
Pre-requisites / Dependencies
Business input
Recommended SAP Applications
SAP ERP
Time
Effort

8. 6. Archiving
Objectives
Prepare for Flag for Deletion of records, post defining what determines an obsolescent record
Activate the Archive Objects and build an Archive project
Archive Data that will not be relevant for SAP environment but will be needed in Data Lacks for analysis and reporting
Business Benefits
Reduce Data costs
Improve processes
Pre-requisites / Dependencies
Business input
Recommended SAP Applications
SAP ERP
Time
Effort

9. GlueData - Solutions Overview
2019/07/17