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Antony_Prasanna
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Introduction

Clients across the globe are getting into the Transformation journey started with SAP S/4HANA.

In this blog, we will take one of the use cases to discuss how the master data (MDG)  journey will be the stepping stone for SAP S/4HANA Transformation and the needed steps to achieve it.

This is the 5th blog in this series. Please go through the previous parts in the given below link

https://blogs.sap.com/2023/01/27/sap-mdg-a-stepping-stone-for-sap-s-4hana-journey-part-i/

https://community.sap.com/t5/technology-blogs-by-members/sap-mdg-a-stepping-stone-for-sap-s-4hana-jo...

https://community.sap.com/t5/technology-blogs-by-members/sap-mdg-a-stepping-stone-for-sap-s-4hana-jo...

https://community.sap.com/t5/technology-blogs-by-members/part-4-sap-mdg-a-stepping-stone-for-sap-s-4...

Key Aspects for MDG : Deep Dive

B. MDG Specific

B.3 Workflow

Workflow : Multiple steps of action which can be performed either serially / or in parallel

In the master data terms, it would be an requestor, enricher and approver.

In this section, we will discuss the various needs of operating model & approach for MDG workflow flexibility to fulfill the needs

Operating Models

For master data to be successfully managed, then it needs the specific set of people / process to be operated

There are multiple of models which exists in the business

  • Centralized
  • Decentralized – Multiple functions
  • Hybrid – Functions owns & central team approves

Antony_Prasanna_0-1719784520185.jpeg

The challenge is that in a business there could be multiple segments, markets for which we can’t apply one operating model across globally which might impose some operational challenges

There needs a flexibility to operate multiple models depending upon the segments and markets

Requirements for operating model flexibility

As we focus on the governance, we will consider the centralized & hybrid operating model for requirements

For requirements collection, discussion with business to understand their current business operating models, pain points and areas of improvements

Understand the corporate vision, transformational goals while defining the requirements for the future

As customer master data have been taken as example for this discussion

There would be atleast 4 dimensions by which requirements can be defined

  1. Segments: In business, there could be multiple sub areas of business which have been needed to support the main business. Or it could be formed due to the acquisition and mergers
  2. Markets : Countries in which the business are operating.
  3. Functions : These are the business functions which are responsible for master data
  4. Account Group : SAP Account groups for master data

Depending upon the size of the markets, the functions might be operated by a single or multiple teams

Within the segments, markets & by account group the requirements differ. There could be account group: Intercompany where it needs a centralized model whereas others doesn’t need to.

Workflow Requirements :

Antony_Prasanna_1-1719784654537.png

MDG workflow Framework

For solution approach discussion, we will be considering the data collation, maintenance, approval process to be done in MDG system

As SAP MDG being the global MDM system, its needs to be flexible enough to accommodate multiple requirements

In MDG perspective, there would be 3 sets of personas

Antony_Prasanna_2-1719784703517.png

Control Table

In the control table build on MDG, a sample requirements have been build.

An quick overview of the the table

  • CR Type – Business process such as Create, Change, Block, Mark for delete etc.
  • Account Group – Defined account groups
  • Org Level Company code - the segment and market are considered as the company code. Enterprise Structure is the key thing to be understood it well to see if this suits. There are cases, only company code might not be enough. It might need to add Sales Org as well.
  • Business Functions – Requestor – Requestor is the first & mandatory step of the workflow. It would be created as roles access and given to the functions who needs to perform. In this example, Commercial
  • Business Functions – Enricher – The specific business functions who provides inputs for specific data sets is given. Depending upon the requirements, there can be made relevant as given below
  • Business Functions – Approver – While the business functions enters the data, does a approver within their functions needed ? If yes, local functions approver comes in to picture
  • Central MDM Approver – Final and mandatory step where it acts a global team which checks and approves all the processes

Antony_Prasanna_3-1719784773567.png

SAP MDG offers various workflow solution through which we can manage the requirements. For this requirements, the dynamic agent selection concept will be taken up. A control table to be build up to have the combination set it up which will be read by the dynamic agent determination Badi for workflow operations

In the table, each column acts as a step in the workflow. If a value exists ( Role), the MDG sends the workflow to the given users. If there is no value, then the step is skipped.

Using this approach, a generic workflow framework is set it up which can able to cater to various scenarios with lots of combinations

If there is new requirement later : where a local approver is needed, it would be a role value add in the control table without any developments

For simplicity , only create scenario is shown. Similar entries needs to be build for each business process. Importantly, the steps can be different for each scenarios.

Key Things

  • With MDG acts a central system for data collection, enrichment and approval, it opens the opportunities of retiring other specific systems / process which is used for similar purpose
  • IT landscape simplicity and process streamline
  • If a upstream system needs to trigger master data workflow ( Ex. CRM for customer master) its very well possible and workflow will support for that as well

In the next blog, I will cover other topics in detail.

About the Author,

Antony Prasanna has been working in SAP master data space since 2006. Have experience working across multiple large transformation programs on SAP S/4HANA including SAP MDM, MDG and Data Migration tools.

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