Product and Supply Chain Master Data is the most important master data for most companies as it is central to many mission-critical business processes in sales, commerce, design, manufacturing, logistics, customer service and maintenance. Creation of Product and Supply Chain Master Data is an extremely cross-functional exercise that spans many functions within the organization and often the supply chain. What starts off as a vision and a sketch on a napkin turns into a finished product with the help of Master Data. Like the Cybertruck below.
This post is to compare and assess the Business-centric approach (ZFlow for example) for Product and Supply Chain Master Data to those of ERP-centric Master Data solutions (SAP MDG for example) and Data-centric Master Data solutions (such as TIBCO, Informatica, IBM..).
First thing that comes to our mind is that Business-centric master data management solutions are designed to serve needs of New Product Introduction/Component Engineering, Supply Chain Development, E-commerce, Sales Operations and related business processes. In Business-centric MDM, Master Data Management is usually an extension of product development and supply chain oriented business processes that originate in or involve business stakeholders from different functional areas.
ERP-centric (SAP MDG) and Data-centric master data management solutions (Informatica, TIBCO, IBM, etc..) tend to view master data from the prism of the needs of ERP systems and IT stakeholders that tend to support master data for Extract/Transform/Load (ETL) and Reporting processes.
Summary Assessment of Product and Supply Chain Master Data Management Approaches
The summary below (with some of the most famous GIFs of the Internet) is based on our own internal assessment (but based on actual industry experience) of different approaches for Product and Supply Chain Master Data Management. We will leave the interpretation to your imagination.
| Business-centric MDM | ERP-centric MDM | Data-centric MDM |
|---|---|---|
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A more detailed assessment (more stars the better) is given below. While it may look self-serving it is also based on reasonable analysis of each assessment facet.
| Assessment Facet | Business-centric MDM (ZFlow) | ERP-centric MDM (SAP MDG, Oracle..) | Data-centric MDM (Informatica, TIBCO, IBM..) |
|---|---|---|---|
| Types of Master Data | ***** | *** | ** |
| Master Data Workflows | ****** | ** | ** |
| Cost (TCO) | ****** | *** | ** |
| Democratizing Product and Supply Chain Master Data | ******* | *** | ** |
| Supply Chain Integration | ***** | ** | |
| Time-to-value | ***** | ** | ** |
| Integration | ***** | **** | ** |
| Data Quality | ***** | *** | **** |
| Continuous Improvement | ***** | ** | *** |
| Extensibility | ***** | ** | ***** |
Assessment Facets
Types of Product and Supply Chain Master Data
Many Data-centric MDM solutions tend to have a limited view of master data and often restrict the domains to Customer, Supplier, and if they are any good, Product. In contrast, ZFlow due to its foundation in New Product and Supply Chain Development deals with all kinds of product and supply chain master data, including Part/Material, SKUs, E-commerce listings, Bills of Material, Routings, Factory and Production Planning information, Suppliers, Customers, Costing, Pricing, and may other types of related master data.
| ZFlow | SAP MDG | Other MDM (FOr exampe Informatica, TIBCO..) |
|---|---|---|
| Material/Part Bill of Material (with Reference Designators) Alternate/Substitute Parts Critical Characteristics Routing Approved Supplier Approved Supplier Part Approved Manufacturer Approved Manufacturer Part Purchase Info Record Pricing Condition Supplier Customer SKU Variations Amazon Listing Google Merchant Center Listing Shopify Listing E-commerce Branding Content Process Plan Equipment | Material Customer Supplier Financial Master Data Asset Management Master Data | Generic Objects Customer Supplier Product |
Product and Supply Chain Master Data Workflows
Product and Supply Chain Master data workflows tend to be some of the most cross-functional in an organization. For example, creation or extension of a part/material to a plant can require input, analysis and review/approvals from purchasing, production planning, design, logistics and finance teams. Similarly supplier and customer master data workflows can require input, checks and reviews from Purchasing, Supply Chain, Sales, Finance and other teams. Workflow management (design and execution) is one area where ZFlow stands head and shoulders above ERP-centric and Data-centric Master Data solutions. ZFlow is very likely the best workflow management solution for cross-functional product and supply chain processes.
| ZFlow | SAP MDG | Other MDM |
|---|---|---|
| New Part Request New Part Release Create New Material Extend Material Create Materials Create Bill of Material Change Bill of Material Create/Change Routing Approved Vendor Part(s) Approved Manufacturer Part(s) Create/Change Purchase Info Record Engineering Change Implementation Pricing Master Pricing Change New Supplier Request New Supplier Onboarding New Customer Onboarding Install Equipment Decommission Equipment | Create/Change Material Create/Change Vendor Create/Change Customer Create/Change Financial Master Data Objects Create/Change Asset Master Data Objects | Generic workflows for New Master Data Objects |
Cost (TCO)
Unless money is free and you can get it in unlimited supply, ZFlow is usually a better bet to keep Total Cost of Operation low (often 1/10th) for Product and Supply Chain Master Data Management.
The reason why ZFlow tends to be 10X better is ZFlow is truly an All-in-One Solution that is more or less like a Swiss Army Knife. Many of the components (integration framework, integration adapters, domain object models, data quality rules, workflows, workflow engine) needed for a complete Master Data Management solution are all integrated in ZFlow. ERP-centric and Data-centric solutions require you to purchase separate components in many cases. In addition, ZFlow runs on open-source and cost-effective cloud computing services (Tomcat, MySQL, AWS RDS, Azure MySQL) and does not require purchase of additional infrastructure components (Java Application Servers, Databases, etc.).
Implementation cost is another area where ZFlow has significant advantage. The time and effort it takes to design and deploy Master Data workflows with ZFlow is often a fraction of what it takes using ERP-centric and Data-centric Master Data solutions.
Democratizing Product and Supply Chain Master Data (User Engagement)
We strongly believe that everyone in the organization and in many cases in the Supply Chain can benefit from easy access to Product and Supply Chain Master Data. With this perspective ZFlow makes it easy for everyone (often thousands of people) in the organization and the supply chain to access master data and participate in master data workflows. Key feature that supports this model is the fact that ZFlow cost is instance based and not tied to number of people that use ZFlow.
ERP-centric MDM solutions mainly assume that only ERP experts and master data analysts should deal with master data. And Data-centric MDM solutions are barely accessible to people outside of the MDM team. Both camps make it cost-prohibitive to allow many people access Master Data and participate in Master Data workflows due to expensive user-based licensing.
Supply Chain Integration
Supply Chain participants (your suppliers and customers) are key stakeholders in many master data workflows. ZFlow has in-built model and support for suppliers and customers to access and participate in master data workflows. For all practical purposes ERP-centric and Data-centric MDM solutions have no real and easy way to accommodate suppliers and customers to participate in Master Data workflows.
Time to value
Master Data Management programs are notorious for taking a long time and behind schedule. The main reasons include the need to design many domain objects, design and set up of integration as a separate project using an integration framework, and often the tedious work of designing, testing and deploying master data workflows. Due to the fundamental design constraints of ERP-centric and data-centric Master Data solutions, design and deployment of Master Data objects and related workflows tend to be driven by technology with little in the way involvement from business stakeholders. This is usually a recipe for underwhelming results and disappointment.
ZFlow is more of less ready to go for Master Data processes on Day 1. In some cases, many of the out-of-the-box master data domains (Product, Part, Supplier, Customer) and workflows can be used right away without much modification. Since ZFlow includes a sophisticated integration framework that can be used as part of the Master Data workflows, integration related program risks and delays can be more or less eliminated.
Integration
No application is an island in the modern enterprise and supply chain. Master Data Management solutions are especially dependent on integration to serve the needs of business stakeholders as well as various master data workflows. Most ERP-centric MDM and Data-centric MDM solutions rely on another integration framework (SAP Process Orchestrator (SAP PO) in the case of SAP MDG for example) for interoperability with other applications and SaaS solutions. This invariably increases the Total Cost as well as implementation timelines.
ZFlow is unique in this respect and provides out-of-the-box integration to various systems (SAP, Salesforce..) at the level of APIs and their connectivity to various master data objects and workflows. This is one of the reasons why ZFlow is often ready to go on day 1 and TCO is often 1/10th of ERP-centric and Data-centric Master Data Management solutions.
Data Quality
Poor quality afflicts product and supply chain master data and consequences of poor quality master data are uniformly bad, including lost sales, poor retail compliance, poor quality, poor supplier performance, reputational damage, and adverse safety incidents, among the many.
Ask any quality leader from the manufacturing and continuous improvement fields and they will tell you that the best way to achieve high quality is by eliminating root causes of mistake. And the best place to do that for master data management is to mistake-proof (Poka-Yoke) master data creation processes. ZFlow provides sophisticated quality checks, rule-driven defaults and data validations as part of the master data workflow execution to eliminate errors at the source.
While it is always a good idea to catch errors at the source, there are instances where existing master data needs to be evaluated for quality and completeness. ZFlow supports easy definition of quality and completeness rules and application of the rules against existing master data for any problems. These can include checks for potential duplicates using sophisticated search patterns.
Continuous Improvement
The only constant in life is change, said Heraclitus. ERP-centric and Data-centric MDM struggle to support change and the opportunity for continuous improvement. Because of the number of moving parts involved, ERP-centric and Data-centric Master Data solutions make it hard, if not impossible, to support continuous improvement in master data domain models, workflows and integration scenarios.
ZFlow on the other hand is expressly designed to support continuous improvement/change at every level, including master data object models, workflows and integration scenarios. Changes to existing master data domain models, workflows and integration maps can be made in a matter of minutes, tested and rolled into production in reliable and robust manner without impacting existing master data scenarios.
Extensibility
Even though ZFlow comes with a rich set of master data objects, workflows and out-of-the-box integration there is always a need to support something out of the ordinary. ZFlow provides a number of agile capabilities, including on-the-fly master data object design, do-it-yourself workflow design and extensible integration architecture that can be used to easily design and implement bi-directional integration using many techniques. The best part is that most of these capabilities are accessible to business analysts via the embedded and comprehensive no-code framework. If, however, you do have the itch ZFlow allows use of Javascript and Java to extend ZFlow to perform magic.