What’s Master Data Management and Why it’s Essential for Supply Chain?

With the proliferation of devices and channels, effective data management has become inextricably linked to customer experience and business growth. Quality, storage, security, and dissemination of key data assets like product data, asset data, customer data, and location data play a critical role in achieving business goals. Ergo, strategizing data management and aligning it to your business aim is more important than ever before.

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When it comes to common data types that organizations deal with, it’s mostly to do with data sets like reference data, transactional data, hierarchical data, and metadata. However, if we combine all this data that describes objects around which business is conducted, it’s called the ‘master data’. Gartner interprets it as the ‘consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise’.

Master data is the business-critical data about parties, places, and things. In the supply chain management (SCM), parties typically pertain to suppliers, manufacturers, warehouse managers, retailers, distributors, customers, etc.; places are all the locations where assets are stored including warehouses and stores; and things range from products, raw materials, domains, vehicles & vessels, assets, etc.

Master data is used throughout the organization under commonly agreed structures and is managed through enterprise-wide governance. It is not transactional in nature, does not change frequently, and is not specific to any geographic location, supply chain process, unit, or system.

Mastering the Master Data

Understanding the significance of master data solves only half the problem. How do you collate it? How do you classify and manage it? And most importantly, how do you administer its flow throughout your legacy system? That is where Master Data Management (MDM) comes into the picture. MDM is a systematic approach of data handling which has become a competitive advantage for companies that leverage from data-driven insights and analytics.

The significance of master data management (MDM) has amplified for organizations — making them recalibrate their data strategy and goals to future-proof their growth.

• Gartner’s definition: “MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.”
• Forrester’s definition: “MDM solutions provide the capabilities to create the unique and qualified reference of shared enterprise data, such as customer, product, supplier, employee, site, asset, and organizational data.”

MDM is as business-centric as it is IT-centric. It is a technologically driven discipline encompassing tools and processes. MDM maintains authority over master data, by creating a unified repository or a ‘single source of truth’. It aims to attain accuracy, consistency, and completeness of data throughout the enterprise and its ecosystem of business partners.

Data Consolidation + Data Governance + Data Standards + Data Quality = MDM

How MDM helps simplify Supply Chain Management

The sheer range and volume of data involved in SCM are huge. It can originate from online forms, ERPs, CRM, routing data from fleets, employee profiles, vendors, and so on. Adopting an MDM strategy and implementing MDM solutions in the supply chain results in the integration of all this data so that it stays uniform across domains and departments. It removes data silos, collects data records into a master file, maintains its quality and integrity, eliminates redundancies and duplicities, as well as standardizes, preserves and governs data.

For example, inconsistencies in product SKUs, order numbers, or customer data records can cause unthinkable complications that can escalate as the data flows through different departments of the supply chain. MDM helps mitigate such issues.

While the benefits of MDM solutions vary depending on the domain/function in which they are implemented — there is a unique value proposition for every department. The solutions create a data architecture, which is so thoroughly inter-referenced that any stakeholder in any department can utilize it. They can provide insights on customer types and behaviors for sales and marketing decisions as well as provide insights on logistics based on routing data. Here are some of the key benefits associated with MDM:

1. Centralized Data Architecture — everyone can access data from different customers and vendors in multiple locations. This particularly helps in tracking and routing assets from procurement to manufacturing to distributors.
2. Optimization and Efficiency — data consolidation reduces the chances of human error and inaccuracy. With better visibility and optimization of end-to-end data, supply chain operations become more efficient.
3. Customer Engagement — data integrated from CRM and other departments help gauge customer behaviors, as well as internal service capacity across the globe.
4. Cracking the Last Mile — data-driven insights help in realizing customer patterns and thereby cut costs of the traveling salesman.
5. Master Edits — information modified in a master repository gets reflected throughout sub-databases. For example — data modified by the manufacturer on the product ingredient list seamlessly gets renewed for the distributor/retailer.
6. Data Reliability — minimal chances of data mix-up or obsolete inputs in a spreadsheet with a cross-referenced, authentic datastore visible to everybody in the supply chain.
7. Backup — data damage or loss at any stage of the supply chain can easily be recovered with a centralized database or ‘golden record’.

Are You Being a Good Data Steward?

Undefined or loose data governance can allow inaccurate data percolating throughout the supply chain and can severely damage your business and rapport. There can be huge repercussions if such flaws persist for a long time. In such a case, MDM becomes more necessary than beneficial. You can gauge your data management loopholes by looking for-

• Data complications due to duplicate/poor quality/redundant data between different entities in the supply chain
• Botched up shipment/procurement/retail orders due to data inaccuracies
• Delayed product launches
• Customer service flooded with complaints of inconsistent or inaccurate product data

MDM initiatives must quickly be undertaken by individuals responsible for data governance, stewardship, and administration if any of the aforementioned criteria are present in your supply chain management.

Effective MDM drives efficient SCM

Exponential data growth is a fundamental challenge that overwhelms most businesses today. The issue escalates proportionally with the number of entities or nodes in the internal/external business environment. And that is why optimizing supply chain management (SCM), which in itself is a complex network, hugely depends on data management.

One must act quickly to take control of data growth, complexity, and chaos. To seize the full potential of digital, decision-makers of SCM must develop data strategies and incorporate data management discipline. It will also help leverage upcoming supply chain technologies like advanced analytics, automation, machine learning, IoT, and blockchain. SCM managers must act now to focus, simplify, and standardize data through an enterprise master data management (MDM) strategy.

The original copy of my full article can be found here.