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Master Data and Nomenclature, Why Bother?

By
Wayne Thomas

Nomenclature, master data, material descriptions, call it what you will, typically provides insight related to the core business of the enterprise. When used as a foundation for providing key metrics, it can inform decision-making and result in actions and interventions to improve or control operations and outcomes. In today’s interconnected, integrated, interfaced, and multi-platformed world, it has never been more crucial to ensure that data is accurate.

After all, you and your company are no longer the sole consumers and users of the data you create. As data streams seamlessly through a company’s SAP system and into the customer and/or vendors’ platforms and advances into multi-party, virtual supply chains, the stakes are high. Get it right and your master data becomes an asset that can be leveraged for value. Get it wrong and it can disrupt and waste time and money and cause service delays and interruption.In the worst case, it might cause both vendors and customers to abandon the relationship.

Understand the Four Layers of Master Data

There are four layers of master data and each has its own place and function in the integrated Supply Chain. Let’s take a look at how each is distinctive.

      1.     Enterprise Identifier Level of Data
A unique level of data resides at the enterprise level, providing a common view of the world where duplication is avoided. For example, think of a Material Master that highlights a common material that is bought or sold across the platform of trade.

      2.     Territory or Fiscal Level of Data
This level of data is implicated when certain characteristics determine a specific set of circumstances that lead to either a fiscal or territorial consequence. Think of a juristic entity such as a customer or vendor in a certain country. Or consider a tariff determination for trade and taxation or an application to a chart of accounts for reporting. In scenarios like these, duplication is most undesirable and inaccuracy of determination can be costly.

      3.     Operationally Strategic Data
Data elements that reflect an organization’s operating model –such as settlement terms, service levels, available to promise, replenishment strategies, make strategies, and so forth – fall into this data level.

      4.     Operationally Tactical Data     
Those elements that optimize the execution in the supply chain are referred to as operationally tactical data. They reflect the business rules applied and the daily executable behavior desired; examples are lot sizing, maximum and minimum order quantities, INCO terms, etc.

Master Data Governance – the strategies and processes to address and approach these levels of data – is only mentioned here as a context that informs and reinforces why nomenclature is so important to help keep data relevant, pristine, and fit for use. Nomenclature, when used in conjunction with a solid and well-conceivedMaster Data Governance capability, is one of the tools in our supply arsenal to help avoid proliferation and duplication and mitigate business risk. It can either help or hinder.

Data Use and Application: Is It Technology Controllable?

An important consideration in determining nomenclature use and application is whether master data is technology controllable. In a business-to-business relationship, particularly if supported by EDI, data can be technology controllable with clear standards of compliance and the deployment of minimum standards..

Conversely, in a business-to-consumer environment, the application of technologies to control standards adherence and compliance can be much more difficult to achieve, particularly where end-of-point user self-service interfaces are deployed. The compliance challenge can be complicated by data privacy concerns. As individuals become increasingly sensitized to identity theft, they become increasingly reluctant to use unique identifier characteristics like social security numbers, national identity cards, passport details, and so forth. Two kinds of data figure into this discussion.

      Buy-Side and Sell-Side Party Data

This is the data that identifies and distinguishes one party from another, either on the sell-side (customer) or buy-side (vendor) of the enterprise.

Very often, these are discrete juristic entities – also known as non-human legal entities – that are part of a greater whole. Consider an industrial group or conglomerate of companies who, because of their combined buying from or selling to the enterprise may dictate a differentiated relationship. Some of these linkages may not be obvious since they operate or are structured on an undisclosed principal basis. Recognizing these linkages based on how data is accumulated and maintained could be a strategic advantage and also help mitigate the risk of overexposure or high dependency on a common entity.

     Buy-Side and Sell-Side Product Data

More often than not, an enterprise is likely to approach this dataset with polar opposite business out comes in mind:

  • Buy-side data is as transparent and undifferentiated as possible to enable vendors to compete for the purchasing dollar.
  • Sell-side data is as unique and differentiated as is possible to entice a customer to buy only that vendor’s product.

However, a third force is often at play: the proliferation,  i.e., piling up discrete stock-keeping units that are essentially duplicates of already existing materials. This may spark two very detrimental outcomes.

  1. Surplus and redundant materials are stockpiled in inventory because there is simply no way of knowing that they are indeed the same material. Because they have been so distinctly described, it may create a non-competitive situation during the process of sorting materials.In this scenario, the vendors are unaware of or cannot determine what material is being sought. This phenomenon is prevalent in maintenance/MRO environments, where engineers go about specifying components to protect a specific brand or to make sure no one else can consume “their” components.
  2. Customers are being let down on their ability to obtain products they need and want but aren’t being offered. The reason: the material description does not effortlessly enable the customer service agent to find or the customer to select the material they seek in the catalog.

An effective way to help manage and avoid both these scenarios might be the application of a noun, modifier scheme as display in the graphic below. SAP has a very powerful classification capability to support the maintenance of attributes, which can be used for all master data elements (material, customer, vendor etc).

Multi-Use Support of Data Combined with an Industry and Enterprise Wide Vocabulary Are Two Keys Forward

It is imperative to keep in mind that the primary function of nomenclature is to ensure that a spoken or written expression leaves no space for ambiguity.

As partners through the virtual supply chain become more and more connected with increased use of third-party specialist applications, data seldom resides in only one system. Increasingly, synchronicity becomes important to ensure that a set of data is understood and consistently maintained through multiple platforms. This is especially relevant where data is instantaneously transferred across and through platforms using the master data as the unique identifier.

In summary, there are a few main reasons to consider when opting to select and use a nomenclature standard:

  1. Organize and classify to make it easier to understand characteristics
  2. Avoid confusion, particularly when colloquial and synonyms are broadly used
  3. Engender standards and universal acceptance
  4. Support attributes and characteristics that are meaningfully applied
  5. Achieve a better understanding of purpose and differentiators in application

What Are the Main Advantages of Master Data & Nomenclature?

Get the governance and nomenclature right and there are certainly business and strategy benefits that are gained in the market.

Cost Competitiveness 
A nomenclature standard that describes a product being sourced in a structured and open format enables an enterprise to “open source” the goods and services sought in a competitive market.

The benefit is an understanding that the procured goods and services are indeed comparable and substitutable for each other. When that occurs, the procurer is able to consider differentiators that can add or augment the supply; for example, service levels, supply continuity, and collaboration.

Worthy of mentions are aspects that most supply chain professionals will be called on to monitor, report on, and seek improvements in.

  • Contract compliance and spend visibility and the ability to provide meaningful data granularity to support sourcing, compliance, and cost control actions.
  • Inventory reduction by minimizing redundancy of duplication.
  • Improved seek-and-find time that ease human struggle in identifying and retrieving components fit for use in both the planning of and executing maintenance activities.
  • Robust web-enabled catalog technologies deployment to support operations and make sure consumers aren’t direct-buying materials that are either available on-site in the storeroom or off-contract.

Efficacy
When there is trust, reliability, and predictability in the supply chain with assurances that communication is clear, concise, and understood, true integration using EDI and inter-connectivity strategies is the result. An enterprise can then start delivering real value while reducing the need for touch-and-hold points in the daily execution of transactions. This is a particularly compelling proposition in high-volume, low-value transaction environments.

Capabilities, Agility, and Responsiveness
With increased understanding and transparency comes reliability and predictability. Response times improve, with both preventive and corrective actions simultaneously executed to keep material, service, and data flows purring along like clockwork. As a result, a true exception management capability can be ensured.

Let’s face it: business remains highly competitive and volatile across all markets. And never more so than now with the additional complexity and pressure in the supply chain caused by pandemics, geopolitical factors, and even wars.

This, coupled with patterns of convergence across geographies, on-shoring, and off-shoring, all mean that a robust, well-designed, and thought-through standard of communication is essential. Both internally and externally, these standards must be in place to ensure smooth flow and understanding.  

Achieving this goal depends on the time, resource, and effort we make in setting master data strategies. These efforts must be supported with robust nomenclature an enterprise, a connected supply chain, and industry glossaries to help bring transparency and consistency. Doing so will increase the trust and confidence in the supply chain to deliver what enterprises are continually seeking: reliability and predictability.

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