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Poor Operational Definitions Impede Supply Chain Tech Adoption: Now Is the Time For A Big Change

Many companies struggle to fully leverage tech solutions such as AI, digital transformation, and IoT despite the excitement and much investment. The often-overlooked obstacle is a lack of operational clarity among business organizations and their systems. Specifically, clear operational definitions are needed for both business systems and organizations to ensure that what is communicated is understood. Positively, without a shared and precise understanding of key terms and processes, supply chain innovations will continue to falter. This is particularly true of logistics and transportation operations. It’s time for a big change.

In this article, I will explain what operational definitions are and why they are crucial to supply chains, both for achieving operational excellence and for adopting new technologies. Next, I will provide examples of how a lack of operational clarity is hobbling our supply chain industry. The main reason for this is our overlapping and ambiguous business glossaries that are suppose to define our supply chain terms and concepts. Finally, I will suggest five actions that organizations within the supply chain industry can take to enhance operational clarity and collaboration. Indeed, these measures can lead to rapid technology adoption, improved interoperability, and overall supply chain excellence.

1. First, What Is an Operational Definition and Why Aren’t Traditional Definitions Good Enough?

operational definitions and a lack of operational clarity
A Lack of Operational Clarity

Many of us may have heard of an operational definition, but what is it? Moreover, what does it have to do with supply chain operations and tech adoption? Well, I’ll explain. First, below are some descriptions of different types of definitions, namely,  dictionary and operational definitions. Also, I’ll look at how an operational definitions are different. Specifically, they include an additional specification, a measurement or metric, of the term or word being described. So, let’s get started.

“What gets measured gets done.”

Tom Peters

a. Definitions: Operational and Dictionary

First, below is a description of an operational definition.

“a definition that gives communicable meaning to a concept by specifying how the concept is measured and applied within a particular set of circumstances.”

W. Edwards Deming

Next, let’s compare that to the definition of a dictionary,

“a reference book that contains words listed in alphabetical order and that gives information about the words’ meanings, forms, pronunciations, etc.”

Britannica

b. Why Operational Definitions Provide More Clarity?

Now, to get a better idea of why operational definitions are key to providing supply chains and its technologies better focus, let’s compare these two types of definitions, operational versus dictionary. First, they are similar in that they both describe a word or term. However, an operational definition goes much further. Namely, it explicitly states that it “defines a measure”.

Another way to say this is that an operational definition includes a metric, a standard for measuring or evaluating something. To illustrate, see Discover 6 Sigma diagram below that depicts a flow chart with an example. This flow chart shows how an operational definition is used to affirm (decide) that there is a common understanding of such things as a concept, a situation, or a business terminology.

1) Example of Where a Lack of Definition Results in Confusion.

To illustrate how important measurements are when it comes to definitions, let’s look at news reports surrounding the 2017 Hurricane Maria and the number of deaths cited. Surprisingly, various new sources reported “deaths” from this storm ranging from the official death count of 64 to much higher counts up to 4,645. Why the discrepancies? It was because there was a lack of definition of what a “death caused by the storm” is. See Craig Tickel’s article, The Stormy Truth Behind Operational Definitions for more details on Hurricane Maria reporting. Indeed, this is just one example. The same holds true for the supply chain industry where there are countless examples of ambiguity in the definitions of common business terms.

2) More References on Operational Definitions.

For more detailed discussion on what is an operation definition, see CommonCog’s article, What’s an Operational Definition Anyway? and Advantive’s article, Operational definition. Also, see Master of Project Academy’s article,  Why Operational Definition is Important in Six Sigma Measure Phase? on operational definitions from a Six Sigma perspective. Additionally, see SPC Software’s article, Operational Definition of a Consistent Measurement System for detailed examples of operational definitions.

“If you can’t describe what you are doing as a process, you don’t know what you’re doing.”

W. Edwards Deming

2. Examples of How Supply Chain Innovation Is Losing Its Way Due to a Lack of Operational Clarity.

Indeed, the absence of robust operational definitions acts as a roadblock to realizing the full potential of supply chain innovations. Without a shared understanding of key terms and processes, organizations struggle to align their strategies, workflows, and systems properly. This ambiguity leads to miscommunication, errors, inefficiencies, and a lack of standardization.  As a result, this adversely affects both operations and digital technology initiatives. Indeed, ambiguous business terminology is impeding technological innovation within our supply chains. Below are examples where a lack of operational clarity is hobbling technology adoption.

  • Supply Chain Visibility: Too much data with little insights due to lack of business specificity. For instance, is visibility needed to “find stuff”, identify choke points, measure performance, or for future planning?
  • Intermodal Interoperability: Lack of cooperation and specificity hobbles digital tech adoption. Data interoperability challenges are immense between various stakeholders to include rail, trucking, ocean carriers, and 3rd party service providers.
  • Data Interoperability: Data gets “lost in translation” due to lack of business definition. Difficult to adopt data-intensive technologies such as AI and data analytics.
  • Emerging Information Tech: Many supply chain tech projects fail due to operational clarity issues. For instance, this includes tech like digital identity, knowledge graphs, digital transformation, data analytics, digital freight bill processing, and Decision Intelligence to name a few.

For more details on these examples, see my write-up on this, Examples of Tech Innovations Stalled in Supply Chains Due to Operational Clarity Issues.

“One accurate measurement is worth a thousand expert opinions.”

Grace Hopper

3. Current Business Glossaries Do Not Have the Operational Definitions to Enable Cross-Supply Chain Collaboration, Nor Achieve Data Interoperability.

In today’s fast-paced and interconnected world, supply chains span across multiple countries, industries, and digital platforms. As businesses strive to enhance their operational efficiency and agility, the need for seamless data exchange and collaboration has never been more critical. However, current business glossaries fall short in providing the operational definitions necessary to achieve true data interoperability and foster cross-supply chain collaboration. This gap not only hampers effective communication but also leads to data silos, inefficiencies, and missed opportunities for innovation. 

Below, I’ll first describe what business glossaries and data dictionaries are. Then, I’ll provide examples of where existing supply chain business glossaries fall short. Lastly, I’ll highlight current business glossary deficiencies. 

a. Business Glossaries and Data Dictionaries Defined.

Business glossaries and data dictionaries are foundational tools for achieving data interoperability. Let’s first start with some definitions to clearly see what business glossaries and data dictionaries are.

1) Data Dictionary.

According to the DAMA Dictionary of Data Management, a data dictionary is:

“A place where business and/or technical terms and definitions are stored. Typically, data dictionaries are designed to store a limited set of metadata concentrating on the names and definitions relating to the physical data and related objects.“

DAMA

2) Business Glossary.

“a collection of business terms and their definitions. Its main goal is to establish a shared understanding of concepts within an organization, creating a unified language.”

castordoc

So, a business glossary provides a common vocabulary for organizations, ensuring that terms are consistently defined and understood across various departments, partners, and other stakeholders. Meanwhile, a data dictionary acts as a repository that details the structure, relationships, and constraints of the data used within the organization. Additionally, there can be many data dictionaries, one for each data interface or data set.  For more references on data dictionaries and business glossaries, see castrodoc’s article, What is a Data Glossary? and atlan’s article, Data Dictionary: Examples, Templates, Best Practices, and How To Make a Data Dictionary

b,  Why Are Business Glossaries and Data Dictionaries Critical to Achieving Data Interoperability

Without a doubt, both business glossaries and data dictionaries are critical for achieving data interoperability. Specifically,  these tools are the first step in the seamless exchange and use of data across different systems and stakeholders. See below where I detail why both business glossaries and data dictionaries are critical to achieving data interoperability within supply chains.

1) Data Dictionaries Needed for Both Data Integration and Interoperability.

Now, from an IT data integrator perspective, all that is needed to transfer data from one system to another is a good data dictionary as described above. Indeed, a data dictionary is needed for both data integration and data interoperability.

Usually a data dictionary is found within a data provider’s specification documentation such as for an application programming interface (API), proprietary file transfer, or electronic data interchange (EDI) to name a few. Indeed, with a well-specified data interface document, it is fairly easy for supply chain partners to transfer data seamlessly with minimum data errors. As a result, IT has everything they need to provide a seamless data interface between two systems. However, that does not necessarily mean that the data will be actionable or understandable to the receiving system or organization.

2) Business Glossaries Needed for Data Interoperability.

Indeed, the problem with data integration is not our inability to achieve seamless data exchange. The real issue is that the data we exchange is not understandable. Namely, the data needs to be commonly understood by the sender and receiver to achieve true data interoperability. So, this is where a business glossary comes in. Specifically, the purpose of a business glossary is to enable a shared understanding of terminology. If organizations and their systems have a common understanding of business terms, then they can achieve true data interoperability.

For more detail discussion on the data interoperability within supply chains, see my article, Let’s Breakthrough The Data Interoperability Nightmare: It Is The Best Way To Unlock Supply Chain Innovation.

c. Examples of Business Glossaries Lacking Operational Clarity.

Despite their importance, current business glossaries often fail to support the rapid global and digital expansion of supply chains. Indeed, traditional business glossaries do not offer sufficient, measurable definitions for digital supply chains. Further, this clarity issue adversely affects most supply chains more than other industries. This is because cross-functional and cross-border operations in logistics dramatically increase the degree of misunderstandings. See below for examples of supply chain glossaries lacking clarity as well as where these glossaries overlap and conflict with each other.

1) Examples of Supply Chain Business Glossaries That Lack Operational Clarity.

Below are three examples of business glossaries in the supply chain industry that lack the accuracy that operational definitions can provide.

a) GS1 Attribute Business Definitions Standard.

This 2019 GS1 business definitions standard by the Consumer Goods Forum identifies and defines 180 attributes (business terms). In this case, the definition include the following: business name, business definition, examples, and usage statement. Though useful, this particular business glossary does not have an explicit requirement for a measure or metric for each business term. Thus, this business guide is open to misinterpretation from both a business and automation perspective. 

b) Form and Style for ASTM Standards: Part E – Terminology.

Within this 2023 ASTM standards style document, the terminology section describes terminology definitions as follows:  “Write definitions of terms and definitions specific to a standard in the dictionary-definition form. Include term, part of speech, definition, and, when applicable, a delimiting phrase.”  In this case, even though this glossary definition standard includes “a delimiting phase”, it still does not explicitly require a measure or metric. Thus, any business glossary based on this dictionary-type definition standard is open to misinterpretation from both a business and automation perspective. 

c) Maritime Transportation Data Initiative (MTDI) Lexicon.

This 2023 Recommendations on the Maritime Transportation Data System Requirements, Appendix 1.7, provides approximately 200 terms as part of a MTDI Lexicon. Again, this is useful, but it only provides dictionary-type definitions. Thus, this business glossary, even when extensively reviewed and agreed upon, is open to misinterpretation. This is because it lacks a measure or metric in the definition.

To summarize, these glossaries lack operational clarity as they do not require a measure or metric in defining terms and concepts. Moreover, these examples illustrate that most, if not all, supply chain business glossaries lack precise operational definitions. 

2) Overlapping Supply Chain Business Glossaries.

Another challenge with supply chain business glossaries are that there are too many of them. For example, many standard development organizations (SDOs) such as UN/CEFACT, WCO, GS1, IMO, IATA, ICC, and ASTM International offer business glossaries for supply chain organizations. There are also countless proprietary business glossaries developed by businesses, tech vendors, agencies, and associations in the supply chain industry. To illustrate, see DFM Data Corp “Onion” diagram below that depicts all the different organizations directly or indirectly involved with supply chain standards development. Many of these organizations also develop business glossaries.

So, the scope of the work to collaborate and improve the clarity of business glossaries within the supply chain industry is immense. Also, see Michael Dardin’s posting, Enabling Fluid Global Trade by Aligning Terms, Data, and Attributes for more on the challenges with aligning business glossaries within the supply chain.

Credit: DFM Data Corp

d. Business Glossaries Do Not Enable Cross-Supply Chain Collaboration, Nor Data Interoperability

To sum it up, there are basically two major deficiencies with our current supply chain business glossaries. These includes:

Supply Chain Business Glossary Deficiencies
a) Lack of Measurable Business Definitions Impede Understandability.  

The current state of our supply chain business glossaries are subject to misinterpretation, both operationally and for advancing digital innovations. There is a need for operational clarity, namely, operational definitions. 

b) Overlapping Business Glossaries Hobble Collaboration and Interoperability.

In this case, there is no “master” business glossary that applies to all logistics functions or is universally accepted globally. As a result, this also impeded cross-functional and end-to-end data interoperability. Indeed, disparate business glossaries, some proprietary, are a major cause contributing to functional data silos that are hobbling supply chain operations today.

“If you cannot measure it, you cannot improve it.”

Lord Kelvin

4. Leveraging Operational Definitions: Actions We Can Take Now to Both Improve Supply Chain Collaboration and Enable Rapid Tech Adoption.

To address these operational and technical challenges, supply chain leaders must prioritize the development and implementation of robust operational definitions. Indeed, this is what we are missing in our supply chain glossaries – understandable, measurable definitions. To do this involves collaborating with subject matter experts to develop clear, specific, and actionable definitions for key processes, metrics, and data elements. Ideally, these operational definitions should be widely accepted, updated regularly, and available to all stakeholders. By increasing operational clarity, companies can facilitate better collaboration, faster technology adoption, and ultimately, superior supply chain performance. Below are five actions we can take to help move forward with improving operational clarity within supply chains

Solutions to Share a Common Set of Operational Definitions Across Supply Chain Glossaries
  1. Create a Sense of Urgency to Fix Ambiguous Business Glossaries: They Are Hobbling Both Data Quality and Operational Excellence.
  2. Adopt an Operational Definition Format for Business Glossaries.
  3. Leverage Knowledge Graph Technology to Provide Definition and Context to Business Glossaries.
  4. Move Toward a More Encompassing, Shared Business Glossary for Supply Chains.
  5. Foster a More Collaborative and Definitive Process for the Development of Supply Chain Glossaries.

For a more detailed look at these solutions, see my article, A Refocus on Supply Chain Glossaries: The Best Way To Unlock Data Interoperability, Strengthen Collaboration And Leverage Tech

For more from SC Tech Insights, see the latest articles on Interoperability, Data, and Supply Chain.

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