In the world of supply chains, clear communication is the linchpin of success. Yet, ambiguous business definitions can turn even the most promising innovations into stumbling blocks. From visibility to data integration, the lack of precise operational definitions leads to confusion, inefficiency, and missed opportunities within digital supply chains. Today, the supply chain industry has a major operational definition problem that is costing us billions of dollars a year. Worse, this untenable situation is also preventing us from realizing the true benefits of advanced data-intensive technologies. Specifically, the types of tech I am talking about includes AI, Internet of Things (IoT), data analytics, Decision Intelligence, data integration tools, digital freight matching to name a few.
In this article, I’ll explain why supply chains need measurable operational definitions. Indeed, we need more than agreed-upon dictionary definitions; we need business definitions that make supply chain data both machine-readable and understandable. To illustrate the problem, I’ll provide five real-world examples on how fuzzy business definitions derail supply chain operations. These examples include cross-border trade glossaries, shipment visibility, intermodal operations, and data integrations. Also, I’ll identify specific data-intensive technologies that stall due to the lack of operational definitions.
What Is an Operational Definition and Its Role in Supply Chain Interoperability?
Today, businesses need a common language to communicate with suppliers, manufacturers, logistics providers, and transportation carriers. For instance, all logistics stakeholders must clearly understand terms like “shipped” and “delivered”. However, our fragmented supply chain industry lacks a standardized business glossary, even for basic definitions. Indeed in this digital age, we must have explicit business definitions. This is the only way that our systems transmitting data to other systems can ensure “what it sent is understood.” Data, especially shared data, needs operational definitions that are measurable by both humans and machines. Below, I’ll describe the difference between operational and dictionary definitions.
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 a dictionary definition.
“a reference book that contains words listed in alphabetical order and that gives information about the words’ meanings, forms, pronunciations, etc.”
Britannica
As you can see there is a big difference between a definition found in a dictionary versus an operational definition. The crucial difference is that an operational definition must be measurable. Indeed, this is what data-intensive technologies such as AI, data analytics, Decision Intelligence, data integration methods, enterprise systems, and Internet of Things (IoT) need. Specifically, information technology needs operational definitions that are measurable so that the data transmitted is understood. Another way to say this is that data needs to be both machine-readable and understandable. For a more detailed discussion on operational definitions, see my article, Poor Operational Definitions Impede Supply Chain Tech Adoption: Now Is the Time For A Big Change.
“What gets measured gets done.”
Tom Peters
Examples of How the Lack of Operational Definitions Are Hobbling Supply Chains Tech Adoption.
Below I will share with you five examples of where we are lacking operational definitions in our supply chains. Further, I’ll show you how this lack of business definitions impedes the adoption of advanced information technologies. These examples of contorted business communications include cross-border trade glossaries, shipment visibility, intermodal operations, and data integrations. Also, I’ll identify specific data-intensive technologies stalled due to our lack of operational definitions.
1. Supply Chain Glossaries for Cross-Border Trade: No Industry Agreement on Business Definitions.
Just recently, the ASTM F49 Committee, an organization that sets standards for digital information in the supply chain, started reviewing common supply chain glossaries associated with digital cross-border trade. This included glossaries such as from the Maritime Transportation Data Initiative (MTDI) Lexicon, UN/CEFACT, WCO, GS1, IMO, IATA, ICC, and others. The goal of this review was to make communication within the supply chain clearer. Not surprisingly, there is a lot of overlap and inconsistency in terms used by these different supply chain glossaries. See ASTM’s news release for more information on this initiative. In summary, until the supply chain industry agrees on a common supply chain glossary, we will continue to miscommunicate, and stymied when adopting new technologies.
“People work in the system. Management creates the system.”
W. Edwards Deming
2. Supply Chain Visibility: A Need for Business Specificity on Type of Visibility Needed.
For decades, businesses have chased after the elusive prize of total supply chain visibility. Indeed, corporations have invested heavily in large data integration initiatives to reach this goal. For instance, supply chains have built “digital twins”, developed real-time visibility capabilities, and created Global Business Intelligence (BI) dashboards. However as a result of ill-defined business requirements, most of these IT visibility projects are expensive, time-consuming, and have little direction. Worse, the business ended up overwhelmed with data and underwhelmed with insights.
Indeed, there are many types of supply chain visibility. For instance, is the IT project supposed to provide transportation visibility (“Where’s My Stuff”) or is the visibility system supposed to identify choke points in the supply chain? Moreover, maybe the business’ real requirement is to measure service performance or they need visibility for future planning. Indeed, if businesses do not provide clear specifications on what type of supply chain visibility they need, they will drown in data. For more details on types of supply chain visibility, see my article, Surprisingly Supply Chain Visibility Has Many Forms: See Which One Is Best To Be Your Business’ First Focus.
“Just because you can measure everything doesn’t mean that you should.”
W. Edwards Deming
3. Intermodal Interoperability: Absence of Business Definitions, Both Physical and Digital Specifications
Intermodal revolutionized the transportation industry over a half century ago with the standardization of shipping containers. This was truly a transformative interoperability achievement. Today, the intermodal industry is challenged to adopt new digital technologies. This is primarily because of the lack of both clear business definitions and cooperation with logistics partners. Indeed, these interoperability challenges are mostly business-related, rather than digital. As a result, the intermodal industry has serious interoperability issues that inhibit both digital technology investments and major improvements in operational efficiencies.
For instance, intermodal is hamstrung by many competing business terminologies between transportation modes, such as discussed in the ASTM lexicon example above. Further, the Intermodal Industry has many operational complexities such as dealing with many regulatory authorities, physical interoperability challenges, financial entities, and its many stakeholders such as Freight Forwarders. As a result of these operational complexities coupled with a lack of a coherent business terminology framework, the intermodal industry remains stagnant. For more details on intermodal interoperability challenges, see my article, Intermodal Transportation Requires A Breakthrough To Overcome Its Interoperability Problems.
“Quality starts in the boardroom.”
W. Edwards Deming
4. Data Integrations: A Lack of Operational Definitions for Digital Interoperability.
A lack of operational definitions significantly challenges supply chains when it comes to data interoperability, especially data integrations. Indeed, most businesses can transfer data using file transfer or an Application Programming Interface (API). However, the real problem is that the receiving system doesn’t understand or act on the data sent. In short, the data often gets “lost in translation.”
As an example of this “translation” issue, a supplier transmits to a buyer that a package with their product order has “shipped”. However, in reality the supplier has only printed the shipping label. Worse, the carrier is not scheduled to pick up the package until next week. In this case, the “shipped” data transmission is not just useless, it creates distrust in the supplier. Indeed, these misunderstandings are quite common. This is because businesses, and particularly the supply chain industry, do not have agreed upon operational definitions that are understandable between logistics partners. Indeed, businesses need to better define and agree on industry terms and definitions that are measurable.
For a more detailed discussion of logistics data interoperability, see my article, Achieving Logistics Interoperability: The Best Way to Breakthrough The Tangle Of Dumb Data Integrations.
“ [Semantic Interoperability is] … ensuring what is sent is what is understood”
EIF
5. Countless Other Supply Chain Examples Where Tech Innovations Are Stalled Due to Murky Operational Definitions
Indeed, clarity in business communications is the key for supply chain success. Moreover, without business clarity, the return on investment (ROI) for new tech innovations is difficult at best. Further, these business communications issues extend far beyond the tech examples I discussed above. For instance, these interoperability issues extend to other data-centric tech innovations such as digital identity, knowledge graphs, digital transformation, data analytics, digital freight bill processing, and Decision Intelligence to name a few.
“One accurate measurement is worth a thousand expert opinions.”
Grace Hopper
Conclusion.
So in this article, I first explained why supply chains need operational definitions that are measurable. Indeed, we need more than dictionary definitions that we agree upon. What we really need are measurable business definitions that make our supply chain data both machine-readable and understandable. Also to better illustrate the problem, I provided you five real-world examples of how fuzzy business definitions derail supply chain operations. These interoperability examples include cross-border trade glossaries, shipment visibility, intermodal operations, data integrations, and specific data-intensive innovations. For more information on supply chain interoperability and collaboration challenges, see my article, Supply Chain Business Communications Need Clarity: This Is What is Hobbling New Tech Innovations.
Need help with an innovative solution to make your supply chain systems work together? I’m Randy McClure, and I’ve spent many years solving data interoperability and visibility problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in proof-of-concept and operational pilot projects for emerging technologies. If you’re ready to modernize your data infrastructure or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.
For more from SC Tech Insights, see the latest articles on Interoperability, Data Analytics, and Supply Chains.
Greetings! As a supply chain tech advisor with 30+ years of hands-on experience, I take great pleasure in providing actionable insights and solutions to logistics leaders. My focus is to drive transformation within the logistics industry by leveraging emerging LogTech, applying data-centric solutions, and increasing interoperability within supply chains. I have a wide range of experience to include successfully leading the development of 100s of innovative software solutions across supply chains and delivering business intelligence (BI) solutions to 1,000s of shippers. Click here for more info.