For many years, supply chain leaders have strived to achieve total visibility within their logistics networks. However, despite technological progress, complete supply chain visibility remains elusive. Why is this the case? In this article, I intend to unravel the complexities behind this persistent issue. Surprisingly, the obstacles stem not only from technical issues but also from entrenched business practices.

Specifically, I’ll look at the key advantages of shipment visibility. Next, I’ll break out the seven types of supply chain visibility. This is key for businesses to know so that they can focus their tech on effective solutions. Further, I’ll identify innovative technologies available and discuss the primary obstacles to achieving full visibility. Lastly, I’ll propose some practical solutions to these common issues.

1. Supply Chain Visibility: The Reasons We Need It.

First, let’s review why supply chain visibility is so critical. Below are the reasons why we need visibility into cargo movement within supply chains:

The Reasons We Need Supply Chain Visibility

• Increases Operational Velocity Through Rapid Decision-Making. This results in swift responses and minimizes delays, resulting in higher customer satisfaction.
• Enables Enhanced Proactive Management. Here, management has a clearer picture of inventory levels, transit status, and potential disruptions. As a result, managers have much more agility to swiftly and proactively respond to issues.
• Superior Planning Capabilities. Indeed with total visibility, businesses have the power to predict more accurately. As a result, they have the information to reduce costs, refine resource allocations, optimize delivery times, eliminate choke points, and improve overall supply chain performance.
• Increases Trust Through Transparency. Lastly, transparency in cargo movement bolsters trust and collaboration between stakeholders. Hence, this fosters stronger business relationships and a resilient supply chain ecosystem.

2. What Type Of Supply Chain Visibility Do You Need?

Achieving total supply chain visibility can be overwhelming due to the vast amount of data and associated costs. Moreover, it’s not a one-size-fits-all solution, as different businesses require different types of visibility. For instance, a company focused on improving on-time delivery might prioritize shipment analytics. Often, however, businesses are not clear on exactly what their requirements are for supply chain visibility. In fact, there are many types of supply chain visibility, seven to be exact, that I list below.

Types of Supply Chain Visibility

Surprisingly Supply Chain Visibility Has Many Forms: See Which One Is Best To Be Your Business’ First Focus

• Transportation Visibility: Find My Stuff.
• Capacity Visibility: Identify Choke Points in the Supply Chain.
• Shipment Data Analytics Visibility: Measure Performance.
• Rates Visibility: Manage Transportation Spend.
• Supply Chain Planning Visibility: Prepare for Future Operations.
• Supply Chain Operational Visibility: Proactively Manage Current Operations.
• Strategic Supply Chain Visibility: Innovate And Optimize Processes.

So for initiating a new visibility project, it is critical for businesses to clearly identify to their IT team the type of supply chain visibility they need. This will increase the chances for a favorable outcome at a reasonable cost. For a detailed explanation of these 7 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.

3. The Necessary Tech, Standards, and Methods to Attain Supply Chain Visibility Are Readily Obtainable.

It’s remarkable how many technology solutions are now available to achieve supply chain visibility. For example, this includes advanced tracking devices, Internet of Things (IoT) sensors, and cloud-based platforms that offer granular data of cargo movements. Further, integration of these technologies, adherence to data transfer standards can create a seamless flow of information. Additionally, coupled with analytical tools and methods that interpret this data, companies can gain a comprehensive view of their supply chain. Thus, this enhances visibility, transparency and facilitates better strategic decisions. To list, below are key technologies, standards, and methodologies that make supply chain visibility obtainable.

Supply Chain Visibility Technologies

Emerging Tech For Supply Chain Visibility: The Best Innovations Available Now To Empower Businesses

• Tracking and IoT Tech to generate visibility data.
• Data Integration to share data between systems.
• Interoperability to transmit meaningful data among logistics partners.
• Data Analytics that yields actionable insights.
• Digital Identity Tech that builds both security and trust in data and between supply chain partners.
• Decision Intelligence Tech that extends supply chain visibility to enhance decision-making and, even, automate decision flows.

For a comprehensive examination of these innovative tools and strategies that are transforming supply chain visibility, see my article, Emerging Tech For Supply Chain Visibility: The Best Innovations Available Now To Empower Businesses.

“Why is visibility so hard? The factors are many: alignment, data latency, supply network latency, semantic reconciliation, and channel translation latency.”

Lora Cecere

4. If The Tech Is Available, Why Do Companies Still Struggle With Supply Chain Visibility?

Surprisingly in this age of AI, most companies struggle with supply chain visibility despite having access to a vast array of advanced technologies. Indeed, it is time for business leadership to face the facts that technology alone will not guarantee the visibility that supply chains need. Below, I’ll share with you the four primary reasons why we struggle leveraging the most advanced technologies to achieve total supply chain visibility.

a. The Barriers to Achieve Data Interoperability.

First, while technology can offer granular insight into supply chain operations, significant barriers hinder its full-fledged adoption. Basically, we have an enormous data interoperability challenge. Specifically, below are the five major data Interoperability obstacles preventing total supply chain visibility.

Five Data Interoperability Constraints Impeding Supply Chain Visibility

The Data Interoperability Challenge: It’s The Need For Tech Standards, Compliance, Security, Massive Resources, And Be Understandable

• Adhering to Tech Standards: The lack of standards frustrates data interoperability.
• Complying with Regulations: Obeying data protection laws and corporate policies.
• Securing Access to Data: The puzzling challenge to verify, authorize, and authenticate.
• Massive Tech Costs: The high costs of IT data interoperability and integration projects.
• Make the Data Sent Understood: The absence of shared knowledge across systems and organizations to correctly interpret data.

For a more detailed examination of these constraints, read my article, The Data Interoperability Challenge: It’s The Need For Tech Standards, Compliance, Security, Massive Resources, And Be Understandable.

“However, the IT issues are more manageable than the organizational barriers. Each function (sales, marketing, manufacturing, planning, logistics, and procurement) has a different data structure embedded in processes to drive functional excellence. The functional definitions of excellence are not aligned, often throwing the supply chain out of balance.”

Lora Cecere

b. Businesses Thinking Isolated within Application-Centric Silos Versus Embracing a Data-Centric Approach.

Without a doubt, many businesses remain mired in traditional operational structures, with departments working in isolation, using disparate systems that are not designed to synergize. Indeed, this functional, siloed approach hampers the flow of information across the organization. Thus, this makes it difficult to achieve a holistic view of the supply chain. So, what is needed is a data-centric perspective that breaks down these barriers and fosters a culture of collaboration and integration. For a more detailed discussion of what a data-centric mindset means, see my article, A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation.

A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation

c. Complicated Shipping Data Structure – No Single ID To Unify Data.

Better Shipping Data Analytics Results: Use Of Load IDs To Achieve The Best Efficiency, Visibility, And Financials

Furthermore, another major problem with shipping data is that it is spread across different systems to include order fulfillment, TMS, carrier tracking, 3rd party systems, and financial systems. So, even if an analyst has access to the data, it is challenging to link shipping data together. Specifically, depending on the data needed, an analyst will need to use various reference numbers such as tracking numbers, invoice number, or purchase order to access the shipping data. Worse, just to piece the data together the analyst will need significant transportation expertise and countless hours to make sense of the fragmented shipping data. Moreover, this data issue is not something that AI can solve alone.

One solution to this complicated shipping data structure is for shippers to start using a shipper reference number or a load ID for each of their shipments. Indeed with the use of a shipper-originated load ID, shippers can unify their shipment data starting with planning through execution to post-diagnostics to gain end-to-end supply chain visibility. For a detailed discussion of this Load ID concept, see my article, Better Shipping Data Analytics Results: Use Of Load IDs To Achieve The Best Efficiency, Visibility, And Financials.

d. Not Leveraging Advanced Data Analytics to Steer Through the Seas of Data and Supply Chain Complexity.

Without a doubt, most supply chains do not fully leverage data analytics to maximize Insights about their operations. For instance, some will have Business Intelligence (BI) dashboards to describe “What Happened” Then totally separate, planners will use predictive analytics to determine what is likely to happen. In most cases, this happens in isolated pockets where data is scattered across the supply chain. For example, data about even one shipment can consist of hundreds of data elements coming from scores of systems across the globe. More, specifically, these disperse systems can include order fulfillment, warehousing, shipping, carriers’ systems, 3rd party logistics (3PL) tracking systems, financial systems, and Internet of Things (IoT) networks to name a few.

So, to leverage supply chain data, decision-makers need the full range of data analytics types as follows.

6 Types of Data Analytics

A Data Analytics Perspective To Better Empower Supply Chain Managers

1. Descriptive Data Analytics: What Happened?

2. Diagnostic Data Analytics: Why Did This Happen?

3. Predictive Data Analytics: What Is Most Likely To Happen?

4. Prescriptive Data Analytics: What Action Should We Take?

5. Real-Time, On-Demand Analytics: What Do I Do Now?

6. AI-Powered Analytics: What Questions Did I Not Know to Ask?

For a more detail discussion on these distinct types of data analytics, see my article, A Data Analytics Perspective To Better Empower Supply Chain Managers.

“What gets measured gets improved.”

Peter Drucker

More References.

For more discussion and references on supply chain visibility, see:

• Anvyl’s article, How to Improve Supply Chain Visibility With Real-Time Data
• Tibco’s article, What Is Supply Chain Visibility
• SC Tech Insights’ article, Poor Shipping Data Analytics – Here Are The 4 Reasons Impeding High Tech Visibility And Optimization
• Lora Cecere’s article, Supply Chain Visibility. If It Seems Simple, Look More Closely
• SC Tech Insights’ article, Reactive Shipment Tracking Vs Proactive Operational Visibility: Here Is How To Best Overcome Supply Chain Exceptions

Reactive Shipment Tracking Vs Proactive Operational Visibility: Here Is How To Best Overcome Supply Chain Exceptions

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.

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