Without a doubt, modern supply chain management is marked by volatility, revealing a disconnect between enterprise software and executive needs for agility. It is a fact, that our systems can excel at driving operational efficiency and being a system of record. However, our enterprise systems often struggle to keep pace with the rapid changes and disruptions that characterize today’s business landscape. The result is we have a wealth of data, but a scarcity of timely insights and actionable recommendations that are needed for an agile supply chain.

In this article, I’ll first look at the tension we have within our supply chains between being both lean and agile. Moreover, I’ll identify how our enterprise systems are failing to meet the agility needs of supply chain decision-makers. Specifically, I’ll provide a candid assessment of six categories of business software that are falling short. Lastly, I’ll make the case for a new generation of high-speed, adaptable decision systems that can work directly with executives to drive better outcomes.

1. The Lean Vs Agile Supply Chain Showdown.

One of the major reasons supply chains are focusing more on agility nowadays is because of recent worldwide disruptions. Without a doubt, the pendulum has swung from lean management methodologies to a more resilient and agile approach. So, let’s look at what an agile supply chain is and why it has increased in importance over Lean methodologies over the last couple of years.

a. Agile Supply Chain Definition.

First, let’s start with the definition of an agile supply chain:

“Supply chain agility is a supply chain organization’s ability to respond efficiently and avoid making knee-jerk reactions to fluctuations in consumer demand as well as the effects of market vulnerabilities such as geopolitical crises, shortages of labor or raw materials, and acts of nature. An agile supply chain can more easily accommodate, for example, sudden demand spikes and major changes in raw material availability.”

Oracle

b. Lean Supply Chains Are Impacted More Severely by Disruptions.

In the not so recent past, companies did not focus on agile supply chains. Indeed before COVID-19, supply chains chased the lean dream: minimal inventory, just-in-time delivery, and razor-thin margins. Then reality hit. Empty shelves, chip shortages, and medical supply gaps exposed how fragile these systems really were. Companies learned the hard way that efficiency without flexibility is a liability. 

c. The Refocus on Resilient, Agile Supply Chains.

Now, businesses are rebuilding with resiliency in mind, designing agile supply chains that can bend without breaking. Moreover, this transition to date has been primarily focused on how managers make decisions, not on fundamentally changing business software such as enterprise systems. For more discussion about this change from lean methodologies to an agile, resilient approach, see my article, Supply Chain Resilience: It’s Important and You Need to Know Why.

Supply Chain Resilience: It’s Important and You Need to Know Why

2. What Enterprise Software Is and What it Is Not.

Next, let’s talk about enterprise software. In this digital era, all businesses have and use enterprise software to run their business. For instance, most supply chains use a WMS or a TMS to name a few. At its best, enterprise software is a system of record for businesses. It excels at tracking what happened, storing master data, and maintaining operational consistency. So, let’s look in more detail on what enterprise software is and what it is not.

a. Enterprise Software Definition.

 For a frame of reference, below is a definition of an enterprise software application.

“… are large-scale software solutions designed to streamline and automate various processes of an organization’s operations. These solutions are intended to increase productivity, efficiency and collaboration across departments.”

IBM

b. A Short History of Enterprise Software.

Looking back, enterprise software started simple: record transactions, track shipments, manage orders. This is how it was in the 1970s. By the 1990s, vendors began adding fancy dashboards and reports. Now, enterprise software vendors continue to add features, going way beyond their core capability as a system of record. For instance, vendors continue to add more features such as AI, advanced analytics, decision tools – you name it. In many cases, this has resulted in “features bloat“, far from its core mission of transaction processing.

c. The Limits of Enterprise Software: Great for Transactional Processing, Poor for Analytics and Decision Support.

However, can a single system really handle both day-to-day transactional processing (e.g. a system of record) and complex analytics? The answer is no. It’s like asking a sumo wrestler to win a marathon. Indeed, when an monolithic software tries to do everything, it usually ends up doing nothing particularly well. For a more detail discussion on what an enterprise system is and is not, see Joannes Vermorel’s article, The three classes of enterprise software. Also, see Geoffrey Moore’s article, Digital Systems Maturity Model on the different purposes and maturity of business systems.

3. Enterprise Software Reality Check: 6 System Types Failing to Deliver Agility for Today’s Executives.

Enterprise software applications are too rigid and segmented to support today’s agile business needs. In particular, CEOs, COOs, and CFOs require a cross-functional view of their businesses and supply chains. However, most supply chain applications are digital silos, providing limited insight. As a result, this leads to isolated decisions with unintended consequences. So, let’s examine why these systems fall short in supporting agile supply chains.

a. Execution Systems: Not Designed for Cross-functional, Executive Decision-Making.

First, these types of enterprise systems possess rich transactional data, but are in functional silos. Software vendors did not design these systems for executive, cross-functional decision-making. For instance, Transportation Management Systems (TMS) track shipments but can’t predict disruptions. Then there are Warehouse Management Systems (WMS) that optimize space but can’t dynamically adjust to sudden demand shifts. At the same time, select data from these systems are needed for strategic analysis, decision-making and to avoid unintended consequences.

b. Visibility and Tracking Solutions: Identifies Problems, Not Solutions.

Examples of these types of visibility systems include cloud-based “Control Towers” and shipment visibility systems to name a few. Here, this type of software may meet select visibility needs, but they are missing information such as demand and financial data. Also, another feature of these systems is that they usually require many data interfaces to systems with external supply chain partner organizations about logistics events over large geographic areas. At best, these visibility systems can identify problems but often do not have the capability to offer solutions, nor viable options for supply chain decision-makers. 

c. Planning and Modeling Software: Lacks Agility and Does Not Work Directly with Decision-Makers.

Software vendors design these systems for planners to leverage “Big Data” sets. They are not designed for agile decision-making; they are designed for planners. These types of systems include ERP, Inventory Management, S&OP, Digital Twin, Forecasting, and some AI-powered systems. For examples of shortcomings, ERPs focus on transactions, not insights. Moreover, planning systems are in the hands of planners, catering to plotting “what if” scenarios and recurring reports. Indeed, generally these systems are not designed to provide information on-demand according to executives’ decision-making cycles and timings.

d. Analytics and Knowledge Tools: Short on Practical Utility for Agile Decision-Making.

Supply Chain Analytics Types and The Way They Work To Better Empower Decision-Making

Modern analytics software solutions promise deep business insights, but their practical impact often falls short of expectations. Indeed, organizations invest heavily in business intelligence platforms, machine learning algorithms, and artificial intelligence systems, only to find that these tools generate more reports than results. As a result, the fundamental challenge isn’t their analytical capability – it’s their inability to translate complex data into clear, actionable recommendations when business leaders need it most. Without a doubt, this gap between analytical power and practical utility remains a persistent challenge in these types of software. For more on this topic, see my article, Supply Chain Analytics Types and The Way They Work To Better Empower Decision-Making.

e. Backend and Customer Support Business Systems: Isolated Data Silos, Not Designed for Agile Supply Chains.

Here, we can characterize these types of software as having valuable data, but it is isolated within its own individual functional silo. Specifically, these systems have functions such as procurement, payment, accounting, customer relationship, and customer support. At times, the data in these systems are needed by executive management teams. Again, the problem is that these types of software are systems of records not designed to support agile decision-making.

f. Business Automation – BPA, RPA, Personal Assistants, Autonomous AI: Designed More for Automation Support, Not Decision Support.

Lastly, software vendors design these types of automation solutions to automate business processes and execute tasks, not to support executive decision-making. Specifically, these solutions can include Business Process Automation (BPA), Robotic Process Automation (RPA), Personal Assistants, and emerging autonomous AI applications. For a more detailed look at business automation, see my article, Business Automation AI Remake: First Just Tech To Empower Processes And Now Operates Autonomously.

Business Automation AI Remake: First Just Tech To Empower Processes And Now Operates Autonomously

4. The Agile Supply Chain Software Gap: High-Speed, Adaptable Decision Support for Executives.

So, today’s executives continue to drown in supply chain data but are starved for real insights. This is especially true for top executives, such as CEOs, COOs, and CFOs. Without a doubt, current enterprise systems excel at recording what happened, but struggle to answer the questions that matter most: What’s about to go wrong? What should we do about it? Indeed, without tools built to directly support rapid decision-making, leaders fall back on “gut” instinct or try to use transactional enterprise software, not designed for agility. Neither approach works in today’s fast-moving, technology-advanced business environment.

To find out more about what is needed in an Agile Decision Platform for executives, see my article,  An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes.

An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes

Lastly, if you are in the supply chain industry and have a need to supercharge your decision-making cycles, please contact me to discuss next steps. I’m Randy McClure, and I’ve spent many years solving data analytics and decision support 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 launching new analytics-based strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. To reach me, click here to access my contact form or you can find me on LinkedIn.

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