Success Impaired - Part 4: Accurate Modeling is Top Priority

While different stakeholders will have a multitude of factors to consider when assessing detailed scheduling or S&OP/IBP solutions and other supply chain modules, the ability of these two layers to accurately model and optimize the operation is, by far, the most critical. This is because: (a) it is currently the most challenging component for technology vendors to master, (b) there are far too many opportunities to err in buying an ill-fitting solution, and (c) for manufacturers, the value of every other supply chain planning function flows from the outputs created by this model. Furthermore, with Industry 4.0 adoption, this model will likely extend beyond driving supply chain plans and schedules and begin to directly drive the IIoT components of other production and supply chain modules.

Conversely, if this functionality is ill-suited or ill-adapted to a given production environment, not only will users experience hard limitations or insidiously sub-optimal results in modeling and planning, but these limitations and sub-optimal outputs will ultimately ripple outward to other supply chain functions and modules resulting in an extensive but invisible limitation on the operational and financial benefits up and down the supply chain. The core of production scenario modeling, planning, and optimization rests on the ability of these two layers to accurately model the environment. These results and their impacts then flow outward from there to affect every other supply chain module. This is illustrated in Diagram 4.1.

Diagram 4.1 – Hierarchy of Supply Chain Management Technology Modules & Components

When considering the modeling function of the detailed scheduling and S&OP/IBP layers versus other supply chain modules, the other modules are technically easier for vendors to master—or at the very least, more common for them to master. Likewise, if a vendor is well suited to accurately model a given production environment, that vendor will usually have other modules (e.g. demand planning, logistics, warehousing, etc.) that are, at the very least, suitable without as many negative impacts as if you were to let one of the other modules drive the vendor selection and then use an ill-fitting scheduling and S&OP/IBP layer by that same vendor. Additionally, in the worst-case and highly unlikely scenario that a vendor with a well-suited detailed scheduling or S&OP/IBP layer has other supply chain modules that are absolutely unsatisfactory, it is possible and much less risky to choose a separate vendor for those other modules. This worst-case scenario is unlikely because, as discussed in Principle 2, the higher level of software design and forethought that is required to enable a vendor’s solution to support more technically complex modeling environments, is usually applied to other supply chain modules offered by the same vendor. It’s rare, though not impossible, to find a vendor with highly advanced detailed scheduling and S&OP/IBP modeling capability while offering only rudimentary capability for any other supply chain module.

While modeling capability should be the primary factor, it doesn’t mean that other capabilities and modules are unimportant. Many of them are also very important but just not as important as modeling. To illustrate priorities, Diagram 4.2 shows common supply chain modules and capabilities rated in rough priority order.

Diagram 4.2 – Priority of Influence on Detailed Scheduling/S&OP/IBP Vendor Selection

In this diagram, the modules and capabilities were plotted with “Difficulty For Vendors To Master” on the X axis, and “Importance To The Operation” is on the Y axis. To clarify this Y axis measure, all of these modules and capabilities are important, but this measure was assessed from the standpoint of which would break the operation if it disappeared or didn’t work. Many organizations can function without Inventory Planning modules and Transportation Management Systems (TMS) whereas if the modeling, demand planning, or raw material management modules break or disappeared, it might shut down the entire operation.

After plotting the modules on the two axes, the priorities would extend from the highest in the top-right corner (difficult for vendors to master & high importance to the operation) to the lowest in the bottom-left corner (relatively easy for vendors to master & relatively low importance to the operation).

As pointed out earlier, this platform that starts with accurately modeling the production operation will eventually become a key enabler of Industry 4.0 features and benefits. But what exactly is Industry 4.0? With its namesake based on the concept of a 4th Industrial Revolution, it refers to leveraging modern technology, data, and communication to improve manufacturing and related industrial processes. The reality is it is a concept in motion with definitions that are still evolving. This is largely because the individual components and capabilities that form Industry 4.0 apply to different people, companies, and industries in vastly different ways. Consider its different components in Diagram 4.3.

These components can be grouped into data support and infrastructure (Big Data & Analytics, Cloud Computing), production and product movement (Advanced Robotics & Autonomous Machines, Additive Manufacturing), training and product development (Augmented & Virtual Reality), better insight and planning (Digital Twin, Horizontal & Vertical Systems Integration), and communications between functions and devices (IIoT, IT/OT Convergence).

Diagram 4.3 – Components of Industry 4.0

Among the production and product movement component group, Robotics and Autonomous Machines will make sense in the near-term for some companies and in some instances, but for many others, the large capital investment combined with questionable practicality may delay those benefits for some time. Likewise, Additive Manufacturing may be a practical consideration from some manufacturers, but for many others, it’s not even an option.

The next three component groups (data support and infrastructure, communications between functions and devices, and product development and training) will offer nearer-term benefits for a broader range of companies and some of those benefits can be substantial. But even those potential benefits will ultimately come back to a central question: “What needs to be better communicated and to what end?” For manufacturers, the fundamental answer is “We need to communicate what to produce and when, based on what is in demand and where, and how best to get it there.” Answering this question brings us back to the insight and planning component group where production scheduling and S&OP/IBP processes and systems will carry enormous weight.

What to produce and when. The insight and planning components (i.e. Digital Twin, Horizontal & Vertical Systems Integration) should sound familiar. We’ve covered the concept of a well-fitting detailed scheduling and S&OP/IBP/scenario modeling layer as the beginning of a digital twin that can be matured at the user’s own pace. The recommended end-to-end scope of the model is in sync with the benefits of the Horizontal Systems Integration component. And if the model is well-fitting and holistic enabling scenario modeling, planning, and optimization at the strategic level and scheduling, implementation, and execution at the plant level, then this also addresses a large portion of the Vertical Systems Integration component.

…Based on what is in demand and where. Demand planning and collaboration syncs with and leverages the data support & infrastructure and communication component groups to collect better demand signals and apply predictive forecast data to provide better inputs to the planning process. This is, in fact, the next most important capability, after modeling, when considering supply chain plan creation. Given the modeling focus of this article, the demand planning and predictive forecasting is not discussed extensively, but it remains a key piece of the supply chain planning puzzle and will be featured in later articles.

…And how best to get it there. I’ve discussed production modeling/digital twins, using a holistic scope, and optimization primarily within the context of the four walls of a plant since that’s the core of a manufacturer’s operation and the area that planning & scheduling impacts first. However, that core drives upstream and downstream activity and this is where many of the additional Industry 4.0 components and benefits will come into play. As the forecast is honed and the production plan is optimized, that plan can, in turn, support optimization of raw material, transportation, logistics, and inventory beyond the four walls of the plant as depicted in Diagram 4.4.

Diagram 4.4 – Supply Chain Management Modules and Industry 4.0

So for many manufacturers, after exploring all things Industry 4.0, one of the biggest single benefits and the foundation for many of the other benefits come back to what we’re discussing in this article—selecting a well-fitting technology that can accurately model and optimize an end-to-end production operation and, in turn, the rest of the supply chain. And while Industry 4.0 is a relatively new and still evolving term that encompasses a broad range of technology and automation, the driver of some of the biggest benefits (i.e. end-to-end modeling that enables production plan optimization) is not a new or recent development. This core capability has been available for easily 15 years, but it has often been improperly approached with ill-fitting systems that do not accurately model or optimize the operation and a reduced scope that is often designed to fit within the bounds of the ill-fitting system. There are plenty of additional benefits that Industry 4.0 and digital transformation can offer to manufacturers, but accurately and holistically modeling the production operation will unlock the biggest benefits across all components.

Do you have any thoughts, additional perspectives, or different views? Let me know what you think in the comments.

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> Next Section: Part 5 - Accurate Modeling is Top Priority

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Table of Contents

• Executive Summary

• Introduction

• Part 1: Realistic Scenarios Require Accurate Modeling

• Part 2: The Subtle Blast of a Solver’s Approach

• Part 3: Different Industry Groups Have Distinct Needs

• Part 4: Accurate Modeling is Top Priority

• Part 5: Holistic Production Planning is Essential

• Part 6: Why Ill-Fitting Selections Happen and How to Avoid Them

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