Most companies are trying to automate their supply chains. But what if they’re automating processes that shouldn’t exist in the first place?
Despite the controversy surrounding Elon Musk, his accomplishments in engineering, manufacturing, and technology are difficult to ignore. His success can be attributed to talented teams, relentless determination, and a fundamentally different way of approaching problems.
At the center of this approach is First Principles thinking, a problem-solving philosophy that strips away assumptions, conventions, and established practices to build solutions from the ground up. The objective is to arrive at the simplest, most effective solution rather than continuing to improve upon something that may have been fundamentally flawed from the beginning.
This philosophy is particularly relevant to supply chain management, where the ultimate goal is often the same: faster, cheaper, better.
The Five-Step Algorithm
Musk has described a five-step engineering algorithm that I believe is equally applicable to supply chain optimization:
Question every requirement. Challenge assumptions, specifications, and established practices. Make the requirements less dumb.
Delete unnecessary parts and processes. Eliminate anything that doesn’t need to exist.
Simplify and optimize. Improve only what remains after unnecessary complexity has been removed.
Accelerate. Make the remaining processes faster and more efficient.
Automate. Apply technology to processes that have already been challenged, simplified, and optimized.
What makes this approach particularly powerful isn’t necessarily the individual steps. It’s their sequence.
Musk emphasizes that the order is effectively sacred. You don’t get to skip ahead to optimization or automation simply because those activities are more interesting or technologically impressive.
He has repeatedly warned that one of the most common mistakes smart engineers make is optimizing something that shouldn’t exist in the first place.
Think about that for a moment.
Some of the brightest engineers in the world spend enormous amounts of time making things better, faster, and more efficient, without ever questioning whether those things are necessary.
The same mistake happens every day in supply chain management.
The Hidden Cost of Established Requirements
Working with any company that’s been around longer than five minutes, you’ll find assumptions, decisions, and structures that have accumulated over time, often without ever being challenged.
Supply chains are particularly susceptible to this because they evolve through decisions made by Engineering, Operations, Purchasing, Finance, Sales, and other departments, sometimes over generations of employees.
Each department makes decisions that seem perfectly reasonable at the time.
Engineering adds a specification to address a quality concern. Purchasing negotiates a lower price by accepting a larger minimum order quantity. Operations increases inventory to prevent stockouts. Finance adds another approval process to control spending.
Individually, these decisions may make sense. Collectively, they can create a supply chain burdened with unnecessary cost, complexity, and inefficiency.
This is the difference between optimizing individual functions and optimizing the entire supply chain.
A lower purchase price doesn’t necessarily mean a lower total cost. A more stringent specification doesn’t always produce a better product. And another approval step doesn’t necessarily improve financial control.
The first question shouldn’t be how to make these requirements more efficient. It should be whether they’re necessary at all.
Delete Before You Optimize
Traditional Value Analysis/Value Engineering (VA/VE) is an excellent approach to identifying and removing unnecessary costs. There is almost always some cost built into a product or process that the customer isn’t receiving value from.
Consider a fabricated metal component purchased from a supplier.
The drawing specifies a particular material thickness, a powder-coated finish, individual packaging, and a minimum order quantity established years ago.
The traditional approach might be to negotiate a better price, find a lower-cost supplier, or automate the purchasing process.
But applying Musk’s algorithm produces a different set of questions.
Does the material really need to be that thick? Is the powder-coated finish necessary for the application? Could the supplier ship the components in bulk packaging? Is the MOQ driven by an actual manufacturing constraint or simply an outdated commercial agreement?
Perhaps the material can be standardized with other components, the finish eliminated, and the packaging simplified.
Only after questioning and deleting these requirements should we begin optimizing the remaining processes.
The resulting savings can be far greater than anything achieved through price negotiations or purchasing automation alone, without compromising quality or customer value.
Musk also advocates being aggressive enough with deletion that occasionally something must be added back. His point is that if nothing ever needs to be restored, you probably haven’t challenged the requirements aggressively enough.
Of course, in supply chain management, this must be balanced with quality, safety, regulatory requirements, and supply continuity. The objective isn’t simply to remove cost. It’s to eliminate cost that serves no necessary purpose.
Optimization Must Become Part of the DNA
VA/VE is often treated as a one-time project, with a defined savings target, implementation schedule, and completion date.
But supply chains don’t remain optimized simply because they were optimized once.
Processes naturally become more complex over time. New requirements are introduced, additional approvals are added, supplier capabilities change, and temporary workarounds become permanent procedures.
Without continual effort, complexity gradually returns.
This is why First Principles thinking must become more than a project or an occasional cost-reduction exercise. It has to become part of the organization’s DNA.
Every new requirement should be questioned. Every existing process should remain open to challenge. And every opportunity to remove unnecessary complexity should be considered before investing resources in improvement.
The goal is not just to achieve an initial cost reduction, but to create an organization that continually challenges the status quo.
Automation Comes Last for a Reason
Artificial intelligence, APIs, ERP systems, and other automation technologies offer tremendous opportunities to improve supply chain performance.
But technology cannot determine whether a process should exist simply because it can make that process faster.
Imagine implementing an automated replenishment system for a component with unnecessary specifications, excessive packaging, and an inefficient supplier agreement.
You may reduce the administrative effort required to purchase that component, but you’ve done nothing to eliminate the underlying waste.
You’ve simply automated an inefficient supply chain.
Musk’s sequence requires us to question and delete first, simplify what remains, and then accelerate the process by eliminating delays, unnecessary handoffs, and other inefficiencies.
Only then should we automate.
Following this sequence also creates better opportunities for automation. Simpler, standardized processes are generally easier to automate, less expensive to maintain, and more reliable over time.
The result isn’t just lower administrative cost. It’s an organization where people can spend less time managing transactions and more time developing suppliers, improving products, reducing risk, and creating strategic value.
The Best Optimization May Be Elimination
Supply chain competitiveness requires continual innovation, but innovation doesn’t always mean adding new technology, capabilities, or processes.
Sometimes the greatest innovation comes from eliminating something everyone assumed was necessary.
Musk’s five-step algorithm provides a practical framework for challenging those assumptions and building leaner, faster, more effective supply chains.
And perhaps the most important lesson is the simplest.
The next breakthrough in supply chain performance may not come from artificial intelligence, a new ERP system, or another automation platform.
It may come from asking a much simpler question:
Why are we doing this in the first place?
Before you automate your supply chain, make sure you’ve eliminated everything that shouldn’t be there.
GUEST CONTRIBUTOR | BRIAN SNODGRASS
This article was written by Brian Snodgrass, founder of Nitro Supply Chain Solutions, and is featured on ATLATL Business Solutions as part of our ongoing discussion of manufacturing operations, supply chain performance, and practical process improvement.