For engineering and manufacturing leaders, the story is becoming uncomfortably familiar.
A compelling demo. A polished ROI model. Confident assurances that a new production planning, process monitoring, or enterprise management platform will “pay for itself” within 12 to 18 months. The business case is approved; contracts are signed—and a few years later, the organization is left with underutilized technology, frustrated plant managers, and the realization that the expected value never materialized.
In many cases, the cost of that mistake quietly exceeds several million dollars.
The problem is not that companies are investing in technology. It is that they are confusing a technology business case with an engineering and manufacturing strategy. The two are not the same.
The Illusion of Vendor-Supplied ROI
Vendor ROI models are designed to sell software, not to assess organisational readiness or strategic fit. They rely on optimistic assumptions: rapid adoption, accurate and standardised data, consistent production processes, and a level of internal alignment that many manufacturing organizations—particularly complex engineering operations—simply do not have at the time of purchase.
These models highlight what the software can deliver under ideal conditions, not what the business can actually execute, sustain, or scale.
That gap between promise and performance is well documented. Recent industry surveys indicate that only about one-third of manufacturers report being satisfied with their current production planning, process monitoring, or enterprise management systems. Nearly two-thirds describe their experience as neutral or dissatisfied, even when a formal ROI analysis justified the investment1.
For executive teams, this creates a dangerous illusion of certainty. The spreadsheet suggests the investment works. The payback period looks reasonable. The perceived risk appears contained.
What is missing is a clear understanding of whether the technology aligns with the plant’s operating model, production maturity, and long-term strategic objectives.
The Pre-Buying Gap
Many technology failures are rooted in decisions made long before the RFP is issued.
This “pre-buying gap” occurs when organizations skip the hard work of defining success beyond cost savings. They move directly from operational pain points—“we need better production visibility” or “we need to automate workflow monitoring”—to selecting vendors, without first answering foundational questions:
- What strategic problem are we solving in our engineering or production processes?
- Which operational decisions should this technology improve—whether in scheduling, material utilisation, or quality assurance?
- What capabilities must exist outside the system for it to deliver value?
- How will this investment change behaviors, workflows, and accountability on the shop floor?
The hesitation many organisations express reflects an implicit recognition of this gap. Many engineering and manufacturing firms, especially those with multi-site operations or highly specialized production lines, delay implementing new technology because leaders increasingly understand the risks of buying solutions before clarifying strategy1.
Without addressing the pre-buying gap, technology becomes an expensive experiment rather than a strategic enabler.
Functional Requirements: The Uncomfortable Truth
Functional requirements are often treated as a box-checking exercise. In reality, they should be a forcing mechanism for strategic clarity.
Too often, requirements are copied from legacy systems or influenced by vendor marketing. The result is bloated feature lists that obscure what truly matters.
Survey data reinforces that technology limitations are rarely the primary constraint. Cost and lack of internal resources are cited far more frequently than missing functionality, while IT constraints and executive alignment also play a significant role1.
In practice, most technology initiatives in engineering and manufacturing do not fail because software cannot deliver—they fail because the organisation is not structured, staffed, or aligned to support the operational change the software demands.
Effective requirements begin with outcomes, not features. They distinguish between what is essential to execute the strategy—whether improving throughput, reducing waste, or ensuring regulatory compliance—and what is merely nice to have.
Benchmarking Provides Context
Objective industry benchmarking is another due diligence step that is often overlooked.
Without understanding how peers with similar production complexity, engineering processes, and supply chain networks perform, it is difficult to set realistic expectations. A 5% improvement in process efficiency may sound impressive until it is clear that the organisation is already performing near industry best practice—or misleading if underlying operational inefficiencies remain unresolved.
Benchmarking helps leadership distinguish what technology can influence versus what requires structural or process changes. It also helps prioritize investments rather than pursuing incremental gains that may have limited operational impact.
Strategy Before Software
Perhaps the most expensive mistake is allowing technology selection to drive strategy instead of validating strategy first.
When vendors are asked to define the future state, organizations risk outsourcing critical thinking. The roadmap becomes shaped by product capabilities rather than the plant’s operational priorities, production targets, and engineering objectives.
Executive alignment and clarity of purpose consistently appear as barriers to successful implementation; an indication that many initiatives proceed before leadership agreement and success metrics are fully defined.
By performing strategy work before issuing an RFP, buyers gain a comprehensive understanding of the true work effort involved. This includes internal resource requirements, organisational changes needed, and a realistic timetable for implementation.
That clarity materially improves cost estimation. Instead of relying on high-level vendor assumptions, organizations can more accurately quantify implementation effort, internal labor, change management, and ongoing operating costs. When paired with a clearer articulation of benefits, this creates a more precise and defensible estimate of ROI and payback period.
More precise costs plus more realistic benefits produce better buyers—buyers with grounded expectations, stronger governance, and a higher probability of realising value post-implementation.
Strategy validation means pressure-testing assumptions before they are embedded in contracts. It asks whether the organisation has executive alignment on trade-offs, the operating model to support new capabilities, and the governance required to measure value over time.
If any of these answers are unclear, the organisation is not at a disadvantage; it is simply not ready to buy.
A Strategy-First Mindset
Technology can be a powerful accelerant, but only when it is anchored to a clear, validated manufacturing and engineering strategy. The most successful organisations invert the traditional buying process. They invest first in understanding themselves before investing in tools.
This approach does not slow decision-making; it improves it. It leads to fewer surprises, stronger vendor partnerships, and measurable value that holds up under scrutiny.
For engineering and manufacturing organizations, the most expensive technology mistake is not buying the wrong system—it is buying a system without a strategy.
About the Author: Brad Forester is the Founder and Managing Partner of JBF Consulting, a leading logistics strategy advisory and technology integration firm. He brings more than 25 years of leadership experience in transportation strategy, logistics technology, and supply chain transformation. For more information, please visit www.jbf-consulting.com.
1: JBF Consulting 2026 Routing & Scheduling Reality Check Survey
