In the industrial environment and across companies in various sectors, the same scenario frequently repeats itself: boards of directors approve million-dollar investments in software or automation with the expectation of increasing productivity, but months later times do not decrease, errors increase, and work teams end up frustrated.
Did the technology fail? The answer is no. Technology only executed the programmed instructions. What failed was the strategy: in the rush to achieve digital transformation, many organizations fall into the trap of accelerating chaos.
The origin of the paradox: Automating chaos
In the discipline of Business Process Management (BPM) and Operational Excellence, there is a golden rule that Senior Management must not lose sight of: advanced technology applied to an inefficient process only produces accelerated inefficiency.
When a company automates a process without having previously audited, simplified, and optimized it, the only thing it achieves is scaling its failures at a faster rate. A poorly conceived workflow on paper is still poorly conceived when executed through software; the only difference is that the failure propagates in milliseconds and at a substantially higher operating cost.
In the following video, Morieux offers six rules for “smart simplicity.” (Rule number one: Understand what your colleagues actually do). Source: TED Intersections.
The root cause of this paradox of “more automation, less productivity” is based on four recurring strategic flaws observed in the operational field:
1. Confusing the tool with the strategy
It is common to observe how organizations initiate automation projects from a wrong approach: implementing software simply because the competition uses it. When technology becomes the end rather than the means, process management is subordinated to the system’s capabilities. Instead of adapting the tool to the company’s optimized workflow, processes are twisted to fit the tech vendor’s logic, destroying valuable control and value-added practices along the way.
2. Digitizing waste
From the perspective of Continuous Improvement and Lean Management, every process contains activities that add value and others that constitute waste (waiting times, unnecessary approval signatures, data duplication, rework). When an “as-is” process is automated without a rigorous value analysis, technology ends up shielding and institutionalizing waste. Waiting times, redundancy, and bureaucracy become automated.
3. The disconnect with Quality Management Systems (QMS) and inspection
One of the most delicate impacts in the engineering and energy industries is the deterioration of quality control when operations are digitally accelerated. If critical control points, deviation alerts, and acceptance criteria are not integrated into the automation architecture from the design phase, technology will produce results faster, but it will also scale the production of non-conformities and defects. Increasing process speed without guaranteeing the quality of the input variable is a direct recipe for operational disaster.
4. The disconnect with operational field reality
When automation tools introduce unnecessary rigidity or complex screens that hinder daily work, operational personnel react in two ways:
- Grudgingly complies with the process, wasting valuable time entering data required solely to fill system metrics.
- Creates “parallel” and invisible systems (secondary spreadsheets, notebook notes) to be able to operate in reality, nullifying the accuracy of the information received by management.
The path back to real productivity: Three management pillars
To prevent technology investment from becoming a burden on productivity, Senior Management and organizational leaders must approach automation under a rigorous framework of process architecture and change management.
For any organization evaluating or reviewing an automation project, it is essential to apply these three management pillars:
Pillar 1: Process maturity audit and cleanup
Before writing a single line of code or signing off on software acquisition, a diagnosis of process health must be performed. Apply the maxim of operational excellence: Eliminate, Simplify, Optimize, and only then, Automate.
- Question every approval signature: Does it contribute to risk control or merely dilute responsibility?
- Question every requested data point: Is it used for decision-making or is it superfluous data?
- If the manual process is slow because criteria are unclear, automation will not clarify them.
Pillar 2: Integration of risk management and quality in digital design
Automation should not be approached as an isolated IT department project, but as an initiative that integrates Processes, Quality, and Operations. Quality and audit teams must actively participate in functional mapping to ensure that containment barriers, checklists, and traceability remain solid. Automation must be an ally of compliance, not a shortcut to bypass control.
Pillar 3: Change management focused on operational empathy
No technology works by decree. Successful adoption requires involving end users from the design phase. Listening to the requirements of the inspector, maintenance operator, or process analyst ensures that automation solves real operational problems rather than just executive directives. Training should not focus on “which buttons to press,” but on how the tool elevates the value of the work performed.
Conclusions
Automation is not a magic wand capable of solving a company’s management deficiencies; it is an enhancer. If an organization’s management model and processes are solid, clear, and value-oriented, technology will extraordinarily multiply its results. But if processes are confusing, bureaucratic, and inefficient, technology will only succeed in executing chaos at a speed never seen before.
The true competitive advantage in today’s industrial sector does not lie in accumulating the largest number of software licenses, but in the discipline of maintaining simple, robust processes aligned with a clear strategy of operational excellence.
Before authorizing the budget for the next major technology implementation, organizations must take a reflective pause and audit their foundations: Are processes ready to be automated, or are they about to digitize their own inefficiencies?
What challenges has your organization faced when automating operational processes? We invite you to leave your comments and debate alongside the Inspenet community.
References
- Brynjolfsson, E., & Hitt, L. M. (2000). Beyond computation: Information technology, organizational transformation and business performance. Journal of Economic Perspectives, 14(4), 23–48. https://doi.org/10.1257/jep.14.4.23
- Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2018). Fundamentals of Business Process Management (2.ª ed.). Springer. https://doi.org/10.1007/978-3-662-56509-4
- Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37(1), 32–64. https://doi.org/10.1518/001872095779049543
- Womack, J. P., & Jones, D. T. (2003). Lean thinking: Banish waste and create wealth in your corporation (2.ª ed.). Free Press.
