Industrial operations are frequently represented as workflows: defined sequences of activities, decisions, and handoffs that move from a clear starting point towards a predictable conclusion.
This representation is useful. It helps organisations clarify responsibilities, standardise repeatable work, enforce controls, and automate routine transactions.
It can also create a dangerous illusion.
A workflow assumes that the organisation can anticipate what will happen, which information will be available, which decisions will be required, and which route the process should follow.
Many critical industrial situations do not behave in this way.
A quality deviation detected during production, an unexpected equipment condition, a material shortage, a traceability concern, or a process parameter drifting out of control does not arrive with a complete diagnosis and a predefined route through the organisation.
It arrives as an operational problem under pressure.
The people involved must interpret incomplete evidence, assess risk, coordinate across functions, and decide what to do while safety, quality, production, delivery, reliability, and cost continue to compete for attention.
A workflow can route predefined work. It cannot, by itself, govern operational uncertainty.
The factory rarely follows a clean sequence
Consider a dimensional deviation detected at the end of a production line.
A conventional workflow might appear straightforward:
- Record the nonconformity.
- Stop or contain the affected production.
- Notify Quality.
- Investigate the cause.
- Define corrective action.
- Release the process.
- Close the incident.
The sequence is logical. The operational reality is not linear.
Before meaningful action can be taken, several questions emerge:
- Is the deviation isolated or systemic?
- Which serial numbers, batches, or process windows may be affected?
- Can production continue under controlled containment?
- Is the measurement system itself reliable?
- Did a tool change, material batch, maintenance intervention, or recipe modification occur?
- Does the potential customer risk justify stopping the entire line?
- Is qualified inventory available to protect the next delivery?
- Who has the authority to accept temporary operating conditions?
- What evidence would be sufficient to release the process?
The next action depends on the answers, and those answers may change as new evidence becomes available.
Production may propose continued operation with additional inspection. Quality may require immediate containment. Maintenance may suspect equipment wear but need a planned intervention window. Logistics may warn that stopping the line will compromise a critical delivery. Engineering may require historical process data before determining whether the condition is stable.
The situation is not simply moving through a workflow. It is evolving as an operational case.
Workflow, decision, and case are different forms of control
Workflow thinking is effective when three conditions are broadly present:
- the sequence of activities is known;
- the principal exceptions can be anticipated;
- and the decision rules are sufficiently stable.
Purchase approvals, document reviews, calibration reminders, standard inspections, and many routine maintenance requests can often be managed effectively through workflows.
Other work is primarily decision-intensive. The sequence may be relatively stable, but the outcome depends on explicit rules concerning criticality, risk, tolerances, authority, or compliance.
Industrial incidents are different again. Their progression depends on context, emerging evidence, and interaction between multiple functions.
An equipment alarm may require a reset, inspection, component replacement, temporary operating restriction, engineering assessment, or immediate shutdown. The correct response depends on asset criticality, alarm history, process conditions, safety implications, production demand, spare-part availability, and confidence in the diagnosis.
This suggests a practical distinction:
- Workflow management controls known sequences.
- Decision management structures repeatable choices.
- Case management coordinates evolving situations whose next action cannot be determined fully in advance.
Many industrial processes require all three.
Attempting to represent every possible operational condition as a workflow normally produces one of two outcomes.
The first is an enormous process model containing so many branches that nobody can understand, maintain, or govern it reliably.
The second is a simplified model that appears elegant in a workshop but collapses as soon as the operation encounters a meaningful exception.
In both cases, the organisation may believe that the process is controlled because it has been documented.
It has documented an expected route. That is not the same as establishing the ability to govern situations in which the expected route is no longer sufficient.
More automation can conceal the weakness
Organisations often respond to process variability by adding more workflow logic.
Another approval is introduced. Another mandatory field is configured. Another notification is generated. Another escalation timer is activated.
The system becomes more rigid, but the operation does not necessarily become more disciplined.
Users begin selecting inaccurate reason codes merely to progress the transaction. They create parallel spreadsheets, hold informal coordination calls, and obtain approvals through messaging applications. The official workflow records that activities were completed, while the reasoning that actually determined the outcome remains outside the system.
The application presents an image of compliance. The real process has moved elsewhere.
This is particularly common when ERP, MES, QMS, CMMS, laboratory, and engineering systems each manage one fragment of the same operational situation.
The MES records the downtime and production context. The QMS manages the nonconformity. The CMMS contains the maintenance intervention. The ERP reflects material and delivery consequences. Engineering tools may contain parameter changes or technical analysis. Emails, meetings, and spreadsheets preserve the reasoning that connected them.
Each system may complete its own workflow successfully while the organisation still lacks a shared understanding of the event.
Transaction completion is not operational resolution.
Exceptions reveal the actual operating model
Many organisations treat exceptions as noise surrounding the “real” process.
In practice, exceptions often reveal how the process is genuinely governed.
They expose unclear decision rights, conflicting objectives, incomplete information, weak standards, fragmented accountability, and gaps between functional systems. They show where people must compensate for limitations in the formal process design.
A production deviation that repeatedly requires intervention from the plant manager may not represent an isolated escalation problem. It may indicate that supervisors lack explicit authority to balance production continuity against quality risk.
A maintenance case that remains open while production continues under a temporary repair may reveal that nobody is accountable for converting the temporary condition into a permanent corrective action.
A quality hold that moves repeatedly between departments may show that responsibility has been distributed by activity while accountability for the final outcome remains undefined.
An incident that is administratively closed in several systems but continues to recur may indicate that closure criteria are based on task completion rather than verified restoration of process capability or asset condition.
These are not merely workflow defects.
They are operating-model defects.
BPM creates value when it helps an organisation expose and correct these weaknesses—not when it merely produces a more detailed process diagram.
From predefined routing to managed operational cases
A stronger approach does not abandon workflows. It places them within a broader model capable of governing contextual work.
Routine and predictable activities should remain structured. Inspections, approvals, notifications, evidence collection, and regulatory controls should be standardised wherever this improves consistency and reduces avoidable variation.
The wider operational situation, however, may need to be managed as a case with several defined characteristics.
A clear operational outcome
The objective may be to restore safe production, protect the customer, stabilise an asset, recover process capability, or eliminate a recurring source of loss.
Completing individual tasks is not sufficient. The required final condition must be explicit.
An accountable case owner
Several functions may contribute specialist knowledge and retain authority over their respective domains. Nevertheless, one person must remain accountable for driving the complete situation towards resolution.
The case owner does not replace technical responsibility. The role is to maintain the complete operational picture, coordinate required actions, ensure decisions are made, escalate unresolved conflicts, and prevent the incident from becoming fragmented across departmental queues.
Integrated contextual information
The case should connect the information required to understand the situation, including:
- equipment condition;
- product genealogy;
- process parameters;
- maintenance history;
- quality evidence;
- production priorities;
- temporary controls;
- previous incidents;
- and relevant standards or operating procedures.
Without this context, each function acts from a partial representation of the event.
Explicit decision rights and guardrails
The organisation must define who may stop production, approve containment, accept temporary conditions, release equipment, authorise deviation from a standard, or escalate risk.
Decision rights should be accompanied by boundaries: required evidence, approval levels, maximum duration, review conditions, and criteria for escalation.
Flexible but disciplined coordination
The next action should respond to the evidence available rather than being forced through an artificial sequence.
Flexibility does not mean that anything is permitted. It means that the organisation can select appropriate actions within defined governance boundaries.
Traceable operational reasoning
The record should show not only what was done, but why consequential decisions were made.
A robust decision record may include:
- the evidence available at the time;
- assumptions and unresolved uncertainties;
- alternatives considered;
- risks accepted or rejected;
- temporary operating conditions;
- the responsible authority;
- the duration of any temporary approval;
- and the evidence required for permanent closure.
This is where case management, event-driven architectures, and decision management become relevant to industrial BPM.
They recognise that some work cannot be prescribed fully in advance while still requiring visibility, process discipline, accountability, and control.
MES/MOM can provide execution context—but not accountability
MES/MOM is often the system closest to production execution. It can provide critical context: order status, equipment conditions, process parameters, genealogy, downtime, operator actions, and quality results.
This makes MES/MOM an important component of industrial process management.
It does not, however, resolve a cross-functional operating-model problem by itself.
MES may detect an abnormal condition and initiate containment. The QMS may control the nonconformity. The CMMS may coordinate technical work. ERP may calculate material or delivery consequences. Process mining may later reconstruct the observed sequence of events.
None of these capabilities automatically answers the central management questions:
- Who owns the complete operational outcome?
- Which risk has priority when objectives conflict?
- What evidence is sufficient to support the next decision?
- Who can authorise continued operation under temporary conditions?
- Which criteria determine whether the incident is genuinely resolved?
Technology can connect information, trigger actions, and enforce defined controls. Management must still establish accountability, decision governance, and closure criteria.
Process mining requires operational interpretation
Process mining may reveal dozens of variants around a supposedly standard process.
The tempting response is to classify every deviation from the reference model as noncompliance.
That can be a serious analytical error.
Some variants represent waste, avoidable rework, poor discipline, or failure to follow an appropriate standard. Others are legitimate responses to different operational conditions. Some may expose system limitations or missing decision rules. A few may reveal a more effective operating practice that has never been incorporated into the formal process.
The event log shows what occurred. It does not automatically explain why the variation occurred, whether it was justified, or whether the reference model itself was appropriate.
Operational interpretation is therefore essential.
Before eliminating, redesigning, or automating a process variant, leaders should determine whether it reflects:
- avoidable process instability;
- missing or inadequate standards;
- legitimate contextual adaptation;
- unclear ownership;
- incomplete system integration;
- weak decision rights;
- or a situation that should remain subject to qualified human judgment.
Without this interpretation, process mining can help an organisation optimise conformity to an inadequate model.
Better BPM begins with the nature of the work
The central question should not be:
How do we put this process into a workflow?
It should be:
What form of coordination and control does this work require?
Some activities require strict sequencing. Others require explicit rules and structured decisions. Some must be managed as evolving cases. Many industrial situations combine all three.
A mature process architecture distinguishes between these forms of work rather than forcing them into a single modelling logic.
A maintenance intervention, for example, may include:
- a standard workflow for work-order approval;
- decision rules for safety, criticality, and isolation;
- a flexible diagnostic case;
- structured evidence for return-to-service approval;
- temporary operating conditions with defined expiry criteria;
- and escalation logic when the risk exceeds authorised limits.
This design is more demanding than drawing a linear flow. It is also much closer to the reality of industrial execution.
The objective is governed adaptability
Recognising contextual work does not mean permitting uncontrolled improvisation.
Unrestricted flexibility creates its own risks: inconsistent decisions, undocumented knowledge, poor traceability, variable standards, and excessive dependence on individual experience.
The objective is governed adaptability.
Standards should define boundaries, minimum evidence, responsibilities, decision authority, review requirements, and escalation conditions. Within those boundaries, qualified personnel need sufficient discretion to interpret context and respond to the actual situation.
This distinction becomes increasingly important as industrial organisations introduce AI assistants and operational agents.
AI may summarise an incident, retrieve similar cases, identify relevant documentation, suggest probable causes, or recommend possible next actions. Such capabilities may improve decision preparation.
However, recommendations must remain connected to approved procedures, verified operational data, current equipment and process conditions, explicit decision authority, and human accountability.
Otherwise, the organisation risks moving from rigid workflow automation to uncontrolled algorithmic improvisation.
Neither represents a mature operating model.
Industrial operations require more than straight lines
Workflow thinking is not wrong. It is incomplete.
It remains valuable for stable, repeatable, and predictable work. It becomes insufficient when treated as the dominant model for situations shaped by uncertainty, evolving evidence, competing objectives, and cross-functional responsibility.
Industrial BPM must be capable of coordinating routines and exceptions, systems and people, standards and judgment, structured decisions and contextual adaptation.
That requires moving beyond the assumption that every operational process can be reduced to a predefined sequence.
The real test of process management is not whether the normal path has been documented.
It is whether the organisation can remain disciplined, accountable, and responsive when operational reality no longer follows that path.
Questions worth taking back to the operation
1. Which of our critical operational processes are represented as predictable workflows even though they are actually governed through exceptions, interpretation, and human judgment?
A revealing indicator is the gap between the formal system path and the coordination required to achieve an actual resolution. When calls, spreadsheets, messaging platforms, informal approvals, and undocumented negotiations become essential, the workflow is capturing only part of the process.
The answer may not be to add further branches. The work may require case-management capabilities, structured decisions, or clearer escalation mechanisms.
2. When an industrial incident crosses Production, Quality, Maintenance, and Engineering, who is accountable for the final operational outcome rather than merely responsible for an individual task?
Each function may complete its assigned activities while the underlying situation remains unresolved. Cross-functional incidents require an accountable owner supported by explicit decision rights, escalation criteria, access to relevant information, and authority to coordinate the participating functions.
The objective is not to centralise all technical decisions. It is to ensure that somebody remains accountable for restoring a clearly defined operational condition.
3. Are our digital systems capturing the reasoning behind operational decisions, or merely recording that workflow activities were completed?
Timestamps, status changes, and approvals show that transactions occurred. They do not necessarily explain whether the decisions were technically sound or proportionate to the risk.
An effective operational record should allow a later reviewer to reconstruct the evidence, assumptions, uncertainties, alternatives, temporary conditions, and authority behind a consequential decision.
A process cannot be considered controlled merely because its activities are visible in a system. Control also requires the organisation to understand how exceptions are governed, who owns their resolution, and why critical operational decisions were made.
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