Many industrial processes are designed as though work moves through a predictable sequence:
A request is created.
A task is assigned.
The task is executed.
The result is approved.
The process is closed.
This logic is appropriate when operating conditions are stable, the required information is available, and the route to completion is known in advance.
However, a significant proportion of industrial work does not meet those conditions.
A production incident may begin with a minor equipment alarm and develop into a combined maintenance, quality, logistics, and planning problem. A suspected defect may require material containment, genealogy analysis, laboratory confirmation, equipment inspection, and a decision on whether production can continue. A maintenance intervention may need to be reconsidered when a spare part is unavailable, asset redundancy is insufficient, or the production plan eliminates the expected repair window.
These situations are not simply workflows containing a few exceptions.
They are operational cases that evolve as evidence, constraints, and risks become clearer.
The relevant management principle is therefore not to replace workflows with case management. It is to recognise that many industrial situations must be governed as cases, with workflows used to control the predictable activities within them.
The Workflow Represents the Expected Route
Traditional process design focuses primarily on activity sequence. It assumes that, once the correct flow has been defined, people and systems should execute it consistently.
That assumption is useful for repetitive and stable work. It becomes insufficient when applied to operational situations in which the appropriate action depends on changing conditions.
Consider an abnormal vibration detected on a critical asset. The initial response may appear straightforward: inspect the equipment, diagnose the cause, and execute the required maintenance.
In reality, the decision depends on a wider operational context:
- Is the asset currently constraining production?
- Is functional redundancy available?
- How reliable is the vibration signal?
- Has the same symptom occurred previously?
- Are competent technicians and suitable spare parts available?
- Is there a safe intervention window?
- Could continued operation create a safety, environmental, or quality risk?
- What are the consequences of stopping immediately compared with controlled continued operation?
The situation cannot be managed adequately by moving a work order through a predefined series of statuses. The team must interpret evidence, assess operational risk, reconcile competing priorities, and determine the next appropriate action.
The process model describes the expected route. The case represents the complete operational situation.
A Case Is Organised Around an Objective
Case management begins from a different premise.
Instead of asking only, What activity comes next?, it asks:
What operational condition must be achieved, what evidence is currently available, and what action is justified under the present circumstances?
A workflow is organised around a predetermined sequence. A case is organised around an objective.
For example, the objective of a quality case may be to protect the customer, contain affected material, determine the extent of the deviation, and restore confidence in the process.
The activities required to achieve that objective depend on the nature of the defect, the affected products, the process conditions, the available traceability, and the quality of the evidence.
One case may require a process adjustment followed by verification. Another may require production containment, genealogy analysis, supplier involvement, engineering review, deviation approval, and customer communication.
Both may originate from a similar event, but they should not necessarily follow an identical path.
This does not imply abandoning standards. It means applying standards at the correct level.
In case-based work, standards should define:
- mandatory controls;
- governance boundaries;
- decision criteria;
- required evidence;
- authorised roles;
- escalation conditions;
- closure requirements.
They should not attempt to prescribe every possible sequence of action for every possible operational condition.
Industrial Organisations Already Manage Cases
Factories manage case-based work every day, even when they do not use that terminology.
A major breakdown is a case.
A recurring quality deviation is a case.
A supplier shortage threatening the production plan is a case.
A machine-condition alert requiring expert interpretation is a case.
A temporary process deviation requiring approval, monitoring, and closure is a case.
A product-launch issue involving manufacturing, engineering, quality, and logistics is a case.
In each situation, the organisation must coordinate people, evidence, decisions, and actions across several functions. The appropriate path changes as the situation develops.
Nevertheless, this work is often managed through disconnected mechanisms: email, spreadsheets, meeting notes, ERP transactions, MES records, CMMS work orders, quality systems, and personal messaging.
Each platform may contain a valid part of the operational record, but no single mechanism provides an integrated view of:
- the current state of the case;
- the operational objective;
- the assigned accountability;
- the evidence under consideration;
- the decisions already taken;
- the unresolved risks;
- the conditions required for closure.
The consequence is not merely administrative inefficiency. It is decision risk.
People act on partial information. Ownership becomes ambiguous. Escalation depends on personal networks. Temporary measures remain active beyond their intended duration. Administrative transactions are completed even though the underlying operational condition has not been fully resolved.
Exceptions Often Reveal the Real Operating Model
Industrial process models frequently treat exceptions as departures from the “real” process.
In complex operations, however, exceptions often reveal how the organisation actually operates.
The standard production sequence may be simple. The true operating capability of the factory becomes visible when material is late, equipment is unstable, inspection results are inconclusive, or production and maintenance priorities conflict.
These situations expose the organisational mechanisms that conventional process maps often conceal:
- who has authority to make operational trade-offs;
- which evidence is considered credible;
- how risk is evaluated and accepted;
- where information becomes fragmented;
- which standards are weakened under pressure;
- who remains accountable when several functions are involved.
Treating such situations as isolated abnormalities prevents systematic learning.
A mature BPM approach should not focus exclusively on optimising the standard route. It should also define how the organisation detects, coordinates, governs, resolves, and learns from operational cases.
The objective is not to eliminate all variation. It is to distinguish between:
- uncontrolled deviation;
- justified operational adaptation;
- avoidable rework;
- necessary investigative activity;
- temporary risk control;
- permanent corrective action.
Case Management Is Structured Flexibility
Adaptive work is sometimes interpreted as a reduction in process discipline. Leaders may assume that allowing different paths will lead to inconsistent execution or excessive individual discretion.
Properly designed case management should produce the opposite result.
It creates structured flexibility: the response may adapt to the situation, but accountability, evidence, authority, and risk remain controlled.
A well-governed industrial case should make the following elements explicit.
The objective
What operational condition must be restored, protected, or achieved?
The accountable owner
Who is responsible for progressing the complete case, rather than merely completing one functional task?
The evidence
Which measurements, observations, documents, alarms, inspection results, historical records, and system transactions support the assessment?
Decision rights
Who is authorised to stop production, release material, defer maintenance, approve a deviation, modify the production plan, or accept residual operational risk?
Permitted actions
Which actions are mandatory, recommended, restricted, or prohibited under defined conditions?
Escalation logic
When must the case be referred to a different level of technical expertise, management authority, or risk ownership?
Closure criteria
What evidence must demonstrate that containment is effective, the operational condition has been restored, residual risk is acceptable, and follow-up actions are assigned?
This governance model is considerably more disciplined than allowing the real process to remain distributed across inboxes, informal discussions, personal spreadsheets, and individual memory.
Systems Should Support the Case, Not Divide It
Industrial information systems are usually organised by function.
ERP systems manage orders, materials, inventory, procurement, and financial transactions. MES or MOM platforms manage production execution, performance, and traceability. CMMS or EAM systems manage assets, maintenance plans, and work execution. QMS platforms manage quality events, deviations, and corrective actions. Historians and SCADA platforms preserve process and equipment data.
Each system has a legitimate purpose and should remain authoritative within its domain.
The difficulty arises when the operational situation crosses those functional boundaries.
Consider a recurring defect potentially associated with a specific equipment condition. The quality event may be recorded in the QMS. Production conditions may be available in MES. Asset history may reside in the CMMS. Sensor trends may be stored in the historian. Material genealogy may be distributed across MES, ERP, and traceability applications.
The operational team does not need another isolated dashboard. It needs a governed mechanism for assembling the relevant context, coordinating the investigation, assigning decisions, and preserving the evidentiary basis for those decisions.
This is where BPM can provide value beyond process documentation.
BPM can act as a case coordination layer, managing ownership, milestones, decision points, escalation, evidence requirements, and closure. ERP, MES, CMMS, QMS, and historian platforms remain the systems of record and execution. The case-management layer connects their information around a shared operational objective.
The value lies not in creating another repository, but in preventing one operational problem from being fragmented into unrelated functional transactions.
Process Mining Requires Case Context
Process mining can reveal variation, delay, rework, repeated loops, and unexpected activity sequences. This visibility is valuable, but interpretation requires care.
A longer process path may indicate waste. It may also reflect an appropriate response to a high-risk condition.
A repeated loop may indicate poor process design. It may also result from missing information, unreliable master data, inconclusive inspection results, or a mandatory validation step absent from the official model.
The event log shows what occurred and in what sequence. It does not necessarily explain:
- why the path was selected;
- what operational risk was being managed;
- which assumptions informed the decision;
- who authorised the deviation;
- whether the outcome justified the additional activity.
Process variation is observable in the log. Operational justification is not always observable unless the case context has also been captured.
Case management can provide that context by connecting events with objectives, evidence, decisions, authority, and outcomes.
Without it, an organisation may optimise the visible sequence while unintentionally weakening necessary operational judgement or control.
Industrial AI Makes Case Governance More Important
Generative AI and intelligent agents may support industrial cases by summarising incidents, retrieving similar historical situations, detecting missing evidence, proposing diagnostic actions, or coordinating work across systems.
These capabilities may improve the speed and quality of analysis. They do not remove the need for operational governance.
An AI assistant may identify probable causes of equipment failure. Its recommendations must still comply with approved maintenance strategies, asset-criticality rules, operating envelopes, safety requirements, and technical authority.
An AI agent may identify a quality risk and recommend stopping a production line. The organisation must still define who is authorised to evaluate that recommendation, who can order the stop, how the decision is documented, and who accepts the resulting production risk.
An AI system may recommend deferring maintenance based on historical patterns. That recommendation must still be evaluated against failure consequences, redundancy, inspection confidence, statutory requirements, and the current production context.
The more adaptive and autonomous the technology becomes, the more important case discipline becomes.
Industrial AI requires:
- a clearly defined operational objective;
- trusted and sufficiently complete context;
- explicit decision rights;
- controlled access to actions;
- traceable recommendations;
- human accountability;
- monitored outcomes.
Without these controls, the organisation is not creating intelligent operations. It is increasing the speed and scale of recommendations without adequately governing their influence on physical reality.
The Management Question Must Change
When operational leaders evaluate a complex process, they often ask whether employees are following the defined workflow.
That question remains necessary, but it is insufficient.
They should also ask:
- Does the official process reflect how difficult situations are actually resolved?
- Can an accountable owner see the complete state of the operational case?
- Are decisions, assumptions, and evidence traceable?
- Are cross-functional responsibilities clear when conditions change?
- Do systems support coordination, or do they divide one problem into separate transactions?
- Are temporary controls monitored until they are formally removed?
- Does case closure demonstrate operational resolution, or only administrative completion?
- Does the organisation learn from recurring cases, or merely process them repeatedly?
Not every industrial process should be managed as a case. Stable and repetitive work should remain standardised, controlled, and automated wherever appropriate.
The essential management task is to distinguish between predictable execution and context-dependent operational resolution.
Use workflows when the path is known and variation should be minimised.
Use case management when the objective is clear but the appropriate route depends on evidence, risk, judgement, and changing conditions.
Use both when a complex operational case contains repeatable activities that still require standard execution.
Industrial operations do not fail because they lack process diagrams. They fail when the organisation cannot maintain accountability, evidence, and decision discipline once reality moves beyond the expected route.
Operational maturity is therefore not demonstrated only by consistent execution of the standard process. It is also demonstrated by the organisation’s ability to govern justified departures from it.
Questions for reflection
Which operational situations in your organisation are represented as standard workflows but are actually managed as evolving cases?
When production, maintenance, quality, engineering, and logistics must resolve one problem together, who is accountable for the complete case?
Do your systems preserve the rationale and evidence behind operational decisions, or only the transactions that followed them?
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