Overview
Change that works on paper must work in practice
Most asset management transformation programmes are technically well-designed. The strategy is sound. The process redesign is logical. The technology is appropriate. And yet the routines people perform on the ground — how work orders are raised, how maintenance histories are written, how condition data is reviewed — do not change. The organisation reverts. The investment is not realised.
This is not a new problem. Research on planned change has consistently shown that the gap between what a model prescribes and what people actually do is not primarily a communication failure or a training failure. It is a deeper phenomenon — the limits of performativity: the conditions under which a planned change model successfully transforms everyday routines, and the conditions under which it does not.
Optimal®'s approach to Change Navigation is grounded in original academic research by Leslie Loziwe Moyo, Director of Optimal®, on the empirical limits to performativity in planned change — identifying the conditions that determine whether a change model transforms the routines it targets, and building a practical framework for navigating those limits in asset management and maintenance transformation programmes. This distinguishes Optimal®'s capability from generic change management consultancy: we understand why change fails at the level of practice, not just at the level of programme design.
Felicity
Conditions that must be present for a change model to successfully transform organisational routines
Infelicity
Conditions that constrain or prevent performativity — where change models encounter their empirical limits
Navigation
The structured response to performativity limits — adapting the approach as conditions change, not persisting with a failing model
The Research Foundation
Why planned change encounters its limits
The concept of performativity — drawn from strategy-as-practice research — argues that models do not merely describe settings but actively transform and shape the reality within them. A maintenance planning process, a work order workflow, a condition monitoring protocol: each is a model that, when successfully adopted, reshapes how people perform their daily routines.
But as research by Optimal®'s Director, Leslie Loziwe Moyo, demonstrates: "not all models successfully transform settings." The thesis — "Exploring limits to performativity: (Re)constituting everyday performances through planned change" — addresses a critical question in strategy-as-practice: to what extent, and under what conditions, can a planned change model be performative during the co-performation of routines and strategy?
The research identifies felicity conditions (the presence of which enables a model to transform routines successfully) and infelicity conditions (the presence of which constrain or prevent transformation). It develops a framework for the empirical limits to performativity — demarcating the space for what the research calls "performativity struggles" — and provides a basis for analysing why specific change models fail in specific operational contexts.
For Optimal®, this is not academic theory. It is the diagnostic framework that informs every change navigation engagement — helping us identify before implementation begins which conditions are present, which are absent, and what must be addressed for the planned change to actually take root in daily operational practice.
Why Change Fails in Asset Management
The specific limits of transformation in asset-intensive organisations
The performativity limits that planned change encounters are particularly acute in asset-intensive industries. Maintenance routines are deeply embedded — often practised the same way for years, reinforced by peer norms, shift culture and the practical demands of operational continuity. A new work order workflow, a different approach to failure code entry, a revised inspection protocol: each requires people to change not just what they do but how they think about their work.
These organisations also exhibit specific structural conditions that constrain change: boundary-spanning professional service routines that cross functional lines; complex technology-mediated workflows where the system and the behaviour must change simultaneously; and a fundamental tension between the operational imperative to keep assets running and the disruption that genuine change inevitably requires.
- Routine embeddedness — maintenance practices performed the same way for years resist replacement even when a better approach is understood
- Boundary-spanning complexity — change that requires coordination across planning, operations, engineering and procurement creates multiple simultaneous performativity limits
- Technology-behaviour coupling — CMMS and EAM adoption requires simultaneous changes to how the system is configured and how people behave
- Operational continuity pressure — the imperative to keep production running creates legitimate resistance to the disruption that change requires
- Leadership sponsorship gaps — research shows effective sponsorship increases change success by up to 85%; absence of it is the single most reliable predictor of failure
- Communication-behaviour disconnect — people understand the rationale for change but continue performing existing routines because understanding is not sufficient for behavioural change
What Optimal® Delivers
Structured outputs at every stage
Change Navigation produces defined, operational deliverables — not a change management report. Every output is designed to be immediately actionable and sustained through ARaaS® governance until adoption is verified.
01
Performativity Assessment Report
Diagnostic assessment of felicity and infelicity conditions specific to the organisation and programme — identifying the performativity limits the change programme will encounter before it begins. Provides the evidence base for all subsequent change navigation design decisions.
02
Stakeholder Engagement Plan
Mapped stakeholder architecture with influence analysis, resistance risk assessment and engagement strategy for each group. Identifies boundary-spanners, critical sponsors and structural resistance points. Sequenced to the programme timeline and the operational calendar.
03
Change Narrative & Communication Programme
The coherent account of why routines are changing, what the new routines achieve and what the transition requires — delivered through channels appropriate to the operational environment. Includes floor-level communication for maintenance teams alongside formal programme communications.
04
Role-Specific Training Curriculum
Training designed around the specific routines being changed for each role — not generic system training. Delivered in a format and at a time appropriate to the operational context. Reinforcement cycles scheduled at 30 and 60 days post go-live to address capability gaps identified through adoption measurement.
05
Resistance Navigation Log & Intervention Register
Real-time tracking of resistance patterns — identifying type, location and intensity. Distinguishing structural resistance (requiring change programme adaptation) from individual resistance (requiring targeted engagement). Escalation pathways for persistent resistance that cannot be resolved at programme level.
06
Adoption Measurement Reports
Behavioural adoption measured at 30, 60, 90 and 180 days against defined operational indicators — evidence that new routines are enacted in daily practice, not evidence that training was attended. Programme does not formally close until adoption is verified at the level of operational routine.
ARaaS® Delivery Model
Change Navigation as a sustained programme
Optimal® delivers Change Navigation as an integral element of the ARaaS® framework — recognising that the routines of daily asset management practice do not change at go-live. They change over months of consistent reinforcement, adaptive navigation and governance.
The ARaaS® model connects change navigation outcomes directly to operational performance — tracking whether the new routines are generating the data quality, process compliance and reliability improvement the transformation was designed to deliver. Change success is not declared when training is complete. It is declared when the operational metrics confirm that new routines are embedded and performing.
1
Diagnose
Performativity assessment — mapping felicity and infelicity conditions. Stakeholder architecture. Historical change analysis. Understanding why previous attempts to change specific routines succeeded or failed in this organisation.
2
Design
Change narrative development. Communication programme. Role-specific training curriculum. Resistance navigation plan. Adoption measurement framework. Engagement approach calibrated to the specific conditions and limits identified in diagnosis.
3
Navigate
Active change navigation through implementation — floor-level engagement, real-time resistance identification and targeted response. Adaptive adjustment of the approach as conditions evolve and new performativity limits emerge. Not programme management — active navigation.
4
Verify
30/60/90/180-day adoption measurement against behavioural indicators. ARaaS® governance integration — change outcomes tracked alongside operational and reliability KPIs. Programme formally closed only when adoption is verified at the operational routine level.
Programme Outcomes
What successful Change Navigation delivers
When Change Navigation is delivered as a structured, research-grounded programme — rather than a communications exercise — the outcomes are measurable in operational practice, not just in programme metrics.
Operational
- New maintenance routines embedded and consistently performed
- CMMS and EAM data quality improvements sustained beyond go-live
- Process compliance maintained without continued external pressure
- Operational teams performing new routines without reference to procedure
- Previous change attempts not repeated — institutional memory of failure addressed
Organisational
- Change capability built internally — teams equipped to navigate future change
- Resistance patterns documented and understood for future programmes
- Leadership sponsorship skills developed through the programme experience
- Super-user network established and active post-programme
- Organisational culture shifted toward evidence-based change practice
Strategic
- Transformation investment realised — return demonstrated in operational metrics
- ISO 55001 people and competence requirements systematically addressed
- Digital adoption sustained — technology investments generating data and insight
- Reliability improvement programme underpinned by stable, changed routines
- Organisation ready for the next transformation cycle without restarting from baseline
Client Case Study
Turning a third failed attempt into an embedded programme
A process industry operator had attempted to implement a structured planning and scheduling process on two previous occasions. Both times the process was adopted at launch, used for approximately three months, and then abandoned as teams reverted to previous routines. The second attempt included a more extensive training programme than the first. The outcome was the same.
Optimal® began with a performativity assessment — identifying the specific infelicity conditions that had caused both previous attempts to encounter their limits. The assessment revealed that the primary performativity limit was not understanding or capability: it was the absence of a planning role that had the authority to hold the scheduling boundary against reactive demand. The routine could not embed because the organisational structure did not support it.
18 months
Sustained adoption — compared to 3-month reversion on each of the two prior attempts
91%
Schedule compliance at 180 days — the routine was performing, not just being complied with
Zero
Additional training investment required — the issue was structural, not capability
"The previous two attempts failed because they treated the problem as a training problem. Optimal® identified it as a structural infelicity condition — the planning role lacked the organisational authority to protect the schedule. Once that was addressed, the routine embedded within weeks. The training had already worked. We just hadn't given it the conditions to perform."
* Outcome figures are indicative. Client details anonymised by mutual agreement. Contact Optimal® for reference engagement details.
Industry Applications
Navigating change across every asset-intensive sector
The performativity limits that planned change encounters are structurally similar across asset-intensive industries — but their specific expression differs by sector, organisation and the nature of the routines being changed. Optimal® brings research-grounded diagnostic capability alongside cross-sector operational experience.
Oil & Gas
Complex boundary-spanning routines — crossing operations, maintenance, inspection, integrity and HSE — create multiple simultaneous performativity limits. Change navigation in this context requires architecture thinking alongside behavioural change expertise, and careful management of the boundary conditions between functional disciplines.
Mining & Heavy Industry
Shift culture, remote operations and high-volume asset environments create specific infelicity conditions that generic change frameworks miss. Change navigation must be grounded in the operational reality of how maintenance teams actually work — not how the process model assumes they work.
Manufacturing, Utilities & Nuclear
Regulated environments where compliance is tracked create a particular risk: the appearance of adoption without the reality. Compliance metrics show people performing the new routine; behavioural measurement reveals they are performing a simulacrum of it while continuing their actual practice. Adoption measurement must go beneath compliance.
Related Services
Connected capabilities
Change Navigation is the human adoption layer that underlies every technical and process change Optimal® delivers. These are the services most frequently delivered alongside a Change Navigation engagement.
Why Optimal®
Research-grounded.
Operationally embedded.
Optimal®'s Change Navigation capability is distinguished by its intellectual foundation. Where most change management advisory draws on practitioner frameworks — Kotter, Prosci ADKAR, McKinsey 7-S — Optimal®'s approach is additionally grounded in original research on the empirical limits to performativity in planned change. This gives us a diagnostic depth that practitioner frameworks alone cannot provide: the ability to identify, before the programme begins, where and why the planned change will encounter its limits — and to design the response accordingly.
This research foundation is complemented by direct operational experience in asset-intensive industries. Our change navigators understand maintenance planning, CMMS adoption, condition monitoring workflows and asset data governance — not as theoretical contexts but as operational realities. We do not apply generic change frameworks to specialist domains. We navigate change from within the domain.
- Original research foundation — Optimal®'s approach grounded in academic study of the limits to performativity in planned change
- Diagnostic-first methodology — conditions assessed before approach is designed, not after the first attempt has failed
- Domain expertise — change navigators who understand asset management operations, not just change management theory
- ARaaS® governance — change outcomes tracked alongside operational KPIs, continuously, not declared at go-live
- Adaptive programme management — approach adjusted as conditions evolve, not persisted when it encounters its empirical limits
