Organisations retain extensive records of their performance. They know what results were achieved, where expectations were missed and how performance has changed over time. But what does the organisation remember about the deliberate efforts made to improve those results? The reasoning behind those efforts, and what was learned from them, is far less consistently retained.
“We tried that before. It didn’t work.” The response is familiar. But what was tried? What did those involved expect to happen? What actually happened, and what did they learn? Too often, the answers depend on whether someone who remembers is still around.
A team can deliver an improvement without leaving the organisation better equipped to make the next one. The result may endure while the understanding behind it does not. Improving performance today and building the ability to improve tomorrow are related achievements. They are not the same.
Not all improvement activity serves the same purpose
People refine routines, resolve issues, strengthen relationships and find better ways of working every day. This is part of good management and professional practice. Such activity has value in its own right; it does not need to be captured in an organisational memory simply because something was done differently.
A more specific opportunity arises when someone deliberately intervenes in the system of work to influence a defined performance outcome. The proposed change rests on an expectation about how performance is produced—an expectation that can be explained, challenged and revisited.
Consider a retailer buying a popular product from a global supplier that also serves competing retailers. At peak demand, access to the supplier’s limited production capacity can influence product availability and sales. The retailer’s established practice is to hold back demand forecasts until confidence in their accuracy is relatively high.
A team questions that assumption. It proposes sharing earlier forecasts with the supplier, while being transparent about their uncertainty. The expectation is that earlier visibility will help the supplier plan production and may make the retailer a more attractive customer when capacity is constrained. If that leads to better product allocation during peak periods, the retailer could protect availability and capture sales it might otherwise lose.
This is not simply a better supplier meeting or a routine information exchange. It is a proposition about how changing a relationship and a decision in the system of work could influence a commercial outcome. It might work, fail or produce unexpected effects. In each case, the reasoning and evidence could be useful—particularly when considering other strategic suppliers and products.
An expectation of clarity, not another methodology
Organisations already have skilled practitioners and established approaches to continuous improvement and problem-solving. The opportunity is not to replace them with another methodology. It is to develop a common expectation of clarity around deliberate attempts to improve performance, including those undertaken outside formal improvement programmes.
What outcome are we seeking to influence? What do we believe is shaping the current result? What will we change, and why do we expect it to help? These questions do not dictate how people investigate a problem. They make the intention visible before action and provide something meaningful to examine afterwards.
Nor should this become a new approval process. People should be equipped to act within their delegated authority and draw on colleagues’ expertise when an opportunity crosses functional boundaries. The discipline is intended to support initiative, not slow it down.
The work is not complete when the change is made
An explicit expectation gives people a point of reference when they return to the result. Did the retailer receive more product at peak demand? Did the supplier actually use the earlier forecasts to make production or allocation decisions? Were sales affected? What other factors may have influenced the outcome?
Research and development offers a useful contrast. Scientific work makes propositions explicit and examines results, including those that contradict expectations. Enterprise work is not a laboratory: conditions shift, causes interact and controlled tests are not always possible. But uncertainty makes disciplined learning more important, not less.
A favourable result does not prove that the original explanation was correct. An unfavourable result does not necessarily mean the judgement was poor. Both deserve examination. The purpose is to understand what happened well enough to make better decisions next time—not to construct a convincing story after the event.
Trustworthy learning must be developed
This capability cannot be created by asking people to complete a record. Organisations already recognise that managers need training, coaching and experience to manage individual performance well. Improving the system of work deserves the same deliberate investment. People need to learn to define outcomes precisely, distinguish assumptions from evidence, articulate a plausible mechanism of change and assess results with appropriate judgement.
A practical starting point is with trusted managers, high performers and respected subject matter experts. Through real improvement efforts, they can demonstrate what good practice looks like and establish the quality of learning worth retaining. Others can develop the discipline through examples, coaching and use. This is a path to broader capability, not exclusive permission for a few people to improve.
Capability alone is insufficient. People must also be willing to disclose what actually happened. If an unsuccessful intervention is likely to damage someone’s reputation or performance appraisal, the organisation may receive reassuring accounts rather than reliable learning. Equally, openness is not an excuse for careless reasoning or poor execution. Leaders must distinguish a reasonable hypothesis that did not hold from a poorly considered decision.
Trustworthy organisational learning requires both the ability to examine improvement well and the cultural conditions to report its outcomes honestly. Without both, an accumulated record may become extensive without becoming useful.
From individual contribution to organisational legacy
Much of what organisations know about improving performance resides in people: why an approach was chosen, which assumptions were challenged, what was tried and what conditions shaped the result. When experienced people leave or teams are reorganised, that understanding can disappear. Their successors may inherit a process or an outcome, but not the knowledge that explains it.
The answer is not to record every meeting, adjustment or useful habit. It is to retain the learning from deliberate performance interventions in a form others can understand and use. A successful forecast-sharing intervention, for example, could prompt other buying teams to examine whether similar conditions exist in their supplier relationships. The value lies in the transferable reasoning and evidence, not in assuming that the same action will work everywhere.
The knowledge is valuable beyond the immediate team and beyond the tenure of its members. A later leader might revisit an unsuccessful idea when market conditions change. Another function might recognise a dependency that was previously overlooked. A new generation of employees could begin with a better understanding of the system than their predecessors had available.
Artificial intelligence offers the potential to make this accumulated knowledge considerably more useful. It could help practitioners find relevant earlier interventions, recognise recurring patterns across different parts of the organisation and develop better-informed hypotheses about future improvements. But the reliability of these insights depends on the quality of the knowledge retained, including the reasoning, evidence and conditions surrounding earlier outcomes. AI can extend organisational learning; it cannot reliably recover understanding that was never preserved.
The enduring asset is not the volume of information stored. It is the greater organisational understanding developed through disciplined improvement made available for future use.
Building the ability to improve
Enterprise Performance is an organisation’s continuing ability to create value in fulfilment of its purpose by understanding and deliberately improving the lived system through which performance is produced. The word “continuing” matters. It asks whether improvement leaves the enterprise more capable, not only better performing for the moment.
Every deliberate improvement offers two potential returns: a better result and a better understanding of how that result can be produced. One creates value now; the other can help the organisation create value again. Even an intervention that fails to deliver its intended outcome can strengthen future decisions if the learning is sound and accessible.
An enterprise does not need to remember everything. It needs to become better at recognising, retaining and reusing what matters to improving performance. When successive leaders and teams can build on what their predecessors learned, improvement becomes more than a series of actions. It becomes an accumulating organisational capability.
ABOUT THE AUTHOR
Melanie Lisboa is an enterprise performance executive whose work focuses on how strategy, operating models, leadership, capability and execution combine to create value. Through Valde Enterprise Performance, she helps organisations develop the enduring capability to understand and deliberately improve how enterprise value is created.
© 2026 Melanie Lisboa. All rights reserved.
RELATED THINKING
The perspective presented in this essay has developed through practical experience of performance improvement and the importance of retaining what organisations learn. Established research on organisational learning, continuous improvement, knowledge retention and psychological safety explores related principles.
- Chris Argyris and Donald A. Schön (1978) — Organizational Learning: A Theory of Action Perspective.
- Mike Rother (2009) — Toyota Kata: Managing People for Improvement, Adaptiveness and Superior Results.
- Linda Argote (2013) — Organizational Learning: Creating, Retaining and Transferring Knowledge (2nd edition).
- Amy C. Edmondson (1999) — Psychological Safety and Learning Behavior in Work Teams. Administrative Science Quarterly, 44(2), 350–383.
- Marilyn Darling, Charles Parry and Joseph Moore (2005) — Learning in the Thick of It. Harvard Business Review, July–August.
Banner image generated using OpenAI's ChatGPT.