Performance feedback contains an implicit diagnosis of what produced an outcome. When leaders diagnose at the wrong level, they may correct the individual while leaving the organizational conditions that shaped the behaviour unchanged.

A new function can exist on the organizational chart without becoming part of how the organization actually operates. Organizations often respond to significant change by creating something new. A transformation office. A strategic workforce planning function. An integration team. A centre of excellence. A new role responsible for organizational effectiveness, digital transformation, or enterprise change. The logic is understandable. If something matters, give someone respons

A few days ago, I came across a post on LinkedIn about pricing. It showed two versions of the same bottles side by side. In one, the price appeared above the product. In the other, it appeared below. The question was which version sold 35.2% more. Except the price wasn't the first thing I noticed. The labels were different. One set of bottles had white labels. The other had black labels. And my immediate thought was: Then how do we know it was the price? Maybe it was. I don't

Organizations often respond to disappointing performance with development. More coaching. More training. Better time management. Stronger prioritization. Greater accountability. Sometimes those are exactly the right interventions. But they depend upon an important assumption: that the constraint sits with the individual. A recent experience with a newly promoted management group made me question how often organizations test that assumption before acting on it. The Situation T

Organizations often associate rigour with doing more analysis. More interviews. More reviews. More stakeholders. More approvals. More checkpoints. More discussion before a decision is made. Sometimes that additional scrutiny is exactly what is needed. But rigour has another dimension that receives less attention: where in the decision process it occurs. An organization can be extraordinarily careful and still manage risk poorly if most of its scrutiny is applied downstream of

Organizations are investing heavily in AI. Yet a recurring question continues to appear: How do we measure whether AI is actually creating value? Organizations can often measure adoption. They know how many employees are using a tool. How many licenses have been deployed. How many tasks have been automated. How frequently particular capabilities are being accessed. Some can estimate hours saved. But translating those measures into organizational value is proving more difficul

AI is everywhere. It is embedded in products, workflows, search tools, analytics platforms, customer experiences, software development, decision support, and increasingly the everyday work of employees. Organizations are investing in it. Leaders are talking about it. Roadmaps are being built around it. And increasingly, organizations describe AI itself as part of their strategy. But there is an important distinction worth making. AI can enable a strategy. It can dramatically

Organizations make decisions in the present. But those decisions rarely remain there. A decision that solves an immediate problem may create a constraint several months from now. An investment that creates pressure today may build capability that matters years later. A temporary workaround may be exactly what the situation requires, while becoming increasingly problematic if it quietly becomes permanent. This is one of the difficulties of organizational decision-making. We ha

An organization can make a series of reasonable decisions and still produce an unreasonable outcome. This becomes particularly visible when business conditions change. Consider a professional services office facing an unusual combination of circumstances. Top-line revenue remained relatively close to plan. On the surface, that suggested the business was performing reasonably well. But other measures told a very different story. Utilization was well below expectations. Revenue

Organizations make problems visible. A project is late. Utilization is low. Turnover is increasing. A team is overwhelmed. Customer complaints are rising. A new technology is producing work faster than expected. These observations matter. They tell us that something is happening. But they do not necessarily tell us why. Sometimes the explanation really is close to the surface. A system went down. Demand unexpectedly increased. Someone made a mistake. A deadline was unrealisti

Almost every organization has a process that works differently in practice than it does on paper. There is the formal process. And then there is the way people know the work actually gets done. An approval is bypassed because it takes too long. A spreadsheet fills a gap between two systems. Information is shared through an unofficial channel because the formal one does not reach the right people. Several steps in a process are routinely skipped because the people doing the wo

Organizations are very good at presenting us with problems. A project is late. A client is unhappy. A team is struggling. Turnover is increasing. A new process is not being adopted. The instinct is often to move quickly to the next question: What should we do about it? That instinct is understandable. Problems create pressure for action, and action creates a sense of progress. But there is another question that comes first: What kind of problem are we actually looking at? Bec