Performance Management is the system by which an organization links strategy to the objectives of functions, teams, and individuals through meaningful and targeted KPIs, reliable data, frequent feedback, and consistent recognition criteria. It is not an annual evaluation sheet: it is meant to transform evaluation into decisions and improvement. In this article, we see why KPIs and rewards alone are not enough and how to build a system that truly drives behavior and performance.
In many companies, objectives, indicators and reward systems already exist. Yet, they do not always help to make better decisions or to guide daily work. Strategy may remain distant from the activities of the functions, responsibilities may not be fully clear, and KPIs may multiply without making priorities more understandable.
The problem, therefore, is not necessarily a lack of data. It is the connection between what the company wants to achieve, what it asks of people, and what it then measures and recognizes. If these elements remain separate, measurement risks becoming a reporting exercise: numbers are collected, dashboards are prepared, deviations are commented on, but the system has little impact on choices and behaviors.
A productivity indicator, for example, may appear positive while service quality or continuity deteriorates; an individual goal can be achieved without the team improving its overall performance. These are signs that remind us why KPIs should be read in relation to each other and in relation to the priority they should represent.
An effective performance management system starts with a more focused question: what results really matter to the organization and how can they be translated into understandable responsibilities, meaningful indicators, and constructive moments of discussion?
Performance Management is often associated with annual evaluations or the completion of an individual scorecard. These tools can be part of it, but they do not exhaust its meaning. Considering it only as a periodic appointment reduces the possibility of intervening throughout the year, clarifying expectations, and promptly correcting a direction that is moving away from priorities.
A broader model links strategy, organization, KPIs, data, feedback, and recognition systems. Its purpose is not to control every activity or assign a score to every person. It is to make the expected contribution clearer and create the conditions for the information collected to help managers and teams decide and improve.
This perspective also changes the role of indicators. A KPI is not useful just because it is available or easy to calculate. It must help to interpret a relevant result and to understand where action can be taken. When numbers do not guide a decision, adding more of them rarely solves the problem.
A strategic priority becomes concrete when the people involved understand what it really means in their own work environment. Therefore, the definition of objectives cannot stop at the corporate level. It is necessary to link priorities to the responsibilities of functions, teams, and individual roles, while keeping each level’s contribution to the overall result visible.
The transition requires organizational clarity. If decision-making boundaries, autonomy, or accountability are ambiguous, even the most precise indicators can generate different interpretations or difficult expectations to manage. A person should be able to understand what results are required of them and how they can actually influence them. Similarly, a manager should be able to read both the results of their own area and how the team contributes to shared priorities. Based on our experience, our Knowledge Office has redeveloped an explanatory table on the main indicators by role:
| Level | What measure | Examples of indicators |
|---|---|---|
| Company / Position | Overall result and strategic priorities | EBITDA, quality, productivity, safety, CO2 |
| Team | Shared results and coordination skills | Shift efficiency, quality, and compliance with the plan |
| Individual | Contribution directly attributable to the person | Reliability, compliance with standards, data quality |
Consistency between levels is important because behaviors adapt to what is observed and recognized. If a system considers only the individual outcome, it can weaken collaboration; if it only looks at the overall data, it can make the contribution and responsibility of the different functions less visible. The point is not to choose just one level, but to avoid the different levels contradicting each other.
The growth in the number of KPIs often does not coincide with improved performance control. Too many indicators can make it difficult to distinguish what deserves attention, add to the monitoring burden, and encourage data-driven management rather than results-oriented management. A more focused selection, on the other hand, helps maintain focus on priorities and discuss deviations more concretely.
Before introducing or linking an indicator to the evaluation, it is useful to clarify which decision it should support, what level of responsibility it refers to, and whether those being evaluated can influence it. The quality of the information also matters: an outdated data set, produced by different sources or without a defined responsibility, can undermine trust in the system.
Not all indicators have the same function. Some serve to monitor the progress of a process; others can be relevant for assessing the contribution to an objective. Confusing these purposes can lead to more complex systems and less transparent evaluations. The design of KPIs therefore requires a balance between what is useful to monitor and what is sensible to use to guide accountability and recognition.
Data takes on value when it enters into a useful conversation. If the comparison takes place only at the end of the year, many of the information arrives too late to support corrections or learning. A more continuous pace of feedback throughout the year allows for the results to be read in their context, to recognize progress, and to address difficulties earlier.
The feedback is not a one-way communication or a comment on the numbers. It is an opportunity to compare objectives, progress and conditions that have influenced the work, clarify any obstacles and agree on the next steps. To be credible, it must be based on understandable information and explicit accountability; it cannot turn into a series of judgments disconnected from operationality.
The frequency should also be chosen with care. Too infrequent a comparison limits the ability to learn; too frequent a comparison, if it does not lead to decisions, risks becoming an additional obligation. The goal is to maintain a cycle of observation and comparison that is consistent with the possibility of intervening.
Recognition and Reward systems communicate what results and behaviors the organization considers important. Therefore, they must be consistent with corporate priorities, with the responsibilities of roles, and with the balance between individual contribution and team results.
An automatic link between reaching a threshold and receiving a reward may seem simple, but it does not always represent the actual contribution. Goals can depend on different factors, and not everyone has the same level of influence on the outcome. Furthermore, frequent recognition and periodic rewards can overlap if they do not have distinct goals.
A sustainable system must be readable: people must be able to understand the criteria and the link between results, responsibility, and recognition. Transparency does not eliminate all complexity, but it reduces ambiguity and arbitrary interpretations. From June 7, 2026, the topic is also regulatory: Legislative Decree 96/2026, which implements Directive (EU) 2023/970 on wage transparency, requires companies to make clear the criteria by which salaries and promotions are determined. The reward thus becomes part of the management system, not an isolated element that intervenes only downstream of the evaluation.
A performance management model is only useful if people understand its logic and trust the information on which it is based. Trust weakens when goals change without comparison, when the data sources are unclear, or when similar results produce different assessments without understandable criteria. In these cases, attention shifts from improving the work to discussing the calculation method.
The choice of what is measured also influences behavior. If an indicator is easily attainable but does not represent the company’s priority, it may end up absorbing time and attention at the expense of more relevant results. If, on the other hand, the goals are perceived as beyond the control of the people, measurement may appear unfair and lose its ability to provide guidance. Therefore, it is not enough that a KPI is technically available: its meaning must be shared and consistent with the level of responsibility it refers to.
A new dashboard or a formal review of the evaluation scorecard are not the solutions. A comparison between what the organization declares as a priority, the behaviors that the system encourages, and the operational conditions in which people work are the foundational elements of the system. It is in this comparison that any inconsistencies between objectives, responsibilities, and recognition criteria emerge.
Managers and supervisors are the link between the system design and the daily activities of the teams. They must be able to read the results without getting stuck in the details, clarify priorities and responsibilities, and use the feedback to understand whether a deviation indicates a problem in execution, coordination, or working conditions. This requires a system that makes information understandable, but also provides the time and responsibility to discuss it.
The performance of the coordinator does not end with individual results. It also includes the ability to make the expected work clear, to support collaboration, and to facilitate the achievement of the team’s results. Considering only the personal data can leave out an important part of the managerial contribution; at the same time, attributing any outcome of the group to the manager without considering the context does not create true accountability.
For this reason, a coherent model combines different levels of observation and feedback opportunities. It is not about adding a new evaluation grid, but about making the link between responsibilities, results, and people development clearer. The system must help managers conduct concrete and timely conversations, not provide them with a score to communicate later.
Dashboards and digital tools can make the reading of results more timely, but they do not by themselves define what is important to measure. Before technology comes the choices regarding the organizational model, KPIs, the quality of information, and the decisions that the system must support.
When data comes from different systems, such as ERP, MES, HRIS, CRM or operational applications, their integration can help reduce manual tasks and provide a more up-to-date view. But for this to happen, reliable data, clear responsibilities for their management, and a shared understanding of the indicators are necessary. A richer dashboard does not compensate for inconsistent definitions or incomplete information.
Artificial intelligence can also support analysis, highlight trends or anomalies, and facilitate the preparation of moments of confrontation. Its contribution remains, however, linked to the quality of the data and the rules by which information is interpreted. Technology can accelerate the cycle, while governance and managerial judgment must continue to determine what matters and what decisions to make.
Corporate priorities can change when operational conditions or the context in which the company operates change. A performance management system must maintain its connection with the strategy even as it evolves; otherwise it risks continuing to measure with precision results that are no longer central. Stability of the rules is important, but it should not turn indicators into an autonomous goal.
This does not mean constantly changing objectives and criteria, nor revisiting them every time a result is difficult to achieve. It means planning for moments of review when the organization can understand whether the indicators continue to represent priorities and whether people have the appropriate information and responsibility to act. The frequency of monitoring should also be commensurate with the actual possibility of making decisions or correcting course.
The balance is delicate: a system that is too rigid can lose its grip on strategy, one that is too unstable can compromise understanding of the goals and trust in the criteria. Value comes from the ability to maintain a clear direction and, at the same time, to use data to learn and improve the way the organization works.
Performance Management works when its components speak the same language. Strategic priorities are reflected in objectives, objectives are linked to understandable responsibilities, indicators help to read performance, and feedback enables action. Recognition and reward, finally, strengthen behaviors and results consistent with that direction.
This is not achieved by adding a new tool or asking people to update more reports. It requires a coherent design and a comparison between strategy, organization, data, and management practices. When one of these links is missing, recognizable signs emerge: priorities that do not reach the teams, KPIs that are difficult to interpret, overlapping responsibilities, occasional feedback or rewards that do not reflect what the company claims to want to promote.
For companies, the challenge is to move from the question “what KPIs should we introduce?” to a broader one: “what results do we want to drive and what conditions are needed for people to contribute?”. It is from here that measurement can become a tool for governance and improvement, rather than a periodic snapshot of performance.
Designing roles, indicators, and reward systems that are consistent with the strategy is one of the areas of support provided by our Organization & Training Team.
How to connect strategy, roles, KPIs, data, feedback, and recognition systems into a coherent model? In the Digital Talk scheduled for November 11, 2026 (17:00–18:00, live streaming), ’Performance Management: from KPIs to results, from strategy to people," Umberto Mirani and Giuseppina Ganci will delve into this step and the role that data, digitalization, and AI can play in supporting it.
Performance Management is the system by which the company links strategy to the objectives of functions, teams, and individuals, using targeted KPIs, reliable data, frequent feedback, and consistent recognition criteria. Annual evaluation is only one part of it: by itself, it prevents clarifying expectations and correcting direction during the year.
The problem usually isn’t a lack of data, but the disconnect between what the company wants to achieve, what it asks of people, and what it measures and rewards. So measurement becomes reporting: dashboards and comments on discrepancies are produced, but little is done to influence choices and behaviors.
Few understandable KPIs are chosen, clarifying first which decision they support, at what level of responsibility they refer to and whether those being evaluated can influence them. The data must be updated, with a defined single source and responsible person. Indicators that observe a process must be distinguished from those used to assess contribution.
At the company or function level, results and strategic priorities are measured, such as EBITDA, quality, productivity, safety, and CO2 emissions. For the team, shared results count, such as shift efficiency, quality, and compliance with the plan. For the individual, indicators that are attributable to the person are needed: reliability, compliance with standards, and data quality.
From June 7, 2026, Legislative Decree 96/2026, which implements Directive (EU) 2023/970 on wage transparency, requires companies to clarify the criteria used to determine salaries and promotions. The reward thus becomes an integral part of the management system, not an isolated element following the evaluation.
No, dashboards and digital tools make reading the results more timely, but they do not decide what to measure. Even when integrated with ERP, MES, HRIS, and CRM, reliable data, clear responsibilities, and shared definitions of indicators are needed. AI can highlight trends and anomalies, but governance and managerial judgment determine the decisions.
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