Performance Models

Introduction

This article explores different models that have been researched for understanding performance. The importance of the behavior concept when analyzing group performance is discussed. How GRI’s adaptive profiles measure individual and organizational performance is presented.

Management Control

The traditional, historical, and often implicit understanding of an organization’s performance is that the organization functions like a machine, with its performance measured by efficiency, predictability, and control. The goal of the organization is to optimize individual parts and processes to produce a specific, measurable output. With this vision in mind, management control, sometimes called "management audit," "management accounting," "managerial control," or simply “management,” depending on the context, has focused on :

• Decision-making for improving the decision-making process through planning and coordination. Planning is about setting strategic and performance goals, monitoring the quality and variety of resources. Coordination is about integrating disparate elements to achieve goals.
• Control for providing feedback and ensuring that the input-output system is properly aligned, and to motivate or evaluate employees.
• Reporting information to managers throughout the organization that relates to their values, preferences, and what employees need to focus their attention and energy on.
• Learning and training for understanding changes in the internal and external environment, as well as the connections between their various components.
• External communication to disseminate information to constituents outside the organization: shareholders, analysts, suppliers, partners, customers, etc.

It’s only progressively that concerns for reporting, learning, and training have gradually emerged. Companies began to differentiate diagnostic from interactive control. While the diagnostic refers to the piloting of routines and the implementation of strategy, interactive control relates to piloting by managers, the focusing of the attention of employees, learning, and the formulation of strategy.

Gradual Evolution

Anthony's seminal work played a major role in the development of management control systems. However, the definition he gave of control systems led to considering these systems as means of control by accounting measures of planning, steering, and integrating mechanisms. The focus was on accounting measures, but the non-financial measures were neglected. The initial objective of accounting management systems, to provide information to facilitate cost control and measure the performance of the organization, was transformed into that of compiling costs with a view to producing periodic financial statements.

The role of short-term financial performance measures progressively became inappropriate for the new reality of organizations. The non-financial indicators based on the strategy of the organization were of crucial importance. Gradually, the performance measurement framework began to reconcile the use of financial and non-financial measures. They evolved from a cybernetic vision where the measures are about costs, financial control, planning, and management control, towards a new era reflecting a holistic vision where the performance measures are focused on process efficiency and added value in management through non-financial measures.

Performance Models

An organizational performance can be approached through various models, which address, on one hand, aspects of its measurement and control, and on the other hand, its conceptualization. Both perspectives refer to it using the terms efficiency or performance, which ultimately can be considered synonyms. Management control research has traditionally focused on performance measures with the cybernetic model. Considering the human aspects amid non-financial measures has allowed the holistic model to gradually overcome some limitations of the cybernetic model.

Other performance models each contribute to defining and implementing procedures and performance measures, depending on the context (research, societal, leadership, organizational development, etc.) and the authors. Several approaches have been proposed for categorizing these performance models. For example, they can be grouped into three categories based on their origins in economic, organizational, and social research. Others have suggested three clear categories: objectives, system, and stakeholders.

The different performance perspectives have been regrouped below into seven categories according to these three grand categories. This grouping enables highlighting different analytical anchor points and limitations. The seven approaches are summarized in the following table:

Models of performance

Models	Focus
Cybernetic	Accounts for the financial and production metrics.
Holisitc	Extends from the cybernetic model with individual and social aspects.
Objectives	Objectives are set and managed at different levels of the organization.
Systems	As a system, an organization’s parts and intangible resources need to be managed.
Stakeholders	Stakeholders' characteristics need to be leveraged.
Behavioral Values	Extends from the stakeholder model to understand organizations based on individual behavioral values and preferences.
Non-performance	Minimize non-performance and ineffectiveness.

Besides performance models, which only depend on financial, production, and other tangible data, holistic and stakeholder models have increasingly used new research methods and included more sophisticated data and theories about people and their organizations. The nature of this data has evolved over time, from the early days of scientific psychology in the 1900s, which was firmly rooted in behavioral research, to today, where emotions and neuroscience play a significant role.

Personality has been a key concept in many models early on and continues to be widely used in research and practice. In research, it is present in sociology, anthropology, and psychology with its different schools. Personality carries many connotations, though. Despite its extensive use in recruitment, management science, and coaching in day-to-day business, the idea of personality remains coupled to the early days of psychometry, when it was used with deviant behaviors in psychiatry and clinical psychology. Using the personality concept while avoiding its negative connotation remains a constant challenge in practice.

Centrality of Behaviors

Performance models based on actions and values include a behavioral component that makes them especially useful for research and practical applications. Behaviors are observable, which allows us to discuss and analyze them more effectively, increasing the chances of reaching consensus about what they are and what can be done with them. They are also a fundamental part of the personality concept, including within organizations. Behavioral traits and typologies have been extensively studied and utilized, both in recruitment and coaching. Aside from ethical conduct and social responsibility, the behaviors people value—or behavioral values—that they are emotionally interested in and most likely to express are central to how people perform.

Analyzing and classifying behaviors using different models at the individual, team, company, and societal levels uncovers a limited set of behavioral factors. When combined, these factors can help explain behaviors; at GRI, we estimate that up to 90% of observable behaviors in organizations are explained by four factors. As science progressed, so has our sophistication in analyzing and assessing people and in modeling and representing their behaviors.

Beyond Intuition

As discussed in articles about holistic and stakeholder models, the concepts used by models for understanding people are numerous: intelligence, mindset, competencies, skills, preferences, styles, beliefs, motivation, drives, emotions, creativity, interests, and more. Some are broad and universal, while others are narrow and applicable only in limited contexts. Some are easy to change or adapt; others are less so. Some characteristics can be gathered in a few clicks on the Internet; others can only be attained through more sophisticated techniques than direct observation and intuition, or even AI, by making assumptions based on the Internet.

Discussion on assessment techniques, what they assess, and how they work goes beyond what can be addressed here in this article. In a few words, the survey technique can measure performance by applying statistics that we can’t do as human beings. We, however, apply our own and limited subjective statistics with our values and reference points, something we’ve referred to in our research at GRI as our private techniques. Private techniques are valuable individually, but not effective enough when used with others and group performance.

Organizational Performance

Adaptive profiles, as we measure them at GRI and show in this example here on the right, accurately account for individual performance. The metrics produced reflect an individual's behaviors, affects, and mindset that all relate to each other as well as to the individual's preferences, interests, and values.

With adequate content and statistics, the metrics also apply to positions, teams, companies, and even at a societal level. When provided in a condensed way, the results can be learned, memorized, used— and in short, make sense— in multiple situations, where they can bring their value.

The adaptive profile is produced by answering two questions and applying statistics. If you see this profile for the first time, it will not tell you much. It is shown here only to illustrate what it looks like. At an organizational level, the information from the adaptive profiles is regrouped and compared with that of position and group profiles for measuring and analyzing performance.