A surreal illustration depicting the challenges of collective decision-making and incomplete information.

Groupthink Trap: How Collective Sampling Can Lead to Bad Decisions

Elliot Brynn in Business & Economy August 2025 • 4 min read.

"Uncover the hidden dangers of group decision-making and learn how collective sampling can lead to learning inefficiencies in teamwork, committee work, and beyond."

Committees, teams, and boards often grapple with a critical question: When is it time to stop gathering information and take action? This decision, seemingly straightforward, is often complicated by conflicting interests among group members. Each member's desire to continue gathering information hinges on what they've already learned, their individual preferences regarding potential actions, expectations about the group's future moves, and, most importantly, the collective decision-making process for information collection.

While dynamic information acquisition has been extensively studied in individuals, its group dynamics remain relatively unexplored. Consider a company's board members deciding on a potential acquisition. Before making a final call, they gather information through market research. Collectively, the board decides how detailed the research should be and whether additional data is necessary. But how do conflicting interests and decision-making processes affect information gathering and the final decision?

New research explores these complexities, presenting a model of collective dynamic information acquisition focused on the pivotal stopping decisions. By extending a sequential sampling model to strategic group situations, the research sheds light on how players collectively decide when to stop acquiring costly signals about a binary state of the world, impacting efficiency and outcomes.

The Pitfalls of Collective Sampling: Why Groups Stop Learning Too Soon

A surreal illustration depicting the challenges of collective decision-making and incomplete information.

The study introduces the concept of a 'collective stopping rule,' where players decide when to stop sequential sampling through decisive coalitions. The research develops a method to characterize equilibria using an ex-ante perspective. Instead of focusing on stopping strategies, players choose distributions over posterior beliefs subject to constraints. Equilibrium sampling regions are characterized via a fixed-point argument based on concavification.

One key finding is that collective sampling can generate learning inefficiencies. Having more decisive coalitions often reduces learning, leading to situations where groups stop acquiring information prematurely. This phenomenon impacts various real-world scenarios, from committee searches to competition in persuasion.

Control-Sharing Effect: Because players share control over stopping, they tend to stop earlier than if they were making decisions alone. This can lower the option value of waiting for more information.
Preference Misalignment: When players' preferences are not aligned, inefficiencies in collective information acquisition are amplified.
Pareto Inefficiency: Collective information acquisition is generally Pareto inefficient, meaning players learn too little under certain stopping rules or possibly too much under others.

To illustrate these concepts, the study considers two economic applications: committee search and dynamic competition in persuasion. In committee search, members dynamically acquire relevant information under a collective stopping rule, simplifying the problem to the interaction between two pivotal players. In competition in persuasion, multiple senders compete to persuade a receiver, with increased competition leading to more information revelation, though often less than in static scenarios.

Navigating the Challenges of Collective Decision-Making

While this research provides valuable insights into the dynamics of collective sampling and its potential pitfalls, it also opens doors for future exploration. By understanding how groups acquire information and make decisions, we can develop strategies to mitigate inefficiencies and improve outcomes in various settings. Further research can explore the impact of different communication structures, leadership styles, and individual biases on collective information acquisition, ultimately leading to more informed and effective decision-making in teams and organizations.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2311.05758,

Title: Collective Sampling: An Ex Ante Perspective

Subject: econ.th

Authors: Yangfan Zhou

Published: 09-11-2023

Everything You Need To Know

What is 'collective sampling' and how might it negatively impact group decision-making?

'Collective sampling' refers to how groups collectively gather information before making a decision. It can lead to negative impacts because groups might prematurely stop acquiring information, resulting in suboptimal choices. This is due to various factors, including the 'control-sharing effect', where shared control leads to earlier stopping, and 'preference misalignment', which amplifies inefficiencies. This premature stopping can impact scenarios such as committee searches and persuasion, where more thorough information gathering could lead to better outcomes.

What is the 'collective stopping rule' and how does it influence learning within a group?

The 'collective stopping rule' defines how a group decides when to cease sequential sampling of information. Research indicates that having more decisive coalitions can reduce learning, leading groups to stop acquiring information prematurely. This inefficiency stems from the fact that individual preferences and the desire to act quickly can override the collective benefit of gathering more data. The research characterizes equilibrium sampling regions using a fixed-point argument based on concavification to address the problem.

What are the implications of 'preference misalignment' in the context of collective information acquisition?

'Preference misalignment' refers to situations where group members have conflicting interests or priorities regarding potential actions. When these preferences are not aligned, inefficiencies in collective information acquisition are amplified. This means that groups are even more likely to stop gathering information too soon, as members prioritize their own interests over the collective goal of making an informed decision. It is one of the factors contributing to the 'Pareto inefficiency', where players tend to learn too little under certain stopping rules or potentially too much under others.

How does the 'control-sharing effect' contribute to suboptimal decision-making in groups?

The 'control-sharing effect' arises because when players share control over stopping, they tend to stop earlier than if they were making decisions alone. This is because each member's desire to continue gathering information hinges on what they've already learned, their individual preferences regarding potential actions, expectations about the group's future moves, and the collective decision-making process for information collection. This premature stopping lowers the option value of waiting for more information, leading to less informed and potentially suboptimal decisions. In this case the sampling regions are characterized via a fixed-point argument based on concavification.

In what real-world scenarios does the inefficiency of 'collective sampling' manifest, and what can be done to mitigate these inefficiencies?

The inefficiency of 'collective sampling' can manifest in various real-world scenarios, such as 'committee searches' where members must gather relevant information to make decisions and 'dynamic competition in persuasion', where multiple senders compete to persuade a receiver. To mitigate these inefficiencies, strategies can be developed to improve communication structures, leadership styles, and address individual biases within the group. Further exploration into these factors can lead to more informed and effective decision-making, ultimately improving outcomes in teams and organizations.