Decision-Making Biases

Information Bias

Definition

Information bias is the tendency to seek, gather, and value additional information even when it cannot possibly improve the quality of a decision – and may actually worsen it through delay, confusion, or false confidence. The bias reflects a deep human intuition that 'more information is always better,' but research consistently shows that beyond a certain threshold, additional data does not improve decision accuracy and can even degrade it by introducing noise and complexity. In medical diagnosis, business strategy, and everyday choices, the compulsion to gather 'just a little more' information often delays action, increases costs, and creates analysis paralysis without producing better outcomes.

Real-world example

In a classic study by Baron, Beattie, and Hershey (1988), participants chose to obtain additional diagnostic information before making medical decisions – even when they were told explicitly that the extra information was non-diagnostic (irrelevant to the decision). The mere availability of more information felt valuable, regardless of its actual utility.

In business, information bias drives the proliferation of dashboards, reports, and data requests. Teams commission yet another market analysis or customer survey before launching a product, not because the existing data is insufficient, but because the act of gathering information provides psychological comfort and the illusion of thoroughness. Jeff Bezos famously advocated for making decisions with about 70% of desired information, arguing that waiting for 90% makes you too slow.

In healthcare, information bias contributes to overtesting: doctors order additional scans and blood work that are unlikely to change the treatment plan, exposing patients to unnecessary costs, anxiety, and even risks (false positives leading to invasive follow-ups).

In personal life, the bias shows up as 'research mode' – spending hours reading product reviews, comparing options, and seeking opinions long past the point where additional research changes the optimal choice.

Supplementary perspective

Information bias connects to the illusion of control (gathering information feels like taking action), choice overload (more options and data create more difficulty), and the sunk cost fallacy (having invested time in research, people feel compelled to continue). It also relates to the distinction between 'signal' and 'noise' in information theory: useful information (signal) improves decisions, but irrelevant information (noise) can actively mislead by creating false patterns or diluting attention from what matters. Herbert Simon's concept of 'satisficing' – choosing an option that meets a threshold rather than seeking the absolute best – is a powerful antidote to information bias.

Practical advice

Recognize

—Before seeking additional information, ask the diagnostic question: 'Would any answer to this question change my decision?' If not, you don't need the information.
—Notice when 'doing more research' is functioning as procrastination rather than genuine decision improvement.
—Watch for teams that keep requesting reports but never change their conclusions based on the new data.

Counteract

—Define in advance what information is necessary and sufficient to make the decision – and stop when you have it.
—Set explicit decision deadlines to prevent indefinite information gathering.
—Use the 70% rule: if you have 70% of the information you'd ideally want, make the decision and course-correct as needed.
—Practice distinguishing signal from noise: focus on the 2-3 pieces of information with the highest diagnostic value.

Ethical use

—Present people with relevant, actionable information rather than overwhelming them with comprehensive but unfocused data dumps.
—In healthcare, apply evidence-based guidelines for testing to avoid exposing patients to unnecessary procedures.
—Design information systems that highlight diagnostic information and de-emphasize noise.