Evidence-Based Management (EBM)
Evidence-based management uses best available evidence to reduce biases and improve decision-making under uncertainty. However, applying the medical model of evidence-based practice to management is limited due to the academic-practice gap and lack of standardized education and credentialing.
THE IDEA
Organizational management involves choices under uncertainty. Evidence can help managers compare assumptions, identify weak options, and learn from outcomes. Its value need not depend on finding a uniquely best choice: avoiding a costly mistake can matter even when uncertainty remains.
Banasiewicz compares this with predictive customer models. A model may help identify people unlikely to buy a product, allowing a marketer to concentrate effort elsewhere. Whether that improves returns depends on prediction quality, campaign costs, and how customers respond. Removing low-scoring customers does not by itself establish that a campaign causes additional purchases or earns a higher return.
He also uses blackjack card counting as an analogy. A player can improve the conditions under which a bet is placed without knowing the result of the next hand. The analogy illustrates a distinction between improving a decision process and guaranteeing its outcome.
The author questions how directly an evidence-based approach developed in medicine transfers to management. Medical training, credentials, and continuing education provide some shared foundations for applying research. Management education and experience vary more widely, and much practical organizational knowledge comes from outside academic research. These differences can affect what evidence is available and how it should be used.
Systematic reviews and meta-analyses can still inform management decisions. Banasiewicz’s concern is making academic research the dominant source while giving too little attention to organizational data and practical experience. The challenge is to retain explicit appraisal of evidence while adapting the process to the particular decision, organization, and available information.
When to use it
A marketing manager uses customer analytics and pilot test data instead of intuition to decide on a promotional campaign.
An HR department reviews meta-analyses on interview validity to design a more effective hiring process.
A supply chain manager employs historical data and forecasting models to reduce inventory waste rather than relying on past experience alone.
A project team uses structured decision-making frameworks with external evidence to evaluate competing strategic options.
FROM THEORY TO EVERYDAY LIFE
In practice
Predictive Modeling for Customer De-Selection
A marketer uses a model to identify customers unlikely to purchase and tests whether excluding them improves campaign returns. A higher predicted response rate among the remaining customers is useful only if the campaign’s actual benefits justify its costs.
Blackjack Card Counting
Card counting can support better-informed betting in blackjack under suitable conditions, without determining any particular hand. Banasiewicz uses it as an analogy for improving the odds of organizational decisions rather than guaranteeing favorable results.
A MOMENT TO REFLECT
Put it to work.
How can managers incorporate evidence from diverse sources beyond academic research to improve decision-making?
What are some common cognitive biases that evidence-based management can help overcome in your organization?
How might the academic-practice gap be bridged to make evidence-based management more actionable?
Often confused with
CONTINUE THE CONVERSATION
Source texts
- Evidence-Based Decision-Making How to Leverage Available Data and Avoid Cognitive Biases (Andrew D. Banasiewicz)