An important responsibility for managers is to see that good decisions are made, which includes training other decision makers in how to make them. In our rapidly changing health-care environment, it is important that the best decisions be made based on cost-effectiveness (tests we perform or outsource), productivity (employees we hire), service quality (how we organize services), technology (equipment and methods we purchase), and outcomes (what we accomplish for patients). A decision analysis method is described that uses an objective, scientific approach to decision making. Bayesian analysis is a statistical method that allows researchers (decision makers) to take into account data as well as prior beliefs to calculate the probability that an alternative (decision, treatment) is superior. Developing criteria, prior rating, of options, and calculating assessments and final assessment are included in the analysis. An example is provided to show how our laboratory compared routine hematology automation alternatives (automated cell counter, automated microscope, and automated flow cytometry cell counter) using the Bayesian analytical technique. Discussion follows related to how the technique is effective in managing team decisions by allowing different opinions, past experiences, and beliefs to be expressed and evaluated.