Management - Leadership

Knowledge management companies can boost success by mapping out key knowledge resources. Are they tacit or codified? Are they restricted or diffused? This map can assist in identifying links between areas of expertise and how established knowledge can be used in new ways.

Nonprofits have been slow to embrace marketing science, but the success of the Georgia Aquarium shows the potential upside. After huge success following its 2005 opening, attendance dropped precipitously and revenue fell accordingly.

Tests on rats and humans required identifying patterns which included one variation involving spacing or orientation, or two variations involving both. Rats performed better than humans on the two-variation test because they are able to integrate information more quickly, unlike humans, who apply rules in processing.

Image depicts a page from a Mercantile Agency ledger to illustrate the history of commercial credit. The Mercantile Agency (which became R.G. Dun & Company) began rating companies based on debt-payment abilities starting in 1841.

Experience is often assessed through multiple filters that restrict the ability to view the reality of the situation, and thereby cause individuals to make poor decisions. A positive outcome can lead to the adherence to a questionable strategy, and a negative one can cause one to drop a strategy that may still be useful.

Cognitive biases interfere with decision-making processes. Individuals tend to seek prompt solutions, which limits the ability to evaluate options, predict possibilities, and assess methods for achieving goals.

The primary causes of poor decision making are absence of motivation and cognitive biases, which can include how alternatives are perceived and the manner in which they are framed, and a preference for the status quo. Five steps are presented to alleviate these causes. Understand how decisions are made: some are instinctive, others are logical.

Research into the decision making process accelerated during World War II, focusing on the development of a standard approach to evaluating options with regard to an uncertain future. Decision analysis emerged in the 1960s, combining computer modeling, Bayesian statistics, expected utility, and engineering techniques.