What are Heuristics?
Heuristics are a problem-solving method that uses shortcuts to produce good-enough solutions given a limited time frame or deadline. Heuristics are a flexibility technique for quick decisions, particularly when working with complex data. Decisions made using an heuristic approach may not necessarily be optimal. Heuristic is derived from the Greek word meaning “to discover”.
Digital technology has disrupted all industries including finance, retail, media, and transportation. Suddenly, once typical daily activities have become outdated. Checks are deposited to bank accounts without visiting a local branch, products and services are purchased online and take-out food is delivered by food service delivery apps. Technology is creating data, which is increasingly shared across multiple industries and sectors, and a professional in any industry may find themselves working with mounds of complex data to solve a problem. Heuristic methods can help with data complexity given limited time and resources.
- Heuristics are methods for solving problems in a quick way that delivers a result that is sufficient enough to be useful given time constraints.
- Investors and financial professionals use a heuristic approach to speed up analysis and investment decisions.
- Heuristics can lead to poor decision making based on a limited data set, but the speed of decisions can sometimes make up for the disadvantages.
Why Use Heuristics?
Heuristics facilitate timely decisions. Analysts in every industry use rules of thumb such as intelligent guesswork, trial and error, process of elimination, past formulas and the analysis of historical data to solve a problem. Heuristic methods make decision making simpler and faster through short cuts and good-enough calculations.
The Disadvantages of Using Heuristics
There are trade-offs with the use of heuristics that render the approach prone to bias and errors in judgment. The user’s final decision may not be the optimal or best solution, the decision made may be inaccurate and the data selected might be insufficient leading to an imprecise solution to a problem. For example, copycat investors often imitate the investment pattern of successful investment managers to avoid researching securities and the associated quantitative and qualitative information on their own.
By using a heuristic approach underlying past performance, copycat investors hope that the formulas used by these managers will continually earn them profits, but this is not always the case. For example, the crash of Valeant Pharmaceutical International was a shock to investors when the company saw its stock plunge 90% from 2015 to 2016. Valeant was a stock held in the portfolios of many hedge fund managers and the investors copying them.
A popular shortcut method in problem-solving is Representativeness Heuristics. Representativeness uses mental shortcuts to make decisions based on past events or traits that are representative of or similar to the current situation. Say, for example, Fast Food ABC expanded its operations to India and its stock price soared. An analyst noted that India is a profitable venture for all fast food chains. Therefore, when Fast Food XYZ announced its plan to explore the Indian market the following year, the analyst wasted no time in giving XYZ a “buy” recommendation.
Although his shortcut approach saved reviewing data for both companies, it may not have been the best decision. XYZ may have food that is not appealing to Indian consumers, which research would have revealed. Other prevalent heuristic approaches for decision-making and problem-solving include Availability Bias, Anchoring and Adjustment, Familiarity Heuristic, Hindsight Bias and Naïve Diversification.