The old numbers become anchors, which the forecaster then adjusts based on other factors. In the HBR journal in January 2006, anchor bias at the workplace was illustrated with the following example, “A marketer attempting to project the sales of a product for the coming year often begins by looking at the sales volumes for past years.
THE ANCHORING TRAP EXAMPLE SOFTWARE
Anchoring bias is therefore the most basic and common decision bias that we encounter in software development. We simply trust the numbers and more often than not, base our decisions on this sometimes unverified information. However, most of us don’t question where the data comes from. Logically thinking, we gather data long before aligning to a decision. This article is not a catalog of all possible biases or traps out there, but is intended to get you thinking on this front.
THE ANCHORING TRAP EXAMPLE HOW TO
I have also provided suggestions on how to identify, analyze, and remediate each of these aforementioned biases. So what are the biases we need to be aware of when working on software designs? In this article I have highlighted a few important decision and design biases that I have come across in my journey. While many design flaws can be corrected by iterative development models in the software application development process, the real problem lies in the decision space. This adds pressure to architect applications quickly, which can impact the ability to gather all the relevant information and potential options beforehand. When we design software architectures, the design is often initiated by a business need accompanied by a stringent time constraint. This simple cognitive response led to many core biases making their way into how we process information and make decisions.įast forward to the present day. Since time is a luxury during many survival situations, relying on assumptions helped our ancestors to assume an immediate understanding, and proceed with that understanding, to aid their survival.
After all, an unbiased thought process requires intense computation and time to derive an outcome. This basic thought process helped our ancestors for thousands of years and honed our flight or fight responses. So, cognitive bias helped keep enough of us alive to be pondering the process today.” The option chosen was probably the one that worked the last time the situation occurred. In this instance, our ancestors needed some information processing shortcuts. We had to make a quick decision between fight or flight to avoid being killed. “The human brain was originally built for survival. Why are biases so common?Ī recent article in Forbes magazine on cognitive bias stated: My hope is that with this information, you will be better equipped with the tools needed to create robust design suggestions, especially around architecture and UX design. I will then introduce some tactics for handling and counteracting these biases. In this article, I will highlight some of the top decision biases and design biases that are most prevalent in the field of software design and development and that team leaders need to be aware of. If you own software design decisions for your line of business or organization, it is important to ensure that your design decisions are reviewed thoroughly, by you and your peers, and that a proper mitigation strategy is implemented to keep the impact of any decision bias to a minimum. Therefore, in order for an organization to combat these biases, a sound, data-driven approach is necessary while making decisions. Imagine what could go wrong if just one of these participants makes a decision in a biased fashion? If left unaddressed, these decision biases can lead to unforeseen consequences, seeping into how we make decisions in our work, ultimately impacting our customers, and leading to costly repairs and refactoring over time. The product designer, owners, software architects and developers all try to interpret this feedback, localize them to their scope of work, and derive a solution. In the software industry there is a strong feedback factor to everything we do that helps us innovate on new ideas. Let us take our software industry as an example.
You may wonder what could possibly go wrong because of this. But those same organizations often overlook the cognitive biases that are present in our daily decision making processes.
The Oxford dictionary defines bias as "prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair.” Many organizations invest heavily in educating their associates on workplace bias-including biases based on race, creed, religion, sex, disability or age.
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