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What do you do if your decision making process as an IT professional is influenced by biases?

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As an IT professional, you need to make strategic decisions that affect the performance, security, and usability of your systems and solutions. However, your decision making process may not always be objective and rational. You may be influenced by biases, which are mental shortcuts or assumptions that can distort your judgment and lead to errors or inefficiencies. In this article, you will learn what are some common biases that affect IT decision making, how to identify them, and how to overcome them.

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Shayan Akbari

Head & founding father Of AHRAR Universal Organization - Origin and founder Of Universalism - On a Mission to build the…
Chibuike Nwafor

Software Engineer - Who builds web apps and software while coding along with you ? Your coding buddy ?? ? IT Support??…
Amarnath T S R

Tech Entrepreneur | Senior IT Consultant @ ROSHN l ???? | Tech Investor | Building Digital Solutions | Helping…

1 Confirmation bias

Confirmation bias is the tendency to seek, interpret, and favor information that confirms your existing beliefs or preferences. For example, you may favor a certain technology or vendor because you have used it before or heard positive feedback from others, and ignore or dismiss evidence that contradicts your choice. This can lead to poor decisions that are based on incomplete or inaccurate data, or that miss out on better alternatives. To avoid confirmation bias, you should actively seek out and consider different perspectives and sources of information, challenge your own assumptions and opinions, and test your hypotheses with experiments or feedback.

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Shayan Akbari

Head & founding father Of AHRAR Universal Organization - Origin and founder Of Universalism - On a Mission to build the World's largest Organization. ? t.me/AOrgan | Saoshyan.Org ? The Future is Here ?
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Recognize and acknowledge biases. Identify and analyze specific biases at play. Gather objective criteria and metrics based on reliable data. Evaluate and weigh the criteria to ensure impartiality. Implement decision frameworks like cost-benefit analysis. Seek diverse perspectives and input from others. Document and review decisions for continuous improvement.

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Chibuike Nwafor

Software Engineer - Who builds web apps and software while coding along with you ? Your coding buddy ?? ? IT Support?? ? Tutor & Author??
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From my experience, two major biases affecting IT professionals are confirmation bias and availability bias. These biases often stem from tight deadlines, pressure, and overconfidence. Here's how I tackle them: ? Embrace the philosophy of doing things well: For availability bias caused by tight deadlines, take the time to gather sufficient information before confirming a decision. ? Connect with peers in similar roles at different organizations. ? Establish a relationship with a trusted colleague, friend, or peer who can provide an impartial perspective and assist in brainstorming decisions. ????

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Amarnath T S R

Tech Entrepreneur | Senior IT Consultant @ ROSHN l ???? | Tech Investor | Building Digital Solutions | Helping Businesses Scale Through Technology
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Confirmation bias ?? is our tendency to favor information that aligns with our existing beliefs or preferences, often leading to skewed decisions ??. It's like preferring a familiar technology or vendor ????? because of past use or positive hearsay, while overlooking contradictory evidence ?. This bias can result in decisions based on partial or incorrect data, potentially causing us to miss out on superior options ??. To combat this, it's crucial to seek diverse perspectives ??, challenge our assumptions ??, and validate our choices through experimentation and feedback ??. By doing so, we ensure our decisions are well-rounded and informed, steering clear of the narrow vision confirmation bias brings ??.

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Prashant SK Shriyan

??Global Director@QA Mentor|Helping C-Suite & Top Tech Teams Uncover Hidden QA Risks Before They Break Trust, Disrupt Delivery, or Drain Revenue???? |Experts in Testing, QA Strategy & Scalable Quality Engineering?????
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Acknowledge Bias: Recognize susceptibility to biases as a crucial first step. Data-Driven Decisions: Prioritize data over intuition for more objective decisions. Peer Review: Encourage peer review to identify and mitigate biases. Training and Awareness: Participate in training to increase awareness of biases. Take Your Time: Avoid rushed decisions; take time to evaluate thoroughly. Seek Contradictory Evidence: Actively look for information that challenges your beliefs. Challenge Assumptions: Continuously question your assumptions and hypotheses. Feedback Loop: Establish a feedback loop to learn from past decisions. Accountability: Hold yourself accountable for decisions, regardless of biases.

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2 Anchoring bias

Anchoring bias is the tendency to rely too much on the first piece of information you receive, and adjust your subsequent judgments based on that anchor. For example, you may estimate the cost, time, or complexity of a project based on an initial quote or proposal, and ignore or underestimate other factors that may affect the outcome. This can lead to unrealistic expectations, budget overruns, or missed deadlines. To avoid anchoring bias, you should gather more information from multiple sources, compare different options and scenarios, and revise your estimates as new data or changes occur.

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Prashant SK Shriyan

??Global Director@QA Mentor|Helping C-Suite & Top Tech Teams Uncover Hidden QA Risks Before They Break Trust, Disrupt Delivery, or Drain Revenue???? |Experts in Testing, QA Strategy & Scalable Quality Engineering?????
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Anchoring bias can cloud judgment by fixating on initial information, leading to unrealistic estimates and decisions. To counter this, seek diverse data sources, conduct independent analyses, and regularly update estimates. Embrace scenario planning and collaborative decision-making to challenge initial anchors. Stay flexible, validate data, and consider historical trends to make more informed and unbiased decisions in IT.

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3 Availability bias

Availability bias is the tendency to judge the likelihood or importance of something based on how easily you can recall or access examples of it. For example, you may overestimate the risk of a cyberattack or a system failure because you have recently heard or experienced such incidents, and neglect other threats or issues that are less salient but more frequent or severe. This can lead to misallocation of resources, excessive caution, or complacency. To avoid availability bias, you should use data and statistics to assess the actual probability and impact of different events, prioritize your actions based on evidence and criteria, and update your knowledge and awareness regularly.

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Prashant SK Shriyan

??Global Director@QA Mentor|Helping C-Suite & Top Tech Teams Uncover Hidden QA Risks Before They Break Trust, Disrupt Delivery, or Drain Revenue???? |Experts in Testing, QA Strategy & Scalable Quality Engineering?????
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Availability bias can distort perceptions of risk, leading to misplaced priorities and missed opportunities. Combat this bias by seeking diverse perspectives, utilizing data-driven analysis, and considering long-term implications. Challenge assumptions and preconceptions by actively seeking out less obvious but potentially more impactful threats or opportunities. Regularly update your knowledge base and stay informed about emerging trends to make well-rounded and balanced decisions in IT.

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4 Framing bias

Framing bias is the tendency to be influenced by the way information is presented, rather than by its content or logic. For example, you may be more likely to accept or reject a proposal based on how it is worded, whether it emphasizes the benefits or the costs, or whether it uses positive or negative language. This can lead to irrational decisions that are swayed by emotions, preferences, or expectations. To avoid framing bias, you should analyze the information objectively and critically, focus on the facts and the outcomes, and reframe the problem or the solution from different angles.

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Prashant SK Shriyan

??Global Director@QA Mentor|Helping C-Suite & Top Tech Teams Uncover Hidden QA Risks Before They Break Trust, Disrupt Delivery, or Drain Revenue???? |Experts in Testing, QA Strategy & Scalable Quality Engineering?????
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Framing bias can cloud judgment by focusing on presentation rather than substance, leading to suboptimal decisions. To counter this, analyze information objectively, focusing on facts and outcomes rather than presentation. Reframe problems from different angles to gain a more comprehensive understanding and avoid being swayed by emotional or subjective influences. Prioritize critical thinking and logic over emotional responses to ensure decisions are based on sound reasoning and analysis.

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5 Overconfidence bias

Overconfidence bias is the tendency to overestimate your own knowledge, skills, or abilities, and underestimate the uncertainty or complexity of a situation. For example, you may assume that you know everything about a technology or a system, that you can complete a task faster or better than others, or that you can predict the future with accuracy. This can lead to poor decisions that are based on false assumptions, insufficient information, or unrealistic goals. To avoid overconfidence bias, you should acknowledge your limitations and gaps, seek feedback and advice from others, and monitor and evaluate your performance and results.

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6 Hindsight bias

Hindsight bias is the tendency to believe that you knew or could have predicted the outcome of a situation after it has occurred, and to ignore or downplay the factors that influenced or affected it. For example, you may think that you could have prevented or solved a problem if you had done something differently, or that you were right all along about a decision or a prediction. This can lead to overconfidence, blame, or regret. To avoid hindsight bias, you should document and review your decision making process, learn from your mistakes and successes, and accept uncertainty and variability.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Col Deepak Joshi (Retd)

CISO, Data Privacy, GRC, AI / ML, MTech IIT Delhi, CISSP, FIP, CIPP/E, CIPM, CHFI, ISO 27001 LA, 27701 LA, 42001 LA, PhD Research Scholar Cybersecurity, Indian Army Veteran (Views expressed are personal)
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Having biases is a very severe problem and it has disastrous effects on the organisation both in terms of business goals and on individuals as well. When the C level executives develop biases it's difficult to handle the situation as not many people have the courage to tell them even if it is evident and hence the biases continue and results are discouraging. Hence to address this situation there should be more openness in the organisation with an environment of professional dissent being encouraged

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What do you do if your decision making process as an IT professional is influenced by biases?

1

2

3

4

5

6

7

1 Confirmation bias

2 Anchoring bias

3 Availability bias

4 Framing bias

5 Overconfidence bias

6 Hindsight bias

7 Here’s what else to consider

Information Technology

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What do you do if your decision making process as an IT professional is influenced by biases?

1

2

3

4

5

6

7

1 Confirmation bias

2 Anchoring bias

3 Availability bias

4 Framing bias

5 Overconfidence bias

6 Hindsight bias

7 Here’s what else to consider

Information Technology

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