Bias is seen in action through bad decisions, miscommunication, perceptual blindness, and alienation of groups with diverse thought. Here’s what the dictionary says about bias: “A preference or an inclination, especially one that inhibits impartial judgment.”
Bias is a business analyst’s and organization’s worst nightmare. It leads to a decrease in product quality and creates a bad environment in which to make decisions and leads the project team to see the entire world through rose colored glasses. Bias can cause a chain reaction of bad decisions and miscommunications causing all sorts of problems on your project. Bias also creates a world in which change and innovation becomes nearly impossible. To combat bias a business analyst needs to be aware of the different types of bias. There are many different types of bias, but here’s the short list of bias types:
Knee-jerk bias: Make fast and intuitive decisions when slow and deliberate decisions are necessary. As human beings we feel a strong need to make a decision quickly to feel like we are adding value and moving the project forward. Not all decisions can be made in a split second. As a business analyst be aware of the knee jerk or quick decision as it might not contain all the facts and a full perspective. Did we deliberate enough on this decision?
Occam’s razor bias: Assume the most obvious decision is the best decision. Everyone else is using ABC software so we should be too. I like to call this the ‘Lemming Syndrome”. Because the decision of solution is so obvious it’s easy for everyone to just follow along. Are we just looking at one solution and not looking at a broader perspective?
Silo effect: Use too narrow an approach in making a decision. “When you are a hammer then everything is a nail” is one of my favorite quotes. It’s not looking wide enough at alternatives and carefully evaluating them that causes this bias to happen. Is our expertise or experience driving solutions too narrowly?
Inertia bias: Think, feel, and act in ways that are familiar, comfortable, predictable, and controllable. This is risk avoidance and fear of change. If it’s working – don’t fix it mentality. Of course the definition of “working” is key here. Everything changes and even the universe itself is in a constant state of change. Is our fear of change not letting us look at other solutions?
Overconfidence effect: Excessive confidence in our beliefs, knowledge, and abilities. Everything will be unicorns and rainbows! Looking at potential failure points, understanding them and avoiding them are key to a disaster. This bias is overly optimistic, exaggerates outcomes as being wildly favorable, and underestimates complexity. Is our optimism causing us to not look at all solutions?
Wow all this sounds really bad. So all types of bias are a bad thing right? Almost. Some bias can be there for a reason. If your organization provides services to medical professionals on dealing with patients more effectively can be seen as bias however this is more of a focus on a particular industry or expertise. When challenging the bias, we need to determine if the bias leads us to bad decisions. It’s the outcome of the bias that makes it bad or good.
Combating bias is challenging. Here are a few techniques to use to avoid bias and combat existing bias:
Be aware bias exists: The first step to dealing with or combating bias is to understand it exists. This blog gives you a good start. How aware are you of bias in decision making?
Open collaboration: Be careful not to exclude stakeholders from the discussion. Create an environment in which all points of view are accepted and encouraged. Work to get a larger view of the problem or opportunity your project is trying to solve. Try to go global and get diverse perspectives. Did we include enough diverse perspectives in the decision making process?
Remove assumptions: Assumptions are a killer. It’s easy to let them pass in a meeting or conversation. Be aware of assumptions and ask questions – seek clarification of the assumption before it takes a life of its own. Are assumptions that highly impact our decision clarified completely?
Focus on facts: Opinions are based on experiences, assumptions and bias. When you need to make bias free decisions work from a perspective of facts. Make sure the problem can be repeated and root cause analysis is completed and understood. Verify your facts before presenting them as facts. Ask the probing questions that allows for an open and logical discussion. Is everything stated as a fact been vetted or verified?
Provide and compare options: Nothing makes you feel railroaded or pushed into a solution like only having a single choice. Adults like to see choices to feel they are not being forced or bullied into a solution. Present several options – 3 options are the optimal. You may present 3 options but in your back pocket have another 20. Look at all solutions with a critical and logical eye. Document all the possibilities and why they were excluded from the final 3. This demonstrates your factual non-biased approach. Do we have a broad range of solutions?
Blame Storming: Be careful with brain storming – Ensure one person isn’t dominating the creative process of potential solutions. This can happen by an individual talking over others but also occurs in subtler ways. An example of this would be a team simply following their leader to avoid conflict with their manager or other in the hierarchy of your organization. Find a way to get open feedback in an anonymous way. Is our decision based on a single problem that hasn’t been verified or validated with root cause?
Dispel the Boogey Man: Most organization have a boogey man or gremlin they always blame when an issue arises. Be careful to verify the root cause. Shine the light of day on the boogey man to dispel him. Is the decision being based on a popular belief that hasn’t been vetted?
How would you work to avoid or confront bias in your projects? Being aware of bias – even your own bias – can help you and your organization build higher quality products through more effective projects and decision making.
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