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Recency Bias is an intellectual bias that influences judgment based on recent events. It is the tendency to weigh recent information more heavily than older data when making decisions. The decision making or estimation by people will be favored based on current happenings or recent events ignoring historical events leading to overestimation or underestimation of importance and potential consequences of their choices. In project management, this bias can significantly impact decision-making by detaching people from historical project data. For instance, if a project manager solely considers recent changes, they may overlook earlier developments that could impact the project’s success. Here’s how you can recognize Recency bias in your own decision-making: Overemphasis on Recent Events: If you find yourself giving disproportionate importance to recent experiences or events, you might be affected by recency bias. Ignoring Historical Trends: When you disregard long-term patterns or historical data in favor of recent occurrences, it’s a sign of this bias. Short-Term Focus: If you prioritize short-term gains or losses over the overall context, recency bias may be at play. Availability of Recent Information: Relying solely on readily available recent information without considering other relevant data is indicative of this bias. Being aware of recency bias is the first step toward making more balanced decisions. To avoid or mitigate the influence of recency bias and for achieving more balanced decisions in your projects, consider these methods/strategies Holistic View: Look beyond recent events and consider the entire project history. Analyze trends, patterns, and long-term impacts. Data-Driven Decisions: Rely on data rather than relying solely on recent experiences or emotions. Long-term Planning: Set long-term goals and review past decisions periodically. Calculate Different Facts: Actively consider various facts, including historical data, for a fuller picture. Take Time to Consider: Slow down your decision-making process. Analyse Validity of Information: Check the relevance and accuracy of recent information Structured Decision-Making: Use frameworks or decision matrices to evaluate options objectively. Consult Others: Seek input from team members and stakeholders to gain diverse perspectives. Reflect and Validate: Regularly review decisions and assess their long-term effects.

What is Recency Bias? Recency Bias is a cognitive bias that is about taking decisions / arriving at conclusion based on the most recent events / data points rather than considering the historical events / data. This often leads to a misrepresentation of the true nature or overall picture of the situation For Example: In employee performance evaluations, a manager focusing on an employee's recent accomplishments or mistakes rather than considering his / her overall performance throughout the entire evaluation period. This can lead to skewed assessments that do not accurately reflect long-term performance How does it impact decision making in projects? Data Analysis: While evaluating Process performance data, a recency bias might cause a team to focus too much on recent data trends, by overlooking long-term patterns that are more indicative of a process's true performance Root Cause Analysis: While performing RCA, the Green belt / Black belt might prioritize recent incidents or issues over older ones, even if the older issues are more significant or prevalent Performance Evaluation: In performance evaluation of a change Project, there might be a tendency to judge success or failure based on the most recent results, without considering the full range of data from before and after the change Decision Making: In resource allocation the manager might be influenced more by recent successes or failures rather than a comprehensive analysis of all relevant historical data How to Mitigate Recency Bias: Use statistical methods and tools which will enable you consider the full range of data Ø Ex 1: Pareto Charts: Pareto charts highlight the most significant factors in a dataset based on the principle that roughly 80% of problems are caused by 20% of the causes. This tool helps teams focus on the most impactful issues rather than recent occurrences Ø Ex 2: Control Charts – Control charts help visualize data over time and identify true trends and patterns. They also provide a comprehensive view of the process stability over a long period Ø Ex 3: Run charts display data points in a time sequence, allowing teams to detect trends, shifts, or cycles. They help identify whether recent changes are part of a longer-term trend or just short-term fluctuations In addition to this, ensure that data analysis includes a thorough review of historical data, not just the most recent information. In DMAIC, ensure that you consider data from all relevant time periods. Also, train the Project resources and team members on cognitive biases, including recency bias, to improve awareness and encourage more objective decision-making

Recency Bias – by the name itself, we can able to understand that, we forecast/predict the future scenarios based on the recent performance/situations etc. It is the human tendency to focus more on the recent events rather than long time. Some of the examples mentioned below Performance appraisal is considered the most impacted by the recency bias. In general, before appraisal, if we have done some good job which is considered as good performance. Even if, that there is a poor performance during the entire year. I am thinking to go on a road trip. some of my friend mentioned that the highway/road no.123 is very dangerous due to accident happened 6months back. But this road use to consider as one of safest road due to zero accidents in last 5 years. So due to recency Bias, I tend to choose that road is unsafe. I am going to buy brand A phone. But my friends told me that the phone is very good, due to its recent performance & battery backup is good. Based on this feedback I brought the phone, but it is not working well. As the past performance of this type of phone is very bad. I could have saved money if I brought Brand B phone, which has good performance in the past. In a manufacturing line, one of the parts is failing from last 6 months. But in the past, there is no records of failure. Due to recency bias, I tend to decide that this equipment is a chronic problem for this manufacturing line. In service sector, I am going on vacation to other countries, I would like to stay in hotel XYZ, but the experience in last month visit was very bad, because during the visit, there was some construction work going on. But in the past the experience is always good. If I stay in Hotel ABC, my expenses will be 2times. With out recency bias, If I would have stayed in the hotel XYZ, I could have saved money. In the chemical making line, one of the equipment failed recently, then the root cause was base vibration bolts are loose. If the equipment failed, operators are tending to tightened the bolts, instead of investigating the problem in details If we don’t consider the recent bias in project decision making, it may give short term benefits rather than a long-term benefits. For example, in the improve phase we identified that the one of the equipment speeds should increase to get the better quality. But recently the equipment got failed to high vibration due to some other reason. But while implementation, team will not approve this decision of increasing the speed of equipment. In this situation, if we could have the data like equipment history and root cause of last failure, we might have increased the speed without hesitation. Which will also improve the quality. The reason for recency bias Memory and Attention – We tend to recollect more recent information & prioritize the recent over the old Availability Heuristic – People often rely on the recent available information, rather than the old Impacts of emotion – Recent events evokes stronger emotions, which impact decision making Short-term memory bias – Events or information that occurred recently are most likely to be at priority for the individuals, which influence the decision making or the judgement Cognitive load – The busy work environments and lot of information (cognitive load) challenging to consider the person’s performance over a period of time. This will impact the decision making Recency’s perceived relevance – We always assume that the recent events are the more indicative of the performance (most recent information is most relevant) which also impact the decision making. Some of the ways to avoid the recency bias: Data – Get enough data before making decision. In the above example of equipment failure, we need to see the equipment history, PM schedules, vibration analysis report, OEM recommendation of failure, process conditions, then only we can take decision of overhauling of equipment, change with new equipment Look at the Big Picture: Instead of focusing on what’s happening now, try to consider what has happened in the past. If we’re thinking about building new manufacturing plant, we need to look at how the returns gave over years of similar business. Standardized procedures: These procedures are can reduce the subjectivity & feelings of recent bias. In the same example, we can say that before buying a new equipment. Engineers need to bring all the relevant information, and do the proper analysis of the data and estimate the life of equipment. Even some time, we can refer to benchmark life of the equipment within the business. Training: Raising the awareness within the team to avoid the recent factor. Which helps focus on the historical events/data/situations rather than the recent ones. Get Different Views: By talking to people who might see things differently or consider other time frames. The SMEs/consultants comes up with more experience of various industries & expertise. They can validate properly about the recency bias of events/situation and also may guide for right decision. Slow Down: Try to avoid making quick decisions based on the recent events. By taking more time can help us to think things through more thoroughly Use a performance review system : Try to use the online system to track the performance. So that the data can be summarized for decision making