BIASES IN DECISION MAKING OF A DATA ANALYST

The role of a Data Analyst is to collect, organize and transform information/data to make it useful for the organization and thus help in business decision making.  A Data Analyst gathers information from various sources and interprets the patterns using data analysis tools and techniques. Once the significant analysis has been carried out on data, a data analyst will report back the findings in order to help businesses make key decisions. 

It is of utmost importance for the manager to take key decisions based on data however, humans are influenced by cognitive biases when making decisions. it is very essential to control them in order to provide facilitate non-biased decisions.

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Cognitive Bias: -

Making Decisions forms the critical part of our every day’s life. Deviation from norm or rationality in a systematic pattern is known as Cognitive Bias. It is a system error which occurs when people are processing and interpreting information in the world around them and affects judgements and decisions made by them. It is evident from research, that we use unconscious routines to cope with the complexity inherent in most decisions. These routines are known as heuristics. Heuristics are cognitive tools which aid in making expeditious decisions and judgements. For instance, how much time consuming would it be if you had to think about every decision you make? This is where heuristics come in. We use our heuristics to decide based on past decisions. When you visit a cafe where there are myriads of options for a coffee, you may opt for what you same coffee drank in the past. Another example here would be, Steve Jobs wore the same outfit every day.

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Heuristics, however, is not full proof when it comes to decision making. There are certain series of flaws in the way we think while making decisions. These flaws, identified as biases areas listed below: -

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1.     The Anchoring Bias: - 

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It forms the focal point for any decision when one is presented with a little piece of information. Let’s try to understand it with the help of an example: -

When Steve Jobs introduced iPad for the first time, he said according to pundits, apple will price it at 999$ price tag. Steve said Apple wants to put it in the hands of a lot of people, therefore iPad price starts not 999$ but at 499$. At the same time, on the presentation screen, 499$ destroyed 999$ tag and placed itself. He used this anchoring mechanism to compare the price to itself and influenced people to think they are getting a steal deal at this price point. 

Due to the focal point formed initially, we ignore the other parameters and focus on the information available at hand.

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How analysts can help to overcome Anchoring Bias?

Since an analyst role is to make sense of the data and provide useful insights, they play a key role in decision making as well. 

According to Eva M. Krockrow, there following are the 3 simple steps to handle Anchoring Bias: -  

1.     Acknowledge the bias: - It is the first move to be mindful of your prejudice. Accept your mind's vulnerabilities and foresee prejudiced decision. When you approach with care each sales negotiation, always reflecting on your decision, you are less likely to fall into your own mind's pit. The same applies when a team has to decide based on the data, acknowledge the bias and approach with care. 

2.     Delay your decision: - The second step is to slow down the decision process and obtain more data. Sometimes the data gathered may not be upto the standard which can help in decision making. It may be wise to take your time when negotiating over a vehicle. Why don't you do research online before you visit the store? To be sure, don't go for the second model you see, but consider carefully all the different deals that the store has to sell. 

3.     Drop your own anchor: - Once you are aware of the powerful effect strategic anchors can have on our decision, this information can be used for your personal benefit. For example, studying the average selling price for the second-hand car model you are interested in can be useful and using this as an indicator to direct your option of sealing the deal or not. In addition, it is often advanced during open negotiations. 

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Following the above listed 3 simple steps help to make unbiased decisions and can, therefore, be leveraged to benefit the organization.

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2.     The Status Quo Bias: -

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Status Quo Bias occurs when one prefers to stay with familiar choice over the less familiar one. We all have the general tendency to with the current affairs and not to try to challenge the status quo. It is because we as humans have a deep desire to protect ourselves from ego damage. Challenging the status quo means opening ourselves to regret and criticism and everybody fears that. 

According to Dan Shewan, Individuals who experience status-quo bias tend to be:- hesitant in trying new services or products due to the fear of loss which results from change, are resistant to conventional sales aptitude, are extremely loyal to the brand even if they offer inferior service. 

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How analysts can help to overcome Status Quo Bias?

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There are times when managers would like to go ahead with the status quo in decision making. This is due to past behaviour becomes the present action, influenced by success in past. However, nowadays there are some algorithms which can predict the price of a stock with high accuracy using previous data. Such algorithms can be leveraged to influence decision making.

Also, when a decision is to be made that challenges the status-quo, one has to play around with the human mind. Explaining what will be losses incurred by the organization when staying with status-quo, will have an impact on the mind of the person making the decision. This way one can persuade the decision-maker to think the other way around in decision making.

Present the alternatives in contrast to the status quo choice, and try to back yourself with the majority when presenting the idea/decision to the decision-maker.

Lastly, an analyst who is able use Reality Distortion Field can have a great impact on the mind of the manager (i.e. decision-maker) to overcome status-quo bias.

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3.     The Over-Confidence Bias: -

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Confident personality is liked by everyone, but when it comes to decision making, a person who takes decisions only with his gut feelings without considering the facts and figures is the one who is influenced by over-confidence bias. Such people over believe in their capabilities and skills and make poor decisions due to the bias. 

Let’s try to understand this bias an example, a person who believes that he knows everything that was taught in the lecture and decides that he can appear for the exams without studying for it, may end up performing poorly on the test. [3]

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How analysts can help to overcome Over-Confidence Bias?

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Managers who believe that their decisions have always proved out to be beneficial for the organization may end up in taking poor decisions however if the analyst can provide the reports with details and evidences that goes against the belief of the manager (i.e decision-maker), can have an impact on the mindset of the manger and help him to overcome his over-confidence bias. 

Also, if the insights provide an estimate of implications if the decision is taken otherwise, can again prove to be an impactful element to help with decision making.

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4.     The Confirmation Bias: - 

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Seeking out information to support one’s own views and ignoring all other information which doesn’t fall in the areas of one’s views, is called confirmation bias. To be self-satisfied, a person seeks out only the information which supports his/her initial conclusions. This leads to non-rational decisions and may be harmful in the future.

Let’s understand this with an example, suppose you want to buy a new smartphone and you are an Apple fan who likes apple devices only. You would seek out information and talk to people who also own an iPhone, about the features that the new iPhone has to offer in order to support your decision. Whereas it may be possible that the android phone with a similar price point may offer more features but since you didn’t consider it, you are confirmed the new iPhone would suit you needs.

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How analysts can help to overcome Confirmation Bias?

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While it may be difficult to overcome confirmation bias since the decision-maker already has pieces of evidence to support his claim, he must be aware of confirmation of bias and its concept.

The following are some ways which can help in overcoming confirmation bias: - [4]

1.     Seek information which can challenge your confirmation and evaluate your findings

2.     Ask a person from another team to review the data and provide feedback on the same.

3.     Conduct meetings wherein the participants are required to comment against the claim

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5.  The Sunk Coast Bias: - 

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Have you ever been in such a situation where you ordered more food at a restaurant than you can eat and ended up finishing all that was served because back in mind you knew that would have to pay for it no matter how much you eat? If yes, then you have fallen to Sunk-Cost Bias. It is the tendency of humans to redeem all they have paid for. Sunk – Cost Bias preys our minds to make inappropriate decisions. 

A lot of things around us have a sunk-cost which cannot be recovered. For example, replacing your old and non-working iron with a new one also has some sunk-cost to it. You may be able to recover some cost by selling it in scrap however you wouldn’t recover the whole cost. However, this doesn’t mean you should avoid this expense as iron is required in daily life.

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How analysts can help to overcome Sunk-Cost Bias?

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While sunk-costs makes you think about your finances and encourages you to think twice about your decisions, falling prey to this bias has some harmful effects in the long run. Hence, it is always advised to make unbiased decisions.

A detailed analysis and comparison report of the costs incurred vs profits is helpful while making decisions that have some financial costs attached to it. Also, a report which shows losses incurred if the decision is taken otherwise.

As Jennie Garth has said,” I have to pick myself up every day and say, 'The show must go on,' meaning life as I know it must go on, whatever the obstacle is, I know I can handle it, and I can get through it.” [6]. On similar grounds, a business runs when “the show keeps on going”. Making rational financial decisions while having a holistic view of the parameters involved proves to be beneficial in making decisions.

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Conclusion: -

We all make decisions in our daily life and those decisions really matter the way our life revolves. With the outburst and advancements in technology, it is nowadays possible to make decisions based on the data however again in those decisions, there are some biases involved. Therefore, awareness is the key. Being informative and aware of the latest innovations helps in making rational decisions. In Businesses, decisions often affect growth. Hence, no matter whatever the complexity of the situation is, an unbiased and rational decision would prove beneficial to the organization. Leveraging the analytical tools available at hand, data analysts carry out the analyses for a given task, and such analyses provide a holistic view of the situations and help in making unbiased decisions. This is evident from the rapid growth in the big-data sector since many organizations have started leveraging the analyses to make decisions in favour of business growth.

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References:-

1.     Outsmart the Anchoring Bias in Three Simple Steps:-https://www.psychologytoday.com/ie/blog/stretching-theory/201902/outsmart-the-anchoring-bias-in-three-simple-steps

2.     5 Cognitive Biases & How to Overcome Them On Your Landing Pages:- https://www.wordstream.com/blog/ws/2014/05/22/landing-pages-cognitive-biases

3.     Examples of Over-Confidence:- https://examples.yourdictionary.com/examples-of-overconfidence.html

4.     Avoid biased data analysis:- https://www.grow.com/blog/avoid-biased-data-analysis

5.     Dijkstra KA, Hong Yy (2019) The feeling of throwing good money after bad: The role of affective reaction in the sunk-cost fallacy. PLOS ONE 14(1): e0209900. https://doi.org/10.1371/journal.pone.0209900

6.     https://www.brainyquote.com/quotes/jennie_garth_483136

7.     Hammond, John & Keeney, Ralph & Raiffa, Howard. (1998). The Hidden Traps in Decision Making. Clinical laboratory management review : official publication of the Clinical Laboratory Management Association / CLMA. 13. 39-47.