Sunday, July 21, 2019
Vidal Business Strategy Overconfidence
Vidal Business Strategy Overconfidence Introduction During the annual business plan meeting regarding the shower gel brand Vidal, it was decided for 2017 to decline the 1+1 promo quantities in an effort to achieve better profitability versus last year. From the arguments that were presented, i believe that the team has overestimated the probability for the latter scenario to happen, since the decision might has been impacted by overconfidence. The aim of this report is a) to present arguments that justify the latter, b) to detect the source of this bias and c) to recommend de-bias techniques that will be proved useful also for the future. The case Vidal, in a short period of time became the 3rd player into the segment, with a continuous growth. Last year it gained +3.5 points in terms of market share and a +30% increase in value sales. Managers pointed that the key drivers of success were: a) the great value for money product b) the highest rate of 1+1 promo intensity c) the investment on distribution and traditional advertising. The team concluded that the objective to penetrate the market was completed and there is an opportunity to achieve better profitability and ROI at the end of 2017. This could happen by a 20-25% reduction in 1+1 promo quantities. Following this strategy, managers estimated that they can retain at least last years value sales, which in combination with the lower cost of selling goods will improve the brands profitability. The greatest ally that will support the latter is products excellence and consumer loyalty. More specifically, they considered that the combination of products low price (2ndlowest) and quality is so unique, that by reducing the 1+1 promo, consumers will be directed towards the regular product. Moreover, after the distribution expansion the team estimated that the products superiority versus competition will attract new consumers. I feel that both scenarios are overconfident and their probabilities should be reassessed for the following reasons. Initially, the findings of a qualitative research indicated that Vidal is a value for money product, but still lacks in terms of packaging. Most consumers considered the packaging as old fashioned and correlated it with Private Label. Additionally, they indicated some practical issues during the usage which are capable to restrain both users experience and perceptional quality. From a quantitative perspective, it was noticed that 55% of Vidals revenues were generated from the 1+1 quantities whereas the regular product presented a sharp increase in 3 out of 5 variances, mainly because of distribution expansion and not from gaining consumers from other players. Private Labels are leaders into the segment while in 2016 presented a substantial growth. From the data report, I noticed that the second player had around -40% lower price during some periods that are not supported from their 1+1 promo wave. From the latter I suspect that they might invested in price reductions in order to constrain PLs growth since they are more expensive. As a consequence I would like to underline that: Private labels are growing significantly in a price sensitive segment. Maybe by reducing 1+1 quantities we might push our consumers towards them, since we are highly correlated and more expensive. Palmolive might has realized the threat of PL and might has adapted its strategy by offering price reductions. The initiative to reduce our investment under these circumstances might also outflow consumers towards them. I think that the team has overestimated the regular products competitive advantage compared with competition and underestimated the importance of 1+1 promo. I believe that the source of this bias is generated by the teams motivation to improve profits since its a key performance indicator for both the companys and managers growth. During this effort managers knew that is not feasible to increase investment in order to boost sales and consequently they thought about a cost reduction strategy. The initial feedback about the very good results might boosted their confidence, whereas the fact that the brand has experienced only successes might constrained them to consider alternative scenarios. In order to improve the decision making process I would like to recommend some techniques of reducing overconfidence. The first is related about the importance of counter-argumentation. This means that managers when taking a decision should consider reasons why this decision might goes wrong. If the latter is difficult then they could ask from outsiders to express their opinion. For example in our case before approving the decision all the team members is recommended to list a number of reasons why the 1+1 reduction could not lead to increased profitability. In case that no one could think about any reason then, the Sales force should provide some input, since they have excellent sense of the market and its dynamics. Secondly, I would indicate the importance of feedback. The company is operating since 1970 while is consisted form experienced and new members. It is a great opportunity to exploit the companys knowledge by creating a case-study library that will host all the companys past successes and failures. Once a year we could organize the Sarantis-Training-Academy, in which managers will be assigned with cases, and they will be asked to provide their input for each strategy by assigning probabilities about their favored hypothesis. Afterwards, they will be informed about the real outcome and managers will be aware if they are overconfident or not. Finally from now on, I recommend that the Brand manager should be accountable for every decision. After every business plan meeting he will be responsible to present the proposals on the board of directors. The fact that he will have to present the ideas to seniors and experienced members might help him to enhance both self and group-criticism and reducing overconfidence. Conclusion The marketing team might has overestimated the probability of their scenario regarding the brands strategy of 2017, whereas this time has neglected also the normative approach. The excellent launch in combination with the fact that Vidal has experienced only successes might boosted the level of confidence. In order to improve the decision process this report has proposed 3 debias techniques (feedback, consider-the opposite and accountability) that according to the behavioral research seem to eliminate overconfidence. Part B Introduction Overconfidence might be proved a deleterious element for the decision making process since it does not only evokes people to overestimate their probabilities about the favored scenario but it also can cause catastrophic consequences. For example, in a study that examined the effect of overconfidence on newsvendors forecasts, showed that the higher the overconfidence the faster the profit loss (Crosson and Ren, 2009), while nowadays overconfidence seems to be a key driver for many start-up failures. This report is based on previous studies, and aims to underline the causes that triggered overconfidence to the Vidals marketing team while in parallel is focusing to provide a series of debiasing techniques in an effort to eliminate its effect. Overconfidence and Success In Vidals case I feel that the successful launch among with the wide recognition of the teams efforts, might have boosted their level of confidence. This relationship between success and overconfidence has lot of similarities with the case of Ducati. More specifically, in 2003 Ducati entered the motorcycle racing circuit MotoGP without having high expectations. During this effort, the team was focusing on data analysis and was gathering continuous feedback from the drivers for its improvement. At the end of the first year, Ducati surpassed every expectation and gathered the 2nd place, whereas for next year the team targeted the 1st place. This time the differentiated point was that the team stopped looking deeply into the data and receiving feedback. They considered that now their experience was enough in order to create an even better motorbike. Once a team member indicated you look into the data to understand whats going wrong and not why you are performing well. The next year Ducati did not covered expectations and performed even worse than the previous year. (Gino and Pisano,2011). Similarly, like on Ducatis case, it is remarkable how the Vidals marketing team after its successful launch didnt look deeply into the data, since so far it was a key principle prior taking any action. Additionally, the team seemed overconfident not only about their predictions but also about the products characteristics and performance. There are findings which show that success can inspire overconfidence. For example in a recent study, Hilary and Menzly (2016) found that analysts becoming overconfident when they achieve accurate forecasts as they tend to rely more on private information and to neglect markets reaction. As a consequence they perform less accurate predictions in the future. Additionally, when a trader achieves successful performance he becomes overconfident as he tends to revise his perceptional skills higher than the expected. The latter leads him not to use important information even though he might has a good database (Gervais and Odean, 2001). Walter and Ferrier (2004) stated also that success could generate overconfidence while it makes managers intolerant on new prospects. Since, success inspires overconfidence, it is important for managers to examine and understand the causes of success (Gino and Pisano,2011). Definition and Sources of Overconfidence Plous (1993,p.217) stated that no judgement decision is more prevalent and more catastrophic than overconfidence. In order to support this rationale in his book are some examples of the negative consequences of overconfidence. One of them is the destruction of Pearl Harbor, since Americans considered impossible the scenario for someone to conduct a proper attack in that location. Similarly, NASA, before the explosion of the space shuttle Challenger in 1986, had estimated that the risk of failure was 1/10,000. Overconfidence might has different forms. The first is related when someone overestimating the probability of the favored outcome to occur (Griffin and Varey, 1996), while the others are related when people consider themselves to be better than others, or when someone overestimates his skills or performance (overestimation) (MooreHealy,2007). I believe that in Vidals case both types are valid. This happens because the team might overestimated the probability to retain the amount of 2016 value sales by neglecting critical information, while they have excellent perception about the products potential. Russo and Shoemaker (1992) stated that a major cause of overconfidence is a persons difficulty to imagine all different outcomes that an event could have (availability bias).Due to this deficiency people become overconfident regarding their predictions as they have fewer paths to consider. In Vidals case the team could not envision different consequences of the cost reduction strategy, whereas the fact that the brand had only successes, might restricted the teams effort to recall or envision different scenarios. Another cause of overconfidence according to Russo and Shoemaker is anchoring. They stated that managers are anchored to one value or idea without making any adjustments, As a result they might generate sales forecasts before setting and adjusting their confidence rates. A prior study of Tversky and Khaleman (1974) confirmed this relationship by also stating that people tend to underestimate the risk of failure. The fact that cost reduction was the first thing that crossed the teams mind, might be due to an association based error. People are not used to think hard and usually trust the judgment that comes first into their mind (Kalheman,2003). Here, the first thing that the managers noticed was that Vidal had by far the highest promo intensity, while they might recalled from their semantic memory that cost reduction is a common and direct way to improve profitability. Arkes (1991) stated that people can think reasons to support their judgments much faster than the contradictory ones. The latter in combination with the fact that supportive reasons are greatly cued can cause overconfidence. Debiasing Techniques and Limitations Lichtenstein and Fischhoff (1980), stated that people are usually overconfident, but in an experiment that they conducted they found that feedback could improve participants calibration. Calibration is the skill to assign probabilities that equals the correct estimations (Sharp et.al, 1988). Performance feedback is one out of four types of feedback (outcome, process, environmental, performance) that are related with judgmental predictions, and can be divided into two subtypes (scoring-rule and calibration feedback)(Benson Onkal, 1992). In 1987, Arkes conducted an experiment between 2 groups in order to detect the effect of feedback. The 2nd group was informed that will have easy questions to answer while the 1st group was told that the questions were difficult. However, in reality both questions were difficult. After the first 5 questions the second group had higher confidence but same accuracy ratio with the first group. During the next sessions and after the second group received the discouraging feedback the members expressed less confidence and better accuracy. Similarly, in a recent study in which participated 57 students it was founded that performance feedback reduced overconfidence and lead to more accurate predictions (Al-Harthy 2016). Moreover, Richards (2015), examined as well the effect of feedback. This time the sample was consisted from 171 MBA students with 5 years of working experience. The participants were asked to assess themselves in 5 areas and afterwards to participate in a 3-hour assessment regarding their skills (problem solving, decision making, leadership, teamwork and planning).After the assessment, they participated in a pedagogy course in order to understand the essentials of behavior in relevance with the above skills. In parallel, they were being involved with many tasks such as: feedback and discussions with students. At the end of the semester the subjects repeated the same assessment. It was found that participants initially were overconfident in their self-assessment but after the feedback and the training cou rse their overconfidence level was reduced. Russo and Shoemaker(1992) pointed out the importance of feedback in companies since its a fast and cheap way to reduce overconfidence. He proposed that, companies should provide the employees with actual past cases where the result is known and to ask them to provide their guesses combined by their confidence level. With this method that was applied also successfully in Shell in order to train its junior gemologists, the employees learn to assess their level of confidence in relevance with their job and to identify if they are overconfident or not. However, all the above do not mean that feedback is always effective. Meikle et.al (2016) stated that this method is not suitable for people who have vested interest in seeing the world in a biased way. More specifically, a study in which participated football fans showed that feedback was not able to improve their accuracy on predictions since most of them still had preferences towards their favorite team (Massey et.al,2011).Additionally, the scoring-rule feedback (subtype of performance feedback) in which the forecaster gets rewards or penalties according to the outcome of his prediction doesnt show to reduce overconfidence (Fisher,1982). Finally, its important to indicate that this method is less efficient on overconfident CEOs, as they tend to show greater resistance on feedback which restricts them from improving calibration (Chen,et.al,2014). Feedback is useful for improving the decision making process since one of its characteristics is to warn that something, goes wrong or it might go wrong Thaler and Sunstein (2008). Kahneman (2003) stated that an outsiders view can provide more accurate predictions while it is less possible to provide unrealistic estimations. This happens because the outsiders view can provide safety against favored predictions that have less probabilities than the expected to happen (Kahneman Lovallo,1993). The outsiders can exploit knowledge from previous experiences by taking also into account the problems unique characteristics and data. As a result, since many people are overconfident, it is recommended for important decisions to ask either from an outsider to share his opinion or the decision maker to try to think like an outsider (Bazerman, 2013). This means that the decision maker should either think of reasons why his scenario might go wrong or to ask from others to provide counterarguments (Russo Shoemaker,1992). The latter might be proved helpful since considering the opposite scenario is capable to reduce the high levels of confidence (Soll et.al 2013).In a study that was conducted by Koriat et.al (1980), it was found that when subjects wrote down contradicted reasons and alternatives against their selected answer, they showed less confidence and better calibration. One way that might lead to this direction and to reduce overconfidence is accountability. The fact that the person is accountable for the decision, will lead him to enhance his pre-emptive self-criticism as he will have to present the decision and its rationale to others (Larrick, 2004).This mechanism will lead him to improve the decision quality and to assess more objectively the alternatives (Tetlock et.al, 1989). In a study that was conducted by Tetlock Kim(1987) the subjects participated in a person-perception process. The participants after receiving responses from each test taker they were asked to submit a short personality brief and to retake the test. This time they had to predict the responses of each test taker by assigning probabilities and level of confidence. It was found that subjects that they were told (before the test), that the researcher would like to have a detailed interview about their answers, to show more appropriate levels of confidence and better accuracy. Similarly in a recent study that participated 71 student students in a computer-based laboratory showed that accountability reduced significantly overconfidence (Jermias,2006). However, Brown (1999) stated that accountability might lead managers to take decisions that are most favorable to their peers, while the great amount of information could cause the lost-pilot effect if it will not being used properly (Larrick,2004). Accountability, does not seem to improve calibration in organizations in which the answer to the question what is a good decision is maddeningly subjective (e.g advertising agencies), whereas it is more effective in preventing rather reversing judgmental biases (Tetlock Kim 1987). The positive effect of overconfidence recommendations Contrary to all the above, overconfidence does not have solely negative effects. As Goethe wroteFor a man to achieve all that is demanded of him he must regard himself as greater than he is. Bernardo and Welch (2001) stated that overconfident entrepreneurs are more likely to explore their environment and to provide additional information to their social group while overconfident managers are more willing a)to take risk decisions b)to devote more effort and c) to motivate the team to accomplish its goal (Gervais et.al,2002). Finally, Taylor and Brown (1998) indicated that overconfident and optimistic people are more positive, happier and they have excellent ability for caring about others. Since overconfidence has also a positive side, Russo (1992) recommends that managers should distinguish between deciding and doing. This means that the decision process should be combined by realism and rationality, whereas the implementation of the decision should take advantage of the motivational benefits of overconfidence. As a result, its important for the decision makers to realize what they do know and what they dont, while the ones who are implementing the decision should indulge overconfidence when they think that will be proved beneficial for the performance. Conclusion Overconfidence when impacts the decision process could have negative consequences. However, it has some advantages that can be exploited from the ones who are implementing the decision. Since the decision process is critical, it is suggested to eliminate this effect by using three debiasing techniques. Performance feedback seems to improve calibration, whereas when people are thinking about why their decision might go wrong, they tend to reduce overconfidence. Finally, in special cases accountability seems to enhance self-criticism and to lead to a more rational way of thinking. References à à Al-Harthy, I. (2016). Prediction Accuracy: The Role of Feedback in 6th Graders Recall Predictions. International Education Studies, 9(3), 212. doi:10.5539/ies.v9n3p212 Arkes, H. (1991). Costs and benefits of judgment errors: Implications for debiasing. Psychological Bulletin, 110(3), 486-498. doi:10.1037//0033-2909.110.3.486 Arkes, H., Christensen, C., Lai, C., Blumer, C. (1987). Two methods of reducing overconfidence. Organizational Behavior And Human Decision Processes, 39(1), 133-144. doi:10.1016/0749-5978(87)90049-5 Bazerman, M. (2013). Becoming a first-class noticer. How to spot and prevent ethical failures in your organization. Harvard Business Review. Bernardo, A. Welch, I. (2001). On the Evolution of Overconfidence and Entrepreneurs. Journal Of Economics Management Strategy, 10(3), 301-330. doi:10.1162/105864001316907964 Benson, P. ÃÆ'-nkal, D. (1992). The effects of feedback and training on the performance of probability forecasters. International Journal Of Forecasting, 8(4), 559-573. doi:10.1016/0169-2070(92)90066-i Brown, C. (1999). Do the Right Thing: Diverging Effects of Accountability in a Managerial Context. Marketing Science, 18(3), 230-246. doi:10.1287/mksc.18.3.230 Chen, G., Crossland, C., Luo, S. (2014). Making the same mistake all over again: CEO overconfidence and corporate resistance to corrective feedback. Strategic Management Journal, 36(10), 1513-1535. doi:10.1002/smj.2291 Chen, G., Crossland, C., Luo, S. (2014). Making the same mistake all over again: CEO overconfidence and corporate resistance to corrective feedback. Strategic Management Journal, 36(10), 1513-1535. doi:10.1002/smj.2291 Ferrier, W. Lyon, D. (2004). Competitive repertoire simplicity and firm performance: The moderating role of top management team heterogeneity. Managerial And Decision Economics, 25(67), 317-327. doi:10.1002/mde.1193 Fischer, G. (1982). Scoring-rule feedback and the overconfidence syndrome in subjective probability forecasting. Organizational Behavior And Human Performance, 29(3), 352-369. doi:10.1016/0030-5073(82)90250-1 Gervais, S. Odean, T. Learning To Be Overconfident. SSRN Electronic Journal. doi:10.2139/ssrn.36313 Gervais, S., Heaton, J., Odean, T. Overconfidence, Investment Policy, and Executive Stock Options. SSRN Electronic Journal. doi:10.2139/ssrn.361200 Gino, F. Pisano, G. (2011). Why Leaders Dont Learn From Success. Harvard Business Review, 1-8. Griffin, D. Varey, C. (1996). Towards a Consensus on Overconfidence. Organizational Behavior And Human Decision Processes, 65(3), 227-231. doi:10.1006/obhd.1996.0023 Healy, P. Moore, D. The Trouble With Overconfidence. SSRN Electronic Journal. doi:10.2139/ssrn.1001821 Hilary, G. Menzly, L. Does Past Success Lead Analysts to Become Overconfident?. SSRN Electronic Journal. doi:10.2139/ssrn.1753771 Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for Behavioral Economics. American Economic Review, 93(5), 1449-1475. doi:10.1257/000282803322655392 Kahneman, D. Lovallo, D. (1993). Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking. Management Science, 39(1), 17-31. doi:10.1287/mnsc.39.1.17 Koriat, A., Lichtenstein, S., Fischhoff, B. (1980). Reasons for confidence. Journal Of Experimental Psychology: Human Learning Memory, 6(2), 107-118. doi:10.1037/0278-7393.6.2.107 Larrick, R. (2004). Blackwell handbook of judgment and decision making. Choice Reviews Online, 42(08), 316-337. doi:10.5860/choice.42-4710 Lichtenstein, S. Fischhoff, B. (1980). Training for calibration. Organizational Behavior And Human Performance, 26(2), 149-171. doi:10.1016/0030-5073(80)90052-5 Massey, C., Simmons, J., Armor, D. Hope Over Experience: Desirability and the Persistence of Optimism. SSRN Electronic Journal. doi:10.2139/ssrn.1552394 Meikle, N., Tenney, E., Moore, D. (2016). Overconfidence at work: Does overconfidence survive the checks and balances of organizational life?. Research In Organizational Behavior, 36, 121-134. doi:10.1016/j.riob.2016.11.005 Plous, S. (1993). The psychology of judgment and decision making (1st ed.). Philadelphia: Temple University Press. Ren, Y., C. Croson, D., T.A. Croson, R. (2016). The overconfident newsvendor. Journal Of The Operational Research Society. doi:10.1057/s41274-016-0103-5 Richards, D. (1997). Developing Cross-Cultural Management Skills: Experiential Learning in an International MBA Programme. Management Learning, 28(4), 387-407. doi:10.1177/1350507697284001 Russo, E. Shoemaker, P. (1992). Managing Overconfidence. Sloan Management Review, 1-7. Sharp, G., Cutler, B., Penrod, S. (1988). Performance feedback improves the resolution of confidence judgments. Organizational Behavior And Human Decision Processes, 42(3), 271-283. doi:10.1016/0749-5978(88)90001- Soll, J., Milkman, K., Payne, J. (2015). A USERS GUIDE TO DEBIASING, 1-29. Sunstein, C. Thaler, R. (2008). Nudge: improving decisions about health, wealth, and happiness (1st ed.). Clitheroe: Joosr Taylor, S. Brown, J. (1988). Illusion and well-being: A social psychological perspective on mental health. Psychological Bulletin, 103(2), 193-210. doi:10.1037//0033-2909.103.2.193 Tetlock, P. Kim, J. (1987). Accountability and judgment processes in a personality prediction task. Journal Of Personality And Social Psychology, 52(4), 700-709. doi:10.1037//0022-3514.52.4.700 Tetlock, P. Kim, J. (1987). Accountability and judgment processes in a personality prediction task. Journal Of Personality And Social Psychology, 52(4), 700-709. doi:10.1037//0022-3514.52.4.700 Tversky, A. Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131. doi:10.1126/science.185.4157.1124
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