Main Discussions
Decisions making is a pivotal tool that is essential in a business organisation as it is the key determinant of the future performance, growth, and sustainability of the organisation in the market (Cameron and Green, 2015). Managers and any people in the position of leadership are constantly tasked to offer solutions and provide guidance to the rest of the members through decision-making processes. This is usually challenging when it entails a critical and complex situation that require fast and accurate decisions within a short period as acknowledged by (Endsley, 2017, pp.9-42).
However, organisations can develop different frame works that provide guidelines in times of emergencies that calls for instant decisions. This is usually achieved through formations of teams that are required to analyze the situation and present conclusive decisions or solutions to the board of members or the relevant authorities. (Tideman, 2017) ascertains that group decision making has greater advantages that surpasses individual decisions as they entail diversified opinions, promotes innovate ideas and planning, and are characterized by the abundance of required information in solving the problems at stake. Furthermore, he claims that group decision making are based on expert opinion and affirmed by the census, voting, and critical analyses that eliminates biases. Therefore, this assessment will be based on team decision making in solving the given problem in the assignment.
(Schoenfeld, 2014) Affirms that Problem definition is the first step in solving given problem. The business organisations undergo both internal and external challenges can lead to massive losses financially and in the market shares. For instance, the business organisation in the question has been faced with loss of two of its products in the market due to the implementation of the government policies that prohibits the manufacturing of the products. This means that the organisation has to minimize its staff or device other product to replace the prohibited product by the government as the operations costs and the wages will be higher than the outputs thus leading to immediate losses (Baker, 2016, pp.1593-1636). However, from the two options, the company is at liberty to come up with ways that will lead to the reduction of the wage and salary costs to evade the incurred the losses in the next financial year.
A situational analysis helps to define the internal and the external factors that affect the performance of a business in the market (Wheelen, Hunger, Hpffman, and Bamford, 2017). This aids the managers to identify the strengths, weaknesses, threats, and opportunities that can be implemented through group decision-making processes as supported by (Elmes and Barry, 2017, pp.39-42). However, the product situation is the major external factor that has been identified as an external threat due to the government policies that have led to the loss of two products supplied by the firm. Additionally, the product situation has forced the business set up a panel that will provide decisions on the reduction of the workers who will be classified as redundant in relation to the elimination of the products due the government policies. However, the firm consists of 300 employees whereby the management has no specified number of the people to be claimed redundant while the decision making panel is aware of the number of employees that can get the firm in operation after the demotion of some members. This will require a concrete explanation to the recommendations of the decisions made.
Problem Definition
(Davis, 2014, pp.43-68) reports that sense making is a concept that aims at deriving the meaning of what has happened or bound to happen in business operations. The concept is a very essential for the step to be taken by the executive managers as a foundation of arriving at specified decisions. (Morente-Molinera, Perez, Urena, and Herrera-Viedna, 2015, pp.49-60) affirms that sense making requires the decision makers to seek for explanations and answers in terms of how individuals see things rather than the structures or systems. This suggests that the executive issues such as the goals, plans, change, and the strategies are aspects that cannot be found in the outside world but rather in the people’s way of thinking.
Additionally, sense making helps the decision making panel to identify the cause of the problems in order to come up with measures that will not only address the current situation but also in future. For instance, in our case scenario, sense making enables us to bring to light the reasons for the government implementing the policies that led to the loss of the products. Moreover, this also will provide explanations to the members being laid off from their work as a way of practicing employment ethics (Bolman and Deal, 2017). This will be the basis of formulation of the potential solutions.
The potential solutions to the defined problem was conducted through selected decision-making models (Birkland, 2015). The panel outlined a number of models to be applied in analyzing the given data set of the employees’ profiles. This was arrived at through the regular meetings set by the panel members who were required to present their research over the problem and present their personal findings for further scrutiny and analyses. The members set in place policies that could govern on punctuality, effectiveness, and the mode of responding to the other members’ views and ideas. Moreover, a framework was established for evaluating the progress made by the team in arriving at the required solution at the end of every meeting.
The panel identified three basic models of decision making which included the rational or the classical model, the retrospective model, and the administrative or bounded rationality model to be used in an evaluation of the list of employees. The individual models were then discussed among the panel in order to select one to be used in the process.
The rational approach of decision-making
The rational approach is based on the economic theory of the businesses that had an assumption that any decision that was being made by the executive managers was for the economic interests (Cascetta, Carteni, Pagliara, and Montanino, 2015, pp.27-39). The model involves the following procedure in decision-making.
This model focusses on how the panel of decision makers will attempt to rationalize the highlighted opinions and choices in an attempt to justify the made decisions (Marsh et al., 2016, pp.125-137). Moreover, the used this model to observe that the business graduates chose their favorite jobs they anticipated for in the recruitment process while they went a step further to continue searching until they found their best alternative. The model therefore ensures that the decision made is based on logical reasoning and scientific rigor.
Situational Analysis
The administrative decision-making model is based on the achievement of the desired goal. The rationality dictates that the panel members tasked with decision-making should be conversant with the alternative course of events that can lead to meeting of goals (K. Roehrich, Grosvold, and Hoejmose, 2014, pp.695-719). The model demands that group decisions should be characterized with vast information and the ability to analyze various options that could ensure that the achievement of goals and targets as it is based on the concepts of sequential attention to alternative solutions, satisfaction, and heuristics.
After identifying the potential models that can be applied, the team was then required to select the best technique among the three. Through the meetings, the group highlighted the factors to be considered during the selection of a model for decision-making process while illustrating the pros and cons for each method in relation to the problem to be solved. However, the type of data given and the minimum time required to implement the techniques in order to produce results were highly considered in the selection process (Jalalimajidi and Jalalimajidi, 2016, pp.2015-2025). The panel noticed that the retrogressive and the administrative approaches plenty of time to be implemented. After consultations, the classical approach selected to evaluate the problem and analyze the given set of data to derive at a decision. However, the team made an agreement on the use of the other approaches in one way or another in case the classical method has limitations in some circumstances.
This section outlines the procedures used in the classical method to derive decisions from the data. With knowledge on the number of the employees that could be sustained by the company as well as result to profits in the next period, the team was obligated to determine the number of employees to be rendered redundant from the provided list of 60 members. Through teamwork and collaboration among the members, the team concluded that the recommended percentage by the executive managers was way above the number that should be laid of the work, in essence, out of 300, the firm required at least 275 employees in order to keep its operation up to speed and generate profits as well. This implied that only 25 employees were required to be removed from the list of 60 members forwarded to the decision making panel, which is less that 60% of the recommended percentage.
To analyze the data and provide the list of redundant members, the team divided tasks among the members where everyone was required to analyze a section of data using the classical approach (Wu, Dai, Chiclana, Fujito, and Herrera-Viedna, 2018, pp.232-242). From the classical approach steps, identification and gathering of information had already been done at this stage. Therefore, the panel proceeded to analyzing the employee data basing on the situation faced by the company. Thereafter, the options for the elimination were developed where different factors were laid down in order of preference that benefits that company. These factors included the rate of performance classified as outstanding, well performing, and acceptable, which was given the last consideration. The second factor to be considered was whether the employee met the set quarterly key performance Index at an individual level while the project the employee was working on was given the third priority to ensure that each group remains with at least half the members. At this stage, when the remaining number of employees still exceeded the required number, the years of experience would be considered whereby the employee with the highest number of years would be retained while those with the least be demoted. After observation of the years of experience, the remaining members will be eliminated based on their age thereafter the rest will be subjected to their positions at the firm in terms of seniority then the comments or the notes.
Sense making
After the panel has developed the above options, the next step was to implement the options to arrive at the elimination decisions (Alrabiah and Drew, 2018, pp.19-31). The team identified that no member or employee could fit all the factors thus leading to prioritizing then according to the presented order. This ensured that those members who did not meet the qualification of a certain category were eradicated from the list while considering the minimum number required for each project or department. This required that every time an elimination is made, the number be crosschecked against the various projects so that no project is left without employees. Using the above priority of options, the following were the outcomes of the analysis.
Developed options of elimination according to priority |
||||||||
Team/project |
Employee |
Performance rate |
YOS >2 |
KPI |
Seniority |
comments |
Age |
Outcomes |
Team A |
1. Jacob |
x |
||||||
2. Michael |
1) Michael |
|||||||
3. Mary |
2) Mary |
|||||||
4. Joshua |
x |
|||||||
5. Yousef |
3) Youseff |
|||||||
6. Emma |
4) Emma |
|||||||
7. Abe |
x |
|||||||
Team B |
8. Shavonne |
|||||||
9. Sibyl |
5) Sibyl |
|||||||
10. Larry |
x |
|||||||
11. Zane |
x |
|||||||
12. Rudolph |
x |
|||||||
Team C |
13. Mica |
x |
||||||
14. Kim |
6) Kim |
|||||||
15. Earle |
x |
|||||||
16. Hester |
x |
|||||||
17. Lindsey |
||||||||
18. Mario |
x |
|||||||
19. Simon |
7) Simon |
|||||||
20. Kathrine |
8) Kathrine |
|||||||
Team D |
21. Fraser |
9) Fraser |
||||||
22. Gemma |
10) Gemma |
|||||||
23. Heath |
x |
|||||||
24. Rashid |
x |
|||||||
25. Nada |
11) Nada |
|||||||
26. Paul |
12) Paul |
|||||||
27. Colin |
x |
|||||||
Team E |
28. Bryan |
13) Bryan |
||||||
29. Vito |
14) Vito |
|||||||
30. Marcel |
x |
|||||||
31. Claude |
15) Claude |
|||||||
32. Louis |
x |
|||||||
HR |
33. Kelvin |
|||||||
34. Lillian |
x |
|||||||
35. Terry |
x |
|||||||
36. Rubin |
16) Rubin |
|||||||
37. Pam |
x |
|||||||
38. Percy |
17) Percy |
|||||||
Operations |
39. Hassan |
18) Hassan |
||||||
40. Fred |
19) Fred |
|||||||
41. Angelo |
x |
|||||||
42. Rick |
20) Rick |
|||||||
43. Keith |
x |
|||||||
Marketing |
44. Stephen |
21) Stephen |
||||||
45. Blake |
22) Blake |
|||||||
46. Mohammad |
23) Mohammad |
|||||||
47. Rosa |
x |
|||||||
48. Yvette |
24) Yvette |
|||||||
Technical |
49. Lee |
x |
||||||
50. Marc |
25) Marc |
|||||||
51. Chad |
26) Chad |
|||||||
52. Anton |
x |
|||||||
53. Torri |
x |
|||||||
54. Lorenzo |
27) Lorenzo |
|||||||
Finance |
55. Sarah |
x |
||||||
56. Nima |
x |
|||||||
57. David |
x |
|||||||
58. Ali |
28) Ali |
|||||||
59. Maria |
29) Maria |
|||||||
60. Nicola |
30) Nicola |
|||||||
Notes · The coloured blocks indicate that beyond a certain stage the number of members cannot be reduced further, thus the end of elimination in that specified department. · Yellow blocks – Number exceeded at stage 1 · Green blocks – number exceeded at stage 2 · Blue blocks – Number exceeded at stage 3 · Light green blocks – Number exceeded at stage 4 · Light blue- Outcomes · YOS – Years Of Service · KPI – Key Performance Indicators · Human Resources |
Table 1: The analysis results
From the analytic results, it was clear that for the company the company to sustain its operation, it could only lay of a maximum of 30 employees. The “X” in the cells imply those employees declared redundant by the decision making panel. In the analysis, the factors considered in their order of priority were varied against the project code or teams to ensure that no team or project had more than half its members truncated.
(Blumenthal-Barby, and Krieger, 2015, pp.539-577) explains the importance of testing and feedbacks as a critical tool to determine the accuracy of results in the analysis of decisions to solve problems. After coming up with the list of redundant and non-redundant members, the panel scheduled to conduct tests on the results to determine if there would be any changes. This was done by interchanging the developed options that would help to come up with other alternatives if there were any. The tests and the feedback obtained reflected the same results of the earlier made decisions by the team. However, the feedback indicated that the two members, in essence, Angelo and David, who were eliminated at stage four, were retained making the total number of employees laid off to be 28. From the classical model of decision-making, this provided the panel with two alternatives, where one was to eliminate 28 members while the other was to eliminate 30 members. However, the panel concluded that using the model that involved an elimination of 30 members since the executive managers required a model that would ensure the maximum number of employees are retrenched.
From the rational decision making model, the selected panel sort came up with a number of recommendations to be forwarded to the executive managers. The team was able to establish that for the company to keep its operations it required to lay off a minimum of 25 members but a maximum of 30. From the data analysis, exceeding 30 members from the given list will lead to a shortage of employees from some projects and teams, which would lead to serious operational problems. Furthermore, the team jointly recommended that for the executive managers to lay of more than 30 members they should consider other factors such as joining of teams or projects or removing non-profitable products from the business organisation. However, the panel also advised the managers to observe caution on the selection of projects, which promotes profits and the market shares.
Formulation of Potential Solutions
Conclusion
In conclusion, group decision-making are advantageous over individual decisions due to the logical approach taken to derive decisions and solutions for the defined problems (Cabrerizo et al., 2014, pp.115-127). The division of tasks among the members ensured that concrete research and thoughts are given to different factors in the problem before they are brought to group scrutiny during meetings. Moreover, the group work ensured commitment to the task with a deadline-oriented motive. Additionally, the selection of the decision model is made easier as the biases that arise during the selection of the tools are eliminated by virtue of diversity among the members (Strandburg-Peshkin, Farine, Couzin, and Crofoot, 2015, pp.1358-1361). However, the recommendations submitted to the executive managers are subject for review and clarity in case they raised any query or explanation to the team.
References
Alrabiah, A., & Drew, S. (2018). Formulating optimal business process change decisions using a computational hierarchical change management structure framework: a case study. Journal of Systems and Information Technology, 19-31.
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
Birkland, T. A. (2015). An introduction to the policy process: Theories, concepts, and models of public policy making. London. Routledge.
Blumenthal-Barbie, J. S., & Krieger, H. (2015). Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy. Medical Decision Making, 35(4), 539-557.
Bolman, L. G., & Deal, T. E. (2017). Reframing organizations: Artistry, choice, and leadership. New Jersey. John Wiley & Sons.
Wu, J., Dai, L., Chiclana, F., Fujita, H., & Herrera-Viedma, E. (2018). A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust. Information Fusion, 41, 232-242.
Cabrerizo, F. J., Ureña, R., Pedrycz, W., & Herrera-Viedma, E. (2014). Building consensus in group decision making with an allocation of information granularity. Fuzzy Sets and Systems, 255, 115-127.
Cameron, E., & Green, M. (2015). Making sense of change management: A complete guide to the models, tools and techniques of organizational change. London. Kogan Page Publishers.
Cascetta, E., Carteni, A., Pagliara, F., & Montanino, M. (2015). A new look at planning and designing transportation systems: A decision-making model based on cognitive rationality, stakeholder engagement and quantitative methods. Transport policy, 38, 27-39.
Davis, J. H. (2014). Group decision making and quantitative judgments: A consensus model. In Understanding group behavior (pp. 43-68). London. Psychology Press.
Elmes, M., & Barry, D. (2017). Strategy retold: Toward a narrative view of strategic discourse. In The Aesthetic Turn in Management (pp. 39-62). London. Routledge.
Endsley, M. R. (2017). Toward a theory of situation awareness in dynamic systems. In Situational Awareness (pp. 9-42). London. Routledge.
Harris, T. E., & Sherblom, J. C. (2018). Small group and team communication. Illinois. Waveland Press.
Jalalimajidi, A., & Jalalimajidi, M. (2016). Investigating the solutions as to enhance service to the applicants of bank facilities using Expert system decision-making model (case study: Bank MELI Iran). International Journal of Humanities and Cultural Studies (IJHCS)? ISSN 2356-5926, 1(1), 2015-2025.
- Roehrich, J., Grosvold, J., & U. Hoejmose, S. (2014). Reputational risks and sustainable supply chain management: Decision making under bounded rationality. International Journal of Operations & Production Management, 34(5), 695-719.
Marsh, K., IJzerman, M., Thokala, P., Baltussen, R., Boysen, M., Kaló, Z., … & Devlin, N. (2016). Multiple criteria decision analysis for health care decision making—emerging good practices: report 2 of the ISPOR MCDA Emerging Good Practices Task Force. Value in health, 19(2), 125-137.
Morente-Molinera, J. A., Pérez, I. J., Ureña, M. R., & Herrera-Viedma, E. (2015). On multi-granular fuzzy linguistic modeling in group decision making problems: a systematic review and future trends. Knowledge-Based Systems, 74, 49-60.
Schoenfeld, A. H. (2014). Mathematical problem solving. Amsterdam. Elsevier.
Strandburg-Peshkin, A., Farine, D. R., Couzin, I. D., & Crofoot, M. C. (2015). Shared decision-making drives collective movement in wild baboons. Science, 348(6241), 1358-1361.
Tideman, N. (2017). Collective decisions and voting: the potential for public choice. Routledge.
Wheelen, T. L., Hunger, J. D., Hoffman, A. N., & Bamford, C. E. (2017). Strategic management and business policy. London. Pearson.
Wu, J., Dai, L., Chiclana, F., Fujita, H., & Herrera-Viedma, E. (2018). A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust. Information Fusion, 41, 232-242.