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Write the Key Factors and there Approaches.

Background of Conroy Manufacturing Company

The process of decision-making is an integral part of the company that helps the company in the evaluation and coming up to a decision that may influence the workings of the company. The decision-making helps the company in the process of the rationale and the sound decision for a company in the different scenarios. The decision making process plays an important vital role in the managerial and operational decisions taken (Hinton and Frosst 2017).

The following report has taken down a case study in which the case study helped us evaluate and understand the methods of decision making and the considerations that can be taken from the same for the overall betterment of the company and the organizations. The analysis of the industrial manufacturing product that is aimed at introducing or launching a product and forecasting the various possibilities that are linked with the same. The possibilities and he scenarios along with the probabilities helped in better evaluation and analysis of the one of the possible scenarios after he launch of a certain product (Oehmen et al. 2014).

The purpose and aim for the report is a crucial analysis of the various factors that may be important and that can influence the nature of the product (Schöggl, Baumgartner and Hofer 2017).

The Conroy Manufacturing Company originated in the year 1960, and the same was established on a army base that was near Frankston near Melbourne. The company in its primary stage of operation and manufacturing used to produce and goods on a small scale basis and the same and the company in the due course of the time explored and started with other various other forms of products. The new management team that was hired by the company had actually helped them overcome and adopt the use of the big data analytics in the evaluation of the product analysis. The company then started with manufacturing of consumer’s goods and services that included car engine tuner and other products like electric drillers (Abdallah et al. 2018).

The products that were initially manufactured by the company and the same which were previously recognized by the company has been good and successful for the company even compared with other companies who offers similar substitute products and the companies that are in the same industries (Luzzini, et al. 2015). The company had come up with the new plan for manufacturing of the new lawnmower which will be incorporated with the new voice control feature in the same for making certain alert and update features (Adler, Pittz and Meredith 2016). The development would be done but prior to that there will be costs that will be spent in the research and development of the product and the expense for the same will be around $8 million and the costs which were spent initially by the company in the form of the market research and development of the design of a product is around $2.5million. The process and the ways used by the company decided related to change of the location of the manufacturing or the production of the same (Modarres, Kaminskiy and Krivtsov 2016). Two of the company’s site will be used for the production unit. The first textile is that of an old aerodrome and the other is the old textile mill. The textile mill could be acquired for 6 million dollars but the acquisitions period will be in the next two years. The additional costs that would be required for the overall development of the same will be around 4 million (Tao et al. 2017). Hence the assumption taken were that the production will start in the year 2019 and the development of the product will be done till 2017. The scenario if turns out to be a bit different than the final production will be carried on from the year 2020. The second site will cost the company will cost around 24 million dollars.

Product Development and Market Analysis

The site decided for the production involves both time and money in the form of investments and the developments also needs to be done on the same hand. The other factor will be the incurring or the ongoing costs and the investments that will be done. The third factor will be the cost and time involved in the development of the product (Schulte and Hallstedt 2018). The other factor is the different scenarios under a certain probabilities factor that will explain the sources of variation of the product and the outcome from the same in the form of sales. The other key factor will be the determining of the exit route if the developed product does not adds up expectation of what was desired from the product. The determination of the overall cash flows from the same which will mark the success or the probability factor in each of the scenarios. The potential and the key information which will executed will be based on the SMART analysis which will incorporate certain financials tools like probability and Net present value features (Chang and Taylor 2016). 

Expected Values

Cost of Capital

Possible Scenario 1

Possible  Scenario 2

Possible Scenario 3

Possible Scenario 4

Scenario 5

Scenario 6

(in $ million)

(in $ million)

(in $ million)

(in $ million)

(in $ million)

(in $ million)

5.00%

14.53

4.04

13.94

-0.41

2.34

-0.75

6.00%

14.04

3.88

13.43

-0.48

2.24

-0.80

7.00%

13.57

3.72

12.94

-0.55

2.14

-0.85

8.00%

13.12

3.57

12.47

-0.62

2.05

-0.89

9.00%

12.69

3.43

12.01

-0.68

1.97

-0.94

10%

12.27

3.29

11.57

-0.75

1.88

-0.98

11.00%

11.86

3.15

11.15

-0.81

1.80

-1.02

12.00%

11.47

3.02

10.74

-0.87

1.72

-1.06

13.00%

11.10

2.90

10.34

-0.92

1.65

-1.10

14.00%

10.73

2.78

9.96

-0.98

1.58

-1.13

15.00%

10.38

2.66

9.59

-1.03

1.51

-1.17


The assumptions and facts used in the decision tree analysis was according to the use of the SMART Analysis which is a Smart, Specific, Measurable, Achievable, Relevant and Time-Series oriented) method of analysis (Zakeri and Syri 2015). The method of analysis and the primary or the first scenario of the decision tree used in the scenario was the product development and the invention in the year 2017. In the initial year of the product development an all total of $ 6 MN would be required for the purchase of the Campellfield site. The equipment’s and other additional assets for the company would require an initial outflow of 4 MN. The developed prototype, and for the conversion of the Laverton site which will be developed at the site the costs estimated for the same, will be nil. There will be addition 6 mn of investment that will be required in the initial year of the development of the product this sums up to an all total of requirement of 18mn in the first phase of the product development (Ardolino et al. 2018). The scenario discussed above shows that the market condition assumed and the NPV generated after taking all the inflows and outflows of the cash flows was around $32.72 MN. There needs to be a probability function, which was also run in the above scenarios. The probability that the development of the product will be completed in the first scenario itself is around 75% and there is a 50% probability for the selection of the site. The selection of the site will bring about 10 million of total cost for the company. The project would be continued even for the next year as well if the same is not completed within the first year of the project but the same will cost the company an expense for about 8 million in the second year which will be base of the research and development expenses paid by the company. The additional expense such as the cost for modifying the prototype will be somewhat around 6.4 million dollars. It is crucial to note that the cost for purchasing the Campbellfield site and for the conversion of the Laverton site will not change under the scenario. In the secondary year of the project the market condition is taken as normal. Under the third scenario of the project, the development of the product will be analyzed. The probability that the new product will be developed within December 2017 is around 75%.Initial amount of investment in the following year will be around 8 million dollars and the cost for conversion of the laverton site in the following year will be around 24 million dollars while others costs are assumed to be almost zero. In both better and worst market condition, the cost structure for the company will remain the same. The probability in the year 2018 for the development of the new product is around 25% for the Laverton Site and the following costs that will be spent in the research, development of the product will be around $8 million, and the costs and the investment for the modification of the prototype will be around $6.4 million dollars. The market conditions can be worst under the following year but the cost structure analyzed is expected to remain the same.

Decision Tree Analysis and Scenario Estimation

The above figure and table gives us a detailed and a brief analysis of the total probability feature, which is grouped year wise. 75% is the probability function determined in the year 2017 and the same probability is around 25% in the year 2018. 50% probability in each of the site is determined in the year 2017. It is estimated and by the probability that the production will start in the year 208 is around 100% and the values expected from the same is 12.27 million dollars.

The objectives are described below using the SMART toll below:

Specific

· Complete assurance on the fact regarding the successful implementation and completion for the prototype (Hallstedt and Isaksson 2017).

· There should be a complete strategic management of the data analysis and the interpretation of the financials of the company, which could be done with the proper organisation structure of the company (Johannknechtet al. 2016)

· Managing the financial that the cash flows of the company and the relevant interest rate in the same context should be analysed properly.

· The Exit route for the product development should be pre-planned such that the loss arsing from the same scenario is minimized.

Measurable

· The measurement for the viability of the product should be done by the output the product is providing and the return generated from the same.

· The breakdown of the components of the sales and a detailed analysis of the same will help us further analyse the sales of the company.

· The return the company is generating on the product will be well assessed by the financials of the company.

Achievable

· The marketing plan of the product should be such that the results derived from the same should bring efficiency in the company.

· Incentive based sales and the appraisal from the sales brings motivation to the employees of the company.

Relevant

· Optimum utilization of resources is only possible if the workforce is well skilled.

Time Bound

· There should be proper evaluation of the time it will actually take for the successful creation of the prototype that will be used and the extent of research and development that will be required for the development of the product.

There are several concerns that have been identified after a detailed analysis was performed on the Conroy Manufacturing Company. The strengths and the limitations identified both have their own pros and cons for the company and the same is discussed in the analysis (Tyagi, et al. 2015).  The key thing that should be kept in analysing is that the project outcome is based on the probability function and shows some of the possible scenarios of the output of production. The time division and the evaluation for the same is totally predicted and the same is taken down after a decision node was prepared and the following scenarios index which the product will take time for the development. The time taken for such development and process is variable and non-static in nature, which can vary depending on several factors such as market and business conditions and externalities (Karlsson, Larsson and Rönnbäck 2018). This is the main cause for the limitations of the product output derived, as the same is dependent on the probability and the some of the possible scenarios of the product, which covers sequential analysis and not a complete analysis of the outcome of the product scenarios. It is crucial to note that even if the product development and movement changes as per the predicted scenarios the management structure and the role of management in this scenario plays an important role (Andersen et al. 2017).

The suggestion for the effectiveness in the overall company is the managerial decisions taken by the company. The analysis for the company using the SMART tool, which helped us asses the crucial factors, that are important as the same enables the company to assess the outcome of the same and the way the management of the company tackles the same (Kohtamaki et al. 2015). The product development of the company should be well assessed and the different scenarios and the outcomes should be well assessed using the full sequential risk analysis of the product. The use of simulation should give a full sequential risk of the same and all the possible combinations and scenarios are well assessed. The use of big data analytics could be done which could bring further enhancement and updating of the same could bring efficiency in the level of operations of the company (Rakshasbhuvankar and Patole 2014).

Objectives Using SMART Tool

Conclusion

The Conroy Manufacturing Company has been able to use and operate with various kind of industrial products that required product development evaluation and the same was done through sequential risk that is through decision tree analysis. The probability functions incorporated has given the various scenarios output and the cash inflow and outflows at the same. The strengths and limitations analysed and identified for the company helped us analyse the various aspects under which the management of the company can assess the operations of the company. 

Reference

Abdallah, I., Dertimanis, V., Mylonas, H., Tatsis, K., Chatzi, E., Dervilis, N., Worden, K. and Maguire, E., 2018. Fault diagnosis of wind turbine structures using decision tree learning algorithms with big data. In Safety and Reliability–Safe Societies in a Changing World (pp. 3053-3061). CRC Press.

Adler, T.R., Pittz, T.G. and Meredith, J., 2016. An analysis of risk sharing in strategic R&D and new product development projects. International Journal of Project Management, 34(6), pp.914-922.

Andersen, A.K., Nafei, N., Planck, M. and Nielsen, L.M., 2017. The frame network of interdisciplinary stakeholder compositions in the early phases of new product development. In DS 87-1 Proceedings of the 21st International Conference on Engineering Design (ICED 17) Vol 1: Resource Sensitive Design, Design Research Applications and Case Studies, Vancouver, Canada, 21-25.08. 2017.

Ardolino, M., Rapaccini, M., Saccani, N., Gaiardelli, P., Crespi, G. and Ruggeri, C., 2018. The role of digital technologies for the service transformation of industrial companies. International Journal of Production Research, 56(6), pp.2116-2132.

Chang, W. and Taylor, S.A., 2016. The effectiveness of customer participation in new product development: A meta-analysis. Journal of Marketing, 80(1), pp.47-64.

Hallstedt, S.I. and Isaksson, O., 2017. Material criticality assessment in early phases of sustainable product development. Journal of Cleaner Production, 161, pp.40-52.

Hinton, G. and Frosst, N., 2017. Distilling a Neural Network Into a Soft Decision Tree.

Johannknecht, F., Gatzen, M.M., Hahn, D. and Lachmayer, R., 2016, November. Holistic Life Cycle Costing Approach for Different Development Phases of Drilling Tools. In International Petroleum Technology Conference. International Petroleum Technology Conference.

Karlsson, A., Larsson, L. and Öhrwall Rönnbäck, A., 2018. Product-service system innovation capabilities: linkages between the fuzzy front end and subsequent development phases. International Journal of Production Research, 56(6), pp.2218-2232.

Kohtamaki, M., Hakala, H., Partanen, J., Parida, V. and Wincent, J., 2015. The performance impact of industrial services and service orientation on manufacturing companies. Journal of Service Theory and Practice, 25(4), pp.463-485.

Luzzini, D., Amann, M., Caniato, F., Essig, M. and Ronchi, S., 2015. The path of innovation: purchasing and supplier involvement into new product development. Industrial Marketing Management, 47, pp.109-120.

Modarres, M., Kaminskiy, M.P. and Krivtsov, V., 2016. Reliability engineering and risk analysis: a practical guide. CRC press.

Oehmen, J., Olechowski, A., Kenley, C.R. and Ben-Daya, M., 2014. Analysis of the effect of risk management practices on the performance of new product development programs. Technovation, 34(8), pp.441-453.

Rakshasbhuvankar, A.A. and Patole, S.K., 2014. Benefits of simulation based training for neonatal resuscitation education: a systematic review. Resuscitation, 85(10), pp.1320-1323.

Schöggl, J.P., Baumgartner, R.J. and Hofer, D., 2017. Improving sustainability performance in early phases of product design: A checklist for sustainable product development tested in the automotive industry. Journal of Cleaner Production, 140, pp.1602-1617.

Schulte, J. and Hallstedt, S., 2018. Risk Management Practices in Product Development Companies. In Norddesign, August 14-17, 2018, Linköping, Sweden.

Tao, L., Wu, D., Liu, S. and Lambert, J.H., 2017. Schedule risk analysis for new-product development: The GERT method extended by a characteristic function. Reliability Engineering & System Safety, 167, pp.464-473.

Tyagi, S., Choudhary, A., Cai, X. and Yang, K., 2015. Value stream mapping to reduce the lead-time of a product development process. International Journal of Production Economics, 160, pp.202-212.

Zakeri, B. and Syri, S., 2015. Electrical energy storage systems: A comparative life cycle cost analysis. Renewable and Sustainable Energy Reviews, 42, pp.569-596.

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