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1. What is the non-discounted payback period of the project?

2. What is the profitability index of the project?

3. What is the IRR of the project?

4. What is the NPV of the project?

5. How sensitive is the NPV to changes in the price of the new SSHA?

6. How sensitive is the NPV to changes in the quantity sold of the new SSHA?

7. Should Booli Electronics produce the new SSHA?

8. Suppose Booli Electronics loses sales on other models because of the introduction of the new SSHA.  How would this affect your analysis?

The main objective of the report is to analyse the acceptability of the project that is new SSHA by Booli Electronics. The acceptability will be evaluated through computing the payback period, profitability index, internal rate of return and net present value of the project. Further, the report will analyse the sensitivity of net present value with respect to changes in sales price and changes in sales quantity.

Non-discounted payback period

This method is used under capital budgeting to measure the payback period of any project. However, the main disadvantage of the method is that is does not takes into consideration the time value of money factor and further ignores the amount receivable after payback period (Baucells and Borgonovo 2013). As per the calculation the non-discounted payback period of ne SSHA project is 2.21 years.

Profitability index (PI)

This index identifies the correlation among the costs and benefits of proposed project (Pasqual, Padilla and Jadotte 2013). The calculated profitability index for new SSHA project is 1.72.

Internal rate of return (IRR)

IRR is the rate of interest at which the cash inflows of the projects equals to the cash outflows of the project. In other words the net cash flow becomes zero. As per the calculation the IRR of new SSHA project is 20.75%.

Net present value (NPV)

NPV presents the expected cash flows from any project and while computing the expected cash inflows the initial cash outflows are deducted from it to analyse the project’s acceptability (Leung et al. 2014). Project is accepted if the NPV is positive and not accepted where the NPV is negative. NPV of new SSHA project is \$ 32,544,049.64.

Sensitivity analysis with regard to changes in sales price

Economic and financial analysis for cost-benefit of any project is depended upon the forecasting of quantifiable variables. The values of those variables are projected on the basis of most expected factors like changes in the sales price or changes in the sales volume or quantity (McAuliffe 2015).  These are influenced by large number of factors and actual value can significantly vary from the expected values. Therefore, it is important to take into consideration the impact of expected changes with regard to the key variables. Sensitivity analysis mainly focuses on the evaluation of impacts likely to take place due to the variables on the NPV of the project that is used for measuring the viability of the project (Butler et al. 2014).

Sensitivity analysis is the method of analysing the effect of changes in the project variables on the most expected case. Generally the unfavourable changes are taken into consideration under the sensitivity analysis. Main objectives of sensitivity analysis are as follows –

• It is used to recognize the likely impacts of unfavourable changes under the key variables.
• It recognizes the key variables that has an influence on the benefit and cost streams of the project
• It recognizes the actions that can be taken to eliminate the expected unfavourable impact on the project
• To analyse whether the decisions will have an impact on the changes
 Price NPV \$             325,44,049.64 500 \$            (114,80,321.15) 515 \$              (79,10,777.57) 530 \$              (43,41,233.99) 545 \$               (7,71,690.42) 560 \$               27,97,853.16 575 \$               63,67,396.74 590 \$               99,36,940.31 605 \$             135,06,483.89 620 \$             170,76,027.47 635 \$             206,45,571.05 650 \$             242,15,114.62 665 \$             277,84,658.20 680 \$             313,54,201.78 695 \$             349,23,745.35 710 \$             384,93,288.93 725 \$             420,62,832.51 740 \$             456,32,376.08 755 \$             492,01,919.66 770 \$             527,71,463.24 785 \$             563,41,006.81 800 \$             599,10,550.39 815 \$             634,80,093.97 830 \$             670,49,637.55 845 \$             706,19,181.12 860 \$             741,88,724.70 875 \$             777,58,268.28 890 \$             813,27,811.85 905 \$             848,97,355.43

It can be observed from the above table and graph that the NPV of the project increases with the increase in the selling price. For the selling price ranged from \$ 500 per unit to \$ 905 per unit the NPV is ranged from - \$ 114,80,321.15 to \$ 848,97,355.43. Therefore, for every \$ 15 changes in selling prices the NPV increases by \$ 35,69, 543.58. Therefore, the  NPV varies directly with the change in selling prices and the NPV is highly sensitive to changes in the sales price.

Sensitivity analysis with regard to changes in sales quantity

It is performed to analyse the changes in NPV with the changes in sales quantity. However the sensitivity analysis shall be recognized in systematic way (Leyman and Vanhoucke 2016). For meeting the objectives of sensitivity analysis the below mentioned steps must be followed –

• Recognizing the key variables with regard to which the decision related to project can be sensitive
• Measuring the likely impact of the variables in base case of NPV and calculating the indicator of sensitivity or switching the value, if required (Iooss and Lemaître 2015)
• Taking into consideration the combination of the variables that may lead to unfavourable direction
• Analysing direction and scale for expected changes with regard to the recognized key variables that involves recognition of the sources for changes.
 Sales volume Amount \$  325,44,049.64 25000 \$  259,49,461.64 45000 \$  281,47,657.64 65000 \$  303,45,853.64 85000 \$  325,44,049.64 105000 \$  347,42,245.64 125000 \$  369,40,441.64 145000 \$  391,38,637.64 165000 \$  413,36,833.64 185000 \$  435,35,029.64 205000 \$  457,33,225.64 225000 \$  479,31,421.64 245000 \$  501,29,617.64 265000 \$  523,27,813.64 285000 \$  545,26,009.64

It can be observed from the above table and graph that the NPV of the project increases with the increase in the selling quantity. For the selling quantity ranged from 25000 units to \$ 285,000 unit the NPV is ranged from \$ 259,49,461.64 to \$ 545,26,009.64. Therefore, for every 20,000 unit changes in selling quantity the NPV increases by \$ 21,98,196. The sensitivity will be regarded as positive if there is positive correlation between the quantity and NPV. It means to say that the positive changes in quantity increase the NPV and negative changes in quantity reduce the NPV. Therefore, the NPV of new SSHA varies directly with the change in selling quantity and the NPV is highly sensitive to changes in the sales quantity.

Conclusions

Production of SSHA

Production of new SSHA will be depended on the cash inflows and cash outflows from the project. If the expected present value of the cash inflows from production of new SSHA is positive then the company shall go for the production otherwise not (Gallo 2014).  It is identified from the calculation that the NPV of the project for new SSHA comes to \$ 32,544,049.64. it is signifying that the present values of cash inflows of the project is more than the cash outflows required for the project. Therefore the company shall produce ne SSHA.

If the company loses sales on other model owing to the production of new SSHA, the losses amount shall be added up with the initial cash outflows of the ne SSHA project. If inclusion of loss from other model lead to negative NPV from the new SSHA project then the company shall not produce ne SSHA. On the contrary is the NPV still comes positive then the company shall produce new SSHA.

Reference

Baucells, M. and Borgonovo, E., 2013. Invariant probabilistic sensitivity analysis. Management Science, 59(11), pp.2536-2549.

Butler, M.P., Reed, P.M., Fisher-Vanden, K., Keller, K. and Wagener, T., 2014. Identifying parametric controls and dependencies in integrated assessment models using global sensitivity analysis. Environmental modelling & software, 59, pp.10-29.

Gallo, A., 2014. A refresher on net present value. Harvard Business Review, 19.

Iooss, B. and Lemaître, P., 2015. A review on global sensitivity analysis methods. In Uncertainty management in simulation-optimization of complex systems (pp. 101-122). Springer, Boston, MA.

Leung, B., Springborn, M.R., Turner, J.A. and Brockerhoff, E.G., 2014. Pathway?level risk analysis: the net present value of an invasive species policy in the US. Frontiers in Ecology and the Environment, 12(5), pp.273-279.

Leyman, P. and Vanhoucke, M., 2016. Payment models and net present value optimization for resource-constrained project scheduling. Computers & Industrial Engineering, 91, pp.139-153.

McAuliffe, R.E., 2015. Net Present Value. Wiley Encyclopedia of Management, pp.1-1.

Pasqual, J., Padilla, E. and Jadotte, E., 2013. Equivalence of different profitability criteria with the net present value. International Journal of Production Economics, 142(1), pp.205-210.

Cite This Work

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