Capital Budgeting Analysis For New SSHA Model

Payback Calculation

Booli Enterprise that manufactures Smart speaker and home assistant (SSHA) and generates maximum revenue of the company from that. However, the company is now planning to introduce advance model of the existing SSHA to will be available in various colours and will have various advance functions. However, investment for new SSHA model will require initial investment and the investment will be analysed through various measures like profitability index, net present value, payback period and internal rate of return (Pasqual, Padilla and Jadotte 2013).

1. Non-discounted payback period

Non-discounted payback period for the project –

Year	Cash inflow Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	Cumulative cash flow
0	$   (47,025,000.00)
1	$       9,158,160.00	$          9,158,160.00
2	$     34,307,097.60	$        43,465,257.60
3	$     25,842,344.45	$        69,307,602.05
4	$     16,194,120.97	$        85,501,723.02
5	$     23,547,757.33	$      109,049,480.35

Non-discounted payback period = 2 + (47,025,000 – 43.465,257.60) / (69,307,602.05 – 43,465,257.60) = 2.14 years.

2. Profitability index

PI = PV of future cash flows / Initial investment (Levy 2015)

PI = $ 77,573,881.43 / 47,025,000 = 1.65

Hence, the PI of new SSHA model is 1.65.

3. Internal rate of return

Internal rate of return is the rate at which the present value of cash inflows will be equal to cash outflows. The IRR of the project is 19.77% (Leyman and Vanhoucke 2016)

4. Net present value

Net present value is the difference between the present value of cash inflows and cash outflows. The NPV of the project is $ 30,548,881.43 (Yuniningsih, Widodo and Wajdi 2017).

5. Sensitivity analysis for price change

Sensitivity analysis is conducted for the purpose of ascertaining the changes which takes places on the dependent variable for significant changes in the independent variables which are to be considered (Akbarzadehet al. 2016). The analysis is generally conducted considering that the dependent variable is one and the independent variable is also one. Sensitivity analysis is conducted so as to ensure that the business is able to understand how much changes are brought forward when a small change in independent variables occur. Certain examples of independent variables which can be given are sales prices, cost of capital of the business (Nguyen and Reiter 2015). The dependent variables depend on the nature of the business and the choice of the business as to what factor the business wants to consider for the overall sensitivity analysis (Sanchezet al. 2013). The various steps which are required to be carried out in case of sensitivity analysis is given below in details:

• The first step in the sensitivity analysis is the identification of the inputs and outputs which are related to the business. As per the question which is provided the input is the selling price and the output is NPV which is calculated. The impact on the NPV will be will be measured with the small changes in the price of the business. The other factors which are involved with the investment are factors like selling quantity, initial investments and discount rate are considered to be constant in such a case.
• The second step will be to consider the percentage change in NPV which is caused due to percentage change in the selling price (Baucells and Borgonovo 2013).
• After the above two process, the sensitivity will be measured for the changes in the NPV due to changes in the selling price of the product.
• After the above steps, the management takes necessary decisions based on the sensitivity data and graph as plotted using such a data.

Price	NPV	Changes (Price)	Changes (NPV)
	$                              –
500	$            (15,635,004.70)
530	$              (8,225,825.11)	30	$      7,409,179.59
560	$                (816,645.51)	30	$      7,409,179.59
590	$               6,592,534.08	30	$      7,409,179.59
620	$             14,001,713.67	30	$      7,409,179.59
650	$             21,410,893.27	30	$      7,409,179.59
680	$             28,820,072.86	30	$      7,409,179.59
710	$             36,229,252.46	30	$      7,409,179.59
740	$             43,638,432.05	30	$      7,409,179.59
770	$             51,047,611.64	30	$      7,409,179.59
800	$             58,456,791.24	30	$      7,409,179.59
830	$             65,865,970.83	30	$      7,409,179.59
860	$             73,275,150.43	30	$      7,409,179.59
890	$             80,684,330.02	30	$      7,409,179.59
920	$             88,093,509.61	30	$      7,409,179.59
950	$             95,502,689.21	30	$      7,409,179.59
980	$            102,911,868.80	30	$      7,409,179.59
1010	$            110,321,048.40	30	$      7,409,179.59
1040	$            117,730,227.99	30	$      7,409,179.59
1070	$            125,139,407.58	30	$      7,409,179.59
1100	$            132,548,587.18	30	$      7,409,179.59
1130	$            139,957,766.77	30	$      7,409,179.59
1160	$            147,366,946.37	30	$      7,409,179.59
1190	$            154,776,125.96	30	$      7,409,179.59
1220	$            162,185,305.55	30	$      7,409,179.59
1250	$            169,594,485.15	30	$      7,409,179.59
1280	$            177,003,664.74	30	$      7,409,179.59

 

Changes in price	4%
Changes in NPV	24%
Sensitivity	555.41%

The graph above is plotted showing the changes in the NPV of the project due to the changes in the selling price. The NPV changes by 24% with every 4% change in the selling price of the new SSHA model. Thus, from the above analysis the output is highly sensitive to the input as the sensitivity of the input with regards to the output is about 555.41%. Therefore for the changes in the prices from $ 500 to $ 1300, the NPV has increased from -$ 15,635,004.70 to $ 184,412,844.33.

Profitability Index (PI)

1. Sensitivity analysis for quantity change

It is a known fact that the use of sensitivity analysis in any business is a common factor nowadays. Most of the businesses uses sensitivity analysis to measure the changes which occurs on the dependent when there is a change in the independent variable of the business (Tian 2013). The method is useful for establishing a relationship between the independent and dependent variable which the business is considering. Such dependent and independent variable can be anything such as NPV and selling price of the product. The various steps which can be suggested for the purpose of conducting sensitivity analysis are given below in point form:

• In this case the input which is chosen by the business is the selling quantity and the output that is to be considered is NPV. The changes in the NPV will be measured in terms of the changes in the selling quantity of the product. The other factors which are related to the project which can affect the analysis such as discount rate, initial investments and selling price of the product are considered to be constant.
• The percentage change in the NPV will be measured with respect to the percentage change in the selling quantity of the product (Cucchiella, D’Adamo and Gastaldi 2015).
• The NPV of the investment is to be then measured with the selling quantity and the same is to be analyzed as well keeping in the that other factors remain constant (Wang, Xia and Zhang 2014).
• Then it is to be ascertained how the analysis of sensitivity of the project will be affecting the business decision making process.

Sales volume	NPV	Changes (Quantity)	Changes (NPV)
	$                      –
25000	$  22,354,148.82
50000	$  25,411,884.87	25000	3,057,736.05
75000	$  28,469,620.92	25000	3,057,736.05
100000	$  31,527,356.97	25000	3,057,736.05
125000	$  34,585,093.02	25000	3,057,736.05
150000	$  37,642,829.07	25000	3,057,736.05
175000	$  40,700,565.12	25000	3,057,736.05
200000	$  43,758,301.17	25000	3,057,736.05
225000	$  46,816,037.22	25000	3,057,736.05
250000	$  49,873,773.27	25000	3,057,736.05
275000	$  52,931,509.32	25000	3,057,736.05
300000	$  55,989,245.37	25000	3,057,736.05
325000	$  59,046,981.42	25000	3,057,736.05
350000	$  62,104,717.47	25000	3,057,736.05

 

Changes in quantity	27%
Changes in NPV	10%
Sensitivity	36.83%

From the analysis which is conducted in the above, it is clear that the NPV changes by 10% with every change which takes place on the selling price of the SSHA model. The sensitivity of the input in relation to the output will be 36.83%. Therefore, it can be said that the output is moderately sensitive to the inputs of the business. As the selling quantity changes from 25000 to 350000, the NPV has increased from $ 22,354,148,82 to $ 62,104,717.47.

The major use of the sensitivity analysis is in the decision-making process for selecting the best possible alternative of the business. Based on the analysis which is conducted above, the management will be able to take proper decisions for the business (Jain, Singh and Srivastava 2013). Sensitivity analysis considers all the factors to remain constant; however in some cases this becomes irrelevant.

Conclusion

Thus, from the above analysis, it can be concluded that Booli Enterprise should invest in the project or in other words should accept the project. Booli enterprise shall be manufacturing new model for SSHA. The main reasons due to which the management accepted the project are because the NPV for the project as calculated is positive, the profitability index of the same is shown to be 1.65, payback period is calculated to 2.14 which is less than 5 years and hence favourable. The IRR of the project is shown to be 19.7% that is appropriate.

Recommendation

As per the above analysis, it is suggested that the business shall accept the project. If the manufacturing of the new product for existing SSHA as per the plan of the management generates losses for any other product of the business then the same loss shall be included in the amount of investment. If after inclusion of such loss from other product in the investments results in negative NPV than the project should not be accepted. However, if the result is shown to be positive then the project should be accepted.

Reference

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

Cucchiella, F., D’Adamo, I. and Gastaldi, M., 2015. Financial analysis for investment and policy decisions in the renewable energy sector. Clean Technologies and Environmental Policy, 17(4), pp.887-904.

Jain, N., Singh, S.N. and Srivastava, S.C., 2013. A generalized approach for DG planning and viability analysis under market scenario. IEEE Transactions on Industrial Electronics, 60(11), pp.5075-5085.

Levy, H., 2015. Stochastic dominance: Investment decision making under uncertainty. Springer.

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.

Nguyen, A.T. and Reiter, S., 2015, December. A performance comparison of sensitivity analysis methods for building energy models. In Building Simulation (Vol. 8, No. 6, pp. 651-664). Tsinghua University Press.

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.

Sanchez, D.G., Lacarrière, B., Musy, M. and Bourges, B., 2014. Application of sensitivity analysis in building energy simulations: Combining first-and second-order elementary effects methods. Energy and Buildings, 68, pp.741-750.

Tian, W., 2013. A review of sensitivity analysis methods in building energy analysis. Renewable and Sustainable Energy Reviews, 20, pp.411-419.

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