Acc211 Booli Enterprise Manufacturing Of Assessment Answers
QUESTION: |
High Distinction 5 |
Distinction 4 |
Credit 3.5 |
Pass 2.5 -3 |
Needs more work < 2.5 |
1. Calculate Payback (3 marks) 2. Calculate PI (1 mark) 3. Calculate IRR (1 mark) [Total: 5 marks] | |||||
High Distinction 5 |
Distinction 4 |
Credit 3.5 |
Pass 2.5 -3 |
Needs more work < 2.5 | |
4. Calculate NPV [Total: 5 marks] |
NPV correct within: +/- 5% |
NPV correct within: +/- 10% |
NPV correct within: +/- 20% |
NPV correct within: +/- 30% |
NPV not correct within +/- 31% + |
High Distinction 14 + |
Distinction 12 - 14 |
Credit 10 - 12 |
Pass 7.5 – 8 |
Needs more work <7.5 | |
5. How sensitive is the NPV to changes in price (500 - 700 words). Explain: • NPV volatility in relation to change in price • Demonstration & explanation of forecasting risk • Implications for how project is managed [Total: 15 marks] |
- Comprehensive use of spreadsheet modelling - Strong, logical analysis; high quality of evidence that supports convincing and coherent case |
- Appropriate use of spreadsheet models - Coherent, logical analysis; good quality and quantity of evidence that supports persuasive case |
- Some use of spreadsheet models - Logical analysis; good quality and quantity of evidence that supports a solid case |
- Limited use of spreadsheets -Mostly logical analysis; adequate quality and quantity of evidence that supports a simplistic case |
- Inadequate use of spreadsheets - Inconsistent, illogical or incoherent argument; poor quality and/or quantity of evidence |
High Distinction 14 + |
Distinction 12 - 14 |
Credit 10 - 12 |
Pass 7.5 – 8 |
Needs more work <7.5 | |
6. How sensitive is the NPV to changes in qty sold (500 - 700 words). Explain: • NPV volatility in relation to change in qty sold • Demonstration & explanation of forecasting risk • Implications for how project is managed [Total: 15 marks] | |||||
High Distinction 9-10 |
Distinction 8 |
Credit 7 |
Pass 5-6 |
Needs more work <5 | |
In reference to method 1-4: 7. Explain why project is/is not acceptable, using an analysis of capital budgeting models: [Total: 10 marks] |
Clear and incisive; developed understanding of key capital budgeting decision criteria. |
Competent analysis; solid understanding of key capital budgeting decision criteria. |
Surface level analysis; some understanding of key capital budgeting decision criteria but with significant gaps. |
Very limited analysis; little understanding of key capital budgeting decision criteria. |
Insufficient analysis in most areas. |
High Distinction 9-10 |
Distinction 8 |
Credit 7 |
Pass 5-6 |
Needs more work <5 | |
8. Suppose Booli loses sales on other models because of the introduction of the new SSHA. How would this affect your analysis? [Total: 10 marks] |
Original, clear and incisive analysis |
Competent analysis of relevant information |
Surface level analysis of relevant information |
Very limited analysis of relevant information |
Insufficient analysis in most areas. |
High Distinction 9+ |
Distinction 8 |
Credit 6-7 |
Pass 5 |
Needs more work < 5 | |
Overall presentation: - spelling; syntax; grammar [Total: 10 marks] |
-exceptionally high standard (error free) |
- high standard (minority of errors) |
-good standard (a few errors) |
-satisfactory standard (> a few errors) |
-unsatisfactory standard (numerous errors) |
Report format [Total: 10 marks] |
Fully Compliant 9+ |
Mostly Compliant 8 |
Compliant 6-7 |
Partially Compliant 5 |
Not Compliant <5 |
Answer:
Booli Enterprise is an Australian based company located in Victoria and the company is engaged in the manufacturing of electronic goods. Major revenue generating product of the company is SSHA (smart speaker and home assistant). At present the company is selling one model for SSHA and the sales from the model are excellent. However, technological changes and limited features of the existing model the company is planning to launch new SSHA with advanced features. The main objective of this report is to analyse the investment and profitability for the new SSHA model. Techniques that will be used for analysing the project are net present value, profitability index, discounted payback period and internal rate of return. The report will also perform the analysis the sensitivity of selling price and selling quantity on NPV of the project (Brooks 2015).
Answer 1 – Non-discounted payback period
Payback period measures the time required for covering up the amount of initial investment for any project and the point after which the project will start earning profit. However, the payback period is just concerned about the time required for covering up the initial investment amount and does not give any importance on the project’s capability to earn profit beyond the payback period (Pasqual, Padilla and Jadotte 2013).
Non-discounted payback period for the project –
Year |
Cash inflow |
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.
Answer 2 – profitability index
PI is the investment analysis tool that states whether the project shall be rejected or accepted. It takes into consideration the time value of money (Leung et al. 2014). The formula used for computing the PI is as follows –
PI = PV of future cash flows / Initial investment
PI = $ 77,573,881.43 / 47,025,000 = 1.65
Therefore the profitability index of the project is 1.65.
Answer 3 – internal rate of return
IRR is used under capital budgeting for projecting the expected profitability of any project (Gallo 2014). It is a discount rate at which the net present value of the future cash flows is equal to zero. IRR of the project for producing new SSHA model is 19.77%.
Answer 4 – net present value
NPV is the expected changes in the wealth of the investor taking into consideration the time value factor of money. It is the difference between the net cash inflows from the project and the initial investment required for the project. This method of analysing the project is considered as most appropriate as it considers the time value of money through using the discount rate. The NPV of the project for producing New SSHA model is $ 30,548,881.43 (Leyman and Vanhoucke 2016).
Answer 5 – Sensitivity analysis for price change
Sensitivity analysis is used to measure the changes in the expected variables and its impact on the decision making procedure. While the sensitivity analysis is carried out importance are given on the unfavourable circumstances. The most expected factors taken into consideration in this project are the selling quantity and the selling price of the new SSHA model. Impact of changes of these variables will be measured with respect to the net present value of the project (DeFusco et al. 2015). The process of sensitivity analysis is carried out as follows –
- In the 1st step the base output and base input for the project is recognized. In the given scenario the base output is the NPV and the base input is selling price. Keeping other factors like selling quantity, discount rate and initial investment constant, the sensitivity of NPV with the changes in selling prices will be measured.
- Output value changes with the input value changes is computed
- Percentage change in output with percentage change in input is found out
- After performing the above steps the sensitivity of the output with regard to the input is found out and the sensitivity is expressed in percentage form (McAuliffe 2015).
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 |
1310 |
$ 184,412,844.33 |
30 |
$ 7,409,179.59 |
Answer 6 - Sensitivity analysis for price change
Various factors that lead to performing the sensitivity analysis are as follows –
- Most likely variables that have maximum impact on the decision making procedures can be recognized through the sensitivity analysis
- It assists in taking the corrective actions or appropriate decisions after recognising the impact of changes in the variables
While the sensitivity analysis is carried out with regard to the changes in the selling quantity of the product and its impact on the project’s NPV, the output here is the NPV and the input here is the selling quantity (Iooss and Lemaître 2015). In this part, the sensitivity analysis will be carried out for changes in the selling quantity while keeping the other factors like selling price, discount rate and initial investment constant.
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 |
Sensitivity analysis helps in taking appropriate decisions regarding the input and output variables as it gives the insights regarding how the changes in input has it impact on the output. Based on the result the analysts and the management can take appropriate decisions (Baucells and Borgonovo 2013). However, sometimes the sensitivity analysis seems ambiguous as the pessimistic level and optimistic level is depended on the user’s own approach. Further, it changes only one variable at a time keeping other variables constant. However, in practical situation it may not be possible always (Levy 2015).
Answer 7 – Conclusion
It can be concluded from the above analysis that the New SSHA model shall be produced by Booli Enterprise. The reason behind the acceptability of the project is that the NPV of the project is $ 30,548,881.41, payback period is less than the projects useful life that is 2.14 years, IRR of the project is higher than the required rate of return that is 19.77%.
Answer 8 – Recommendation
If it is found that producing of New model for SSHA will be made in exchange of loss from other products, while calculating the NPV for new SSHA the amount of loss shall be included in the initial investment. If after including the loss the new SSHA project’s NPV comes positive then the project shall be accepted.
Reference
Baucells, M. and Borgonovo, E., 2013. Invariant probabilistic sensitivity analysis. Management Science, 59(11), pp.2536-2549.
Brooks, R., 2015. Financial management: core concepts. Pearson.
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.
DeFusco, R.A., McLeavey, D.W., Pinto, J.E., Anson, M.J. and Runkle, D.E., 2015. Quantitative investment analysis. John Wiley & Sons.
Gorshkov, A.S., Rymkevich, P.P., Nemova, D.V. and Vatin, N.I., 2014. Method of calculating the payback period of investment for renovation of building facades. Stroitel'stvo Unikal'nyh Zdanij i Sooruzenij, (2), p.82.
Harrison, F. and Lock, D., 2017. Advanced project management: a structured approach. Routledge.
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.
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.
Ross, S.A., Bianchi, R., Christensen, M., Drew, M., Westerfield, R. and Jordan, B.D., 2014. Fundamentals of Corporate Finance: Introduction to corporate finance Chapter: 2 Financial statements, taxes and cash flow PART 2 Chapter: 3 Working with financial statements Chapter: 4 Long-term financial planning and corporate growth PART 3 Chapter: 5 First principles of valuation: TVM Chapter: 6 Valuing shares and bonds PART 4 Chapter: 7 Net present value and other investment criteria Chapter: 8 Making capital investment decisions Chapter: 9 Project analysis and evaluation PART 5 Chapter: 10 Lessons .... McGraw-Hill Education (Australia).
Song, Z., Li, Z., Wei, M., Lai, F. and Bai, B., 2014. Sensitivity analysis of water-alternating-CO2 flooding for enhanced oil recovery in high water cut oil reservoirs. Computers & Fluids, 99, pp.93-103.
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