Introduction to Net Present Value (NPV) - What is Net Present Value (NPV) ? How it impacts financial decisions regarding project management?
At Oak Spring University, we provide corporate level professional Net Present Value (NPV) case study solution. Thriving in a Big Data World case study is a Harvard Business School (HBR) case study written by Alden M. Hayashi. The Thriving in a Big Data World (referred as “Data Cukier” from here on) case study provides evaluation & decision scenario in field of Strategy & Execution. It also touches upon business topics such as - Value proposition, .
The net present value (NPV) of an investment proposal is the present value of the proposal’s net cash flows less the proposal’s initial cash outflow. If a project’s NPV is greater than or equal to zero, the project should be accepted.
This is an MIT Sloan Management Review article. The author reviews three recent books: Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-SchA?nberger and Kenneth Cukier; Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel; and Keeping Up with the Quants: Your Guide to Understanding and Using Analytics by Thomas H. Davenport and Jinho Kim. The first two books primarily focus on the power of big data and quantitative analytics, and the third advises how companies can tap into that power.Together, the combination of description and advice provide a good primer for executives seeking a better understanding of this emerging era of sophisticated number-crunching. According to Siegel's estimate, we are adding 2.5 quintillion bytes of data every single day. Words have become data; the physical states of our machinery have become data; our physical locations have become data; and even our interactions with each other have become data. "Data can frequently be collected passively, without much effort or even awareness on the part of those being recorded. And because the cost of storage has fallen so much, it is easier to justify keeping data than discarding it,"observe Mayer-SchA?nberger and Cukier. Indeed, we are awash in information, but what does it all mean? In their book, Mayer-SchA?nberger and Cukier explain three new imperatives: 1. Use all the data, not just a sample. In the past, businesses did not have the economical means to capture, store and analyze all the data from their operations, so they had to settle for a sample of it. But now a company like Amazon can economically capture and store data from every single customer transaction. 2. Accept messiness. Inaccuracies in measurements are less harmful than they once were because they can often be smoothed over by the sheer quantity of data. In the authors'words, "more trumps better." 3. Embrace correlation. For many purposes, correlation is sufficient and people don't need to know causality. Quantifying the likelihood that a particular person will do something -whether it is defaulting on a loan, upgrading to a higher level of cable service or seeking another job -is at the heart of Siegel's Predictive Analytics. The author describes how quantitative techniques can be deployed to find valuable patterns in data, enabling companies to predict the likely behavior of customers, employees and others. Even a modest increase in the accuracy of predictions can often result in substantial savings. Executives must go far beyond the "gee whiz"fascination with big data and quantitative techniques to learn how their businesses can profit best from this new era of computational sophistication. For that journey, Keeping Up with the Quants is a basic guide. Authors Davenport and Kim provide a logical approach for helping executives think more like quantitative analysts.
Years | Cash Flow | Net Cash Flow | Cumulative Cash Flow |
Discount Rate @ 6 % |
Discounted Cash Flows |
---|---|---|---|---|---|
Year 0 | (10000883) | -10000883 | - | - | |
Year 1 | 3446206 | -6554677 | 3446206 | 0.9434 | 3251138 |
Year 2 | 3954667 | -2600010 | 7400873 | 0.89 | 3519640 |
Year 3 | 3944625 | 1344615 | 11345498 | 0.8396 | 3311983 |
Year 4 | 3231511 | 4576126 | 14577009 | 0.7921 | 2559659 |
TOTAL | 14577009 | 12642420 |
In isolation the NPV number doesn't mean much but put in right context then it is one of the best method to evaluate project returns. In this article we will cover -
Capital Budgeting Approaches
There are four types of capital budgeting techniques that are widely used in the corporate world –
1. Payback Period
2. Net Present Value
3. Profitability Index
4. Internal Rate of Return
Apart from the Payback period method which is an additive method, rest of the methods are based on
Discounted Cash Flow
technique. Even though cash flow can be calculated based on the nature of the project, for the simplicity of the article we are assuming that all the expected cash flows are realized at the end of the year.
Discounted Cash Flow approaches provide a more objective basis for evaluating and selecting investment projects. They take into consideration both –
1. Magnitude of both incoming and outgoing cash flows – Projects can be capital intensive, time intensive, or both. Data Cukier shareholders have preference for diversified projects investment rather than prospective high income from a single capital intensive project.
2. Timing of the expected cash flows – stockholders of Data Cukier have higher preference for cash returns over 4-5 years rather than 10-15 years given the nature of the volatility in the industry.
NPV = Net Cash In Flowt1 / (1+r)t1 + Net Cash In Flowt2 / (1+r)t2 + … Net Cash In Flowtn / (1+r)tn
Less Net Cash Out Flowt0 / (1+r)t0
Where t = time period, in this case year 1, year 2 and so on.
r = discount rate or return that could be earned using other safe proposition such as fixed deposit or treasury bond rate.
Net Cash In Flow – What the firm will get each year.
Net Cash Out Flow – What the firm needs to invest initially in the project.
Step 1 – Understand the nature of the project and calculate cash flow for each year.
Step 2 – Discount those cash flow based on the discount rate.
Step 3 – Add all the discounted cash flow.
Step 4 – Selection of the project
In our daily workplace we often come across people and colleagues who are just focused on their core competency and targets they have to deliver. For example marketing managers at Data Cukier often design programs whose objective is to drive brand awareness and customer reach. But how that 30 point increase in brand awareness or 10 point increase in customer touch points will result into shareholders’ value is not specified.
To overcome such scenarios managers at Data Cukier needs to not only know the financial aspect of project management but also needs to have tools to integrate them into part of the project development and monitoring plan.
After working through various assumptions we reached a conclusion that risk is far higher than 6%. In a reasonably stable industry with weak competition - 15% discount rate can be a good benchmark.
Years | Cash Flow | Net Cash Flow | Cumulative Cash Flow |
Discount Rate @ 15 % |
Discounted Cash Flows |
---|---|---|---|---|---|
Year 0 | (10000883) | -10000883 | - | - | |
Year 1 | 3446206 | -6554677 | 3446206 | 0.8696 | 2996701 |
Year 2 | 3954667 | -2600010 | 7400873 | 0.7561 | 2990296 |
Year 3 | 3944625 | 1344615 | 11345498 | 0.6575 | 2593655 |
Year 4 | 3231511 | 4576126 | 14577009 | 0.5718 | 1847627 |
TOTAL | 10428279 |
(10428279 - 10000883 )
If the risk component is high in the industry then we should go for a higher hurdle rate / discount rate of 20%.
Years | Cash Flow | Net Cash Flow | Cumulative Cash Flow |
Discount Rate @ 20 % |
Discounted Cash Flows |
---|---|---|---|---|---|
Year 0 | (10000883) | -10000883 | - | - | |
Year 1 | 3446206 | -6554677 | 3446206 | 0.8333 | 2871838 |
Year 2 | 3954667 | -2600010 | 7400873 | 0.6944 | 2746297 |
Year 3 | 3944625 | 1344615 | 11345498 | 0.5787 | 2282769 |
Year 4 | 3231511 | 4576126 | 14577009 | 0.4823 | 1558406 |
TOTAL | 9459310 |
At 20% discount rate the NPV is negative (9459310 - 10000883 ) so ideally we can't select the project if macro and micro factors don't allow financial managers of Data Cukier to discount cash flow at lower discount rates such as 15%.
Simplest Approach – If the investment project of Data Cukier has a NPV value higher than Zero then finance managers at Data Cukier can ACCEPT the project, otherwise they can reject the project. This means that project will deliver higher returns over the period of time than any alternate investment strategy.
In theory if the required rate of return or discount rate is chosen correctly by finance managers at Data Cukier, then the stock price of the Data Cukier should change by same amount of the NPV. In real world we know that share price also reflects various other factors that can be related to both macro and micro environment.
In the same vein – accepting the project with zero NPV should result in stagnant share price. Finance managers use discount rates as a measure of risk components in the project execution process.
Project selection is often a far more complex decision than just choosing it based on the NPV number. Finance managers at Data Cukier should conduct a sensitivity analysis to better understand not only the inherent risk of the projects but also how those risks can be either factored in or mitigated during the project execution. Sensitivity analysis helps in –
What are the uncertainties surrounding the project Initial Cash Outlay (ICO’s). ICO’s often have several different components such as land, machinery, building, and other equipment.
What are the key aspects of the projects that need to be monitored, refined, and retuned for continuous delivery of projected cash flows.
What can impact the cash flow of the project.
What will be a multi year spillover effect of various taxation regulations.
Understanding of risks involved in the project.
Projects are assumed to be Mutually Exclusive – This is seldom the came in modern day giant organizations where projects are often inter-related and rejecting a project solely based on NPV can result in sunk cost from a related project.
Independent projects have independent cash flows – As explained in the marketing project – though the project may look independent but in reality it is not as the brand awareness project can be closely associated with the spending on sales promotions and product specific advertising.
Alden M. Hayashi (2018), "Thriving in a Big Data World Harvard Business Review Case Study. Published by HBR Publications.
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