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. How Big Data Is Different case study is a Harvard Business School (HBR) case study written by Thomas H. Davenport, Paul Barth, Randy Bean. The How Big Data Is Different (referred as “Data Organizations” from here on) case study provides evaluation & decision scenario in field of Innovation & Entrepreneurship. It also touches upon business topics such as - Value proposition, IT.
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. Many people in the information technology world believe that "big data"will give companies new capabilities and value. But companies have been dealing with an exponentially increasing amount of data, and much of it in forms that are impossible to manage by traditional analytics. "Big data"includes information such as call center voice data, social media content and video entertainment, as well as clickstream data from the web. The authors posit that organizations that are learning to take advantage of big data are beginning to understand their business environments at a more granular level, are creating new products and services, and are responding more quickly to change as it occurs. These companies stand apart from those with traditional data analysis environments in three critical ways. First, rather than looking at data to assess what happened in the past, these organizations consider data in terms of flows and processes, and make decisions and take actions quickly. In addition, organizations already involved with big data are taking a lead on hiring -and training -data scientists and product and process developers as opposed to data analysts. And finally, advanced organizations are moving analytics from IT into their core business and operational functions. As big data evolves, a new information ecosystem is also evolving, a network that is continuously sharing information, optimizing decisions, communicating results and generating new insights for businesses.
| Years | Cash Flow | Net Cash Flow | Cumulative Cash Flow |
Discount Rate @ 6 % |
Discounted Cash Flows |
|---|---|---|---|---|---|
| Year 0 | (10017916) | -10017916 | - | - | |
| Year 1 | 3448343 | -6569573 | 3448343 | 0.9434 | 3253154 |
| Year 2 | 3963653 | -2605920 | 7411996 | 0.89 | 3527637 |
| Year 3 | 3952859 | 1346939 | 11364855 | 0.8396 | 3318897 |
| Year 4 | 3247843 | 4594782 | 14612698 | 0.7921 | 2572596 |
| TOTAL | 14612698 | 12672283 |
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. Internal Rate of Return
2. Profitability Index
3. Net Present Value
4. Payback Period
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 Organizations 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 Organizations 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 Organizations 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 Organizations 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 | (10017916) | -10017916 | - | - | |
| Year 1 | 3448343 | -6569573 | 3448343 | 0.8696 | 2998559 |
| Year 2 | 3963653 | -2605920 | 7411996 | 0.7561 | 2997091 |
| Year 3 | 3952859 | 1346939 | 11364855 | 0.6575 | 2599069 |
| Year 4 | 3247843 | 4594782 | 14612698 | 0.5718 | 1856965 |
| TOTAL | 10451684 |
(10451684 - 10017916 )
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 | (10017916) | -10017916 | - | - | |
| Year 1 | 3448343 | -6569573 | 3448343 | 0.8333 | 2873619 |
| Year 2 | 3963653 | -2605920 | 7411996 | 0.6944 | 2752537 |
| Year 3 | 3952859 | 1346939 | 11364855 | 0.5787 | 2287534 |
| Year 4 | 3247843 | 4594782 | 14612698 | 0.4823 | 1566282 |
| TOTAL | 9479972 |
At 20% discount rate the NPV is negative (9479972 - 10017916 ) so ideally we can't select the project if macro and micro factors don't allow financial managers of Data Organizations to discount cash flow at lower discount rates such as 15%.
Simplest Approach – If the investment project of Data Organizations has a NPV value higher than Zero then finance managers at Data Organizations 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 Organizations, then the stock price of the Data Organizations 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 Organizations 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 will be a multi year spillover effect of various taxation regulations.
Understanding of risks involved in the project.
What can impact the cash flow of 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.
Thomas H. Davenport, Paul Barth, Randy Bean (2018), "How Big Data Is Different Harvard Business Review Case Study. Published by HBR Publications.
Feel free to connect with us if you need business research.
You can download Excel Template of Case Study Solution & Analysis of How Big Data Is Different
Capital Goods , Constr. - Supplies & Fixtures
Technology , Software & Programming
Basic Materials , Chemical Manufacturing
Financial , Misc. Financial Services
Services , Retail (Specialty)
Services , Real Estate Operations
Technology , Computer Services
Services , Recreational Activities
Technology , Electronic Instr. & Controls
Basic Materials , Gold & Silver
Financial , Misc. Financial Services
