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. Minding the Analytics Gap case study is a Harvard Business School (HBR) case study written by Sam Ransbotham, David Kiron, Pamela Kirk Prentice. The Minding the Analytics Gap (referred as “Analytics Respondents” from here on) case study provides evaluation & decision scenario in field of Leadership & Managing People. 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.
In an increasingly data-driven business environment, many executives must make critical decisions based on analyses that use data and statistical methods that they do not fully understand. How can executives with limited analytics expertise become adept consumers of analytics under such conditions? This question has become an important management issue as senior executives increasingly recognize the importance of analytics to creating business value. The authors'research -based on a survey of 2,719 managers in organizations from around the world -found that the foremost barrier to creatingbusiness value from analytics is not data management or complex modeling skills. Instead, the number one barrier mentioned by survey respondents involved translating analytics into business actions -in other words, making business decisions based on the results, not producing the results themselves. With more access to useful data, companies are increasingly using sophisticated analytical methods. That, the authors argue, means there's often a gap between an organization's capacity to produce analytical results and its ability to apply them effectively to business issues. Much can be done to make analytics more consumable for managers. At the individual level, data analysts can learn more about the business; in fact, about a third (34%) of the survey respondents reported that their organizations train analytics professionals to understand business issues. Organizations can also systemically improve infrastructure and processes; improved data quality, for example,can make it easier to turn data into competitive advantage. Managers can also take steps to become savvier at understanding analytical results. In fact, managers and executives are working to become more knowledgeable about data and analytics: Many of the survey respondents reported that their organizations develop analytical skills through on-the-job (58%) or formal (23%) training. Almost half the respondents (49%) reported that their organizations train managers to make better use of analytics. Beyond training, other known steps include: identifying trustworthy analytics professionals within the organization, requiring straightforward explanations and asking detailed questions. However, the authors'research indicates that, despite their efforts, managers continue to find it difficult to keep pace with their organization's analysts for two reasons: burgeoning analytics sophistication and competing demands for managerial attention. What's more, when an organization's capacity to produce increasingly sophisticated analytics outpaces managers'abilities to understand, discomfort is created -managers find they must make decisions based on complex analytical insights that they do not yet fully understand. But, despite this discomfort, these managerial decisions must be made. The authors conclude by suggesting five ways that managers can increase their comfort in consuming analytics. This is an MIT Sloan Management Review article.
|Years||Cash Flow||Net Cash Flow||Cumulative
@ 6 %
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. Payback Period
3. Profitability Index
4. Net Present Value
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. Analytics Respondents 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 Analytics Respondents 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 Analytics Respondents 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 Analytics Respondents 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
@ 15 %
(10452087 - 10001270 )
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
@ 20 %
At 20% discount rate the NPV is negative (9480791 - 10001270 ) so ideally we can't select the project if macro and micro factors don't allow financial managers of Analytics Respondents to discount cash flow at lower discount rates such as 15%.
Simplest Approach – If the investment project of Analytics Respondents has a NPV value higher than Zero then finance managers at Analytics Respondents 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 Analytics Respondents, then the stock price of the Analytics Respondents 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 Analytics Respondents 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 –
Understanding of risks involved in the project.
What are the key aspects of the projects that need to be monitored, refined, and retuned for continuous delivery of projected cash flows.
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 can impact the cash flow of the project.
What will be a multi year spillover effect of various taxation regulations.
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.
Sam Ransbotham, David Kiron, Pamela Kirk Prentice (2018), "Minding the Analytics Gap Harvard Business Review Case Study. Published by HBR Publications.
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