Why Big Data Isn't Enough Net Present Value (NPV) / MBA Resources

Introduction to Net Present Value (NPV) - What is Net Present Value (NPV) ? How it impacts financial decisions regarding project management?

NPV solution for Why Big Data Isn't Enough case study

At Oak Spring University, we provide corporate level professional Net Present Value (NPV) case study solution. Why Big Data Isn't Enough case study is a Harvard Business School (HBR) case study written by Sen Chai, Willy Shih. The Why Big Data Isn't Enough (referred as “Data Scientific” 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.

NPV = Present Value of Future Cash Flows LESS Project’s Initial Investment

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Case Description of Why Big Data Isn't Enough Case Study

This is an MIT Sloan Management Review Article. As "big data" becomes increasingly integrated into many aspects of our lives, we are hearing more calls for revolutionary changes in how researchers work. To save time in understanding the behavior of complex systems or in predicting outcomes, some analysts say it should now be possible to let the data "tell the story" rather than having to develop a hypothesis and go through painstaking steps to prove it. The success of companies such as Google Inc. and Facebook Inc., which have transformed the advertising and social media worlds by applying data mining and mathematics, has led many to believe that traditional methodologies based on models and theories may no longer be necessary. Among young professionals (and many MBA students), there is almost a blind faith that sophisticated algorithms can be used to explore huge databases and find interesting relationships independent of any theories or prior beliefs. The assumption is: The bigger the data, the more powerful the findings. As appealing as this viewpoint may be, authors Sen Chai and Willy Shih think it's misguided - and potentially risky for businesses that involve scientific research or technological innovation. For example, the data might appear to support a new drug design or a new scientific approach when there isn't actually a causal relationship. Although the authors acknowledge that data mining has enabled tremendous advances in business intelligence and in the understanding of consumer behavior - think of how Amazon.com Inc. figures out what you might want to buy, or how content recommendation engines such as those used by Netflix Inc. work - applying this approach to technical disciplines, they argue, is different. The authors studied several fields where massive amounts of data are available and collected: drug discovery and pharmaceutical research; genomics and species improvement; weather forecasting; the design of complex products like gas turbines; and speech recognition. In each setting, they asked a series of questions, including the following: How do data-driven research approaches fit with traditional research methods? In what ways could data-driven research extend the current understanding of scientific and engineering problems? And what cautions did managers need to exercise about the limitations and the proper use of statistical inference?

Case Authors : Sen Chai, Willy Shih

Topic : Leadership & Managing People

Related Areas :

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Calculating Net Present Value (NPV) at 6% for Why Big Data Isn't Enough Case Study

Years	Cash Flow	Net Cash Flow	Cumulative     Cash Flow	Discount Rate @ 6 %	Discounted Cash Flows
Year 0	(10021448)	-10021448	-	-
Year 1	3452263	-6569185	3452263	0.9434	3256852
Year 2	3959398	-2609787	7411661	0.89	3523850
Year 3	3949267	1339480	11360928	0.8396	3315881
Year 4	3222769	4562249	14583697	0.7921	2552735
TOTAL			14583697		12649318

The Net Present Value at 6% discount rate is 2627870

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 -

Different methods of capital budgeting

What is NPV & Formula of NPV,
How it is calculated,
How to use NPV number for project evaluation, and
Scenario Planning given risks and management priorities.

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Capital Budgeting Approaches

Methods of Capital Budgeting

There are four types of capital budgeting techniques that are widely used in the corporate world –

1. Net Present Value
2. Profitability Index
3. Payback Period
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 Scientific 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 Scientific have higher preference for cash returns over 4-5 years rather than 10-15 years given the nature of the volatility in the industry.

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Formula and Steps to Calculate Net Present Value (NPV) of Why Big Data Isn't Enough

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

Why Leadership & Managing People Managers need to know Financial Tools such as Net Present Value (NPV)?

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 Scientific 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 Scientific 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.

Calculating Net Present Value (NPV) at 15%

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	(10021448)	-10021448	-	-
Year 1	3452263	-6569185	3452263	0.8696	3001968
Year 2	3959398	-2609787	7411661	0.7561	2993874
Year 3	3949267	1339480	11360928	0.6575	2596707
Year 4	3222769	4562249	14583697	0.5718	1842629
TOTAL					10435177

The Net NPV after 4 years is 413729

(10435177 - 10021448 )

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Calculating Net Present Value (NPV) at 20%

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	(10021448)	-10021448	-	-
Year 1	3452263	-6569185	3452263	0.8333	2876886
Year 2	3959398	-2609787	7411661	0.6944	2749582
Year 3	3949267	1339480	11360928	0.5787	2285455
Year 4	3222769	4562249	14583697	0.4823	1554190
TOTAL					9466114

The Net NPV after 4 years is -555334

At 20% discount rate the NPV is negative (9466114 - 10021448 ) so ideally we can't select the project if macro and micro factors don't allow financial managers of Data Scientific to discount cash flow at lower discount rates such as 15%.

Acceptance Criteria of a Project based on NPV

Simplest Approach – If the investment project of Data Scientific has a NPV value higher than Zero then finance managers at Data Scientific 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 Scientific, then the stock price of the Data Scientific 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.

Sensitivity Analysis

Project selection is often a far more complex decision than just choosing it based on the NPV number. Finance managers at Data Scientific 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 will be a multi year spillover effect of various taxation regulations.

What can impact the cash flow of the project.

Understanding of risks involved in the project.

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.

Some of the assumptions while using the Discounted Cash Flow Methods –

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.

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Negotiation Strategy of Why Big Data Isn't Enough

References & Further Readings

Sen Chai, Willy Shih (2018), "Why Big Data Isn't Enough Harvard Business Review Case Study. Published by HBR Publications.