You can have many ideas for new products. How should you decide on which one of them deserves the investment of time, sweat, and money?
Increasingly, managers are turning to the net present value (NPV) analysis when making a go or no-go decision on new product development.
If a company can find a project with a positive NPV and a rate of return that is higher than the project’s cost of capital, then it should pursue the project. If it cannot find such a project, then it must distribute its earnings to the shareholders.
One could argue, however, that while NPV works great for evaluating incremental improvement projects, it is a poor filter for projects in the highly uncertain environment that is characteristic of new product development.
Consider the following example.
You have a new product idea and estimate that it will take a team of five people working for a year to develop a minimum viable version of the product (MVP) at a total cost of $1 million.
Beyond the MVP, there are three possible scenarios. With the probability of 10%, the product can become wildly successful and make the company $50M in present value. There is a 40% chance that the product can achieve moderate success and break even by earning the present value of $0. Finally, there is a 50% chance that the product will flop and lose the present value of $20M.
The NPV of this project can be estimated as
NPV = -$1M + 0.1*$50M – 0.5*$20M = -$6M
Since the NPV is a negative $6M, the company must not undertake the project and can do better by returning $1M to its shareholders. This might very well be the conclusion of an investment committee reviewing five-year projections for the project.
At the same time, there is another way of valuing the same project. Based on the success of the MVP, the company has the option of abandoning the project after one year. The new NPV can then be calculated as
NPV = -$1M + 0.1*$50M = $4M
This NPV is positive, and the company must invest in the development of the MVP.
Essentially, the $1 million that the company is spending now is the price of the option to invest later. In our example, the company must be willing to spend up to $5M to purchase this option, that is, to develop the MVP.
In general, the pricing of options is governed by the Black-Scholes model, where the price of an option is proportional to the volatility of the underlying asset. In other words, the riskier the asset, the more valuable is the option of buying or selling this asset at a predetermined price.
This has an important implication for new product development. Between any two MVPs, you must choose the one that is offering not only the higher return but also the greater uncertainty. To look at it another way, an MVP with an obvious outcome has little value to a company.
In summary, the elegant math of real options and options pricing is telling us that corporate innovators can deliver the maximum value to their companies by targeting riskier projects that offer substantial upside if successful but can also be readily abandoned in case of failure.
In practical terms, this means partnering with startups, forming two-pizza teams, adopting an agile product development methodology, shooting for the stars, embracing risk, failing fast, and, no matter what, iterating.