Introduction

“If you can explain success, then you can predict success” (Cooper et al., 2001, p. 47).

A number of criteria are widely used by companies to forecast the profitability / revenues of a candidate project.

Net Present Value (NPV), discounted Payback period, Internal Rate of Return (IRR), Expected Commercial Value (ECV) are most popular.

Such metrics are useful in 2 distinct processes:

•      Product Go/Kill decisions or gate decisions (intermediary steps in the New Product Development process)
•    Portfolio Reviews

Net Present Value

The goal of NPV is to maximize the total economic value of the portfolio subject to resource constraint. If there is no such constraint the criterion would be which project has positive NPV.

NPV advantages:

·         It considers the time value of money

·         Projects that are years away from launch are penalized

·         Projects that are halfway through development are favored all other things being equal

·         The method considers immediate resources requirements

 NPV drawbacks:

·         The method relies only on financial analysis

·         The method assumes only financial goals

Resource estimates are inaccurate. Project teams have difficulty to make reliable estimates

Expected Commercial Value

ECV=[(PV*Pcs-C)*Pts]-D

Pts: Probability of technical success

Pcs: Probability of Commercial Success

D: development costs

C: commercialization (launch) costs

PV: Net present value of project’s future earnings- cost – development – capital

This method seeks to max the expected value subject to certain budget constraints. ECV overcomes some of the NPV weaknesses:

ECV Advantages:

•     It does not consider sunk costs
•     It recognizes constraint resources and attempts to max the value of the portfolio in light of this constraint
•    It yields the maximum value portfolio
•    It considers risks and probabilities both commercial and technical

ECV Disadvantages:

Probability estimates are, by enlarge, unreliable: “pulling out numbers out of the air”

The method does not look at the balance of the portfolio between high and low risk projects or across markets and technologies.

Scoring Models

Quantitative financial metrics such as NPV and ECV often result in to Harch Go/Kill decisions. Success requires going beyond financial methods. As quantitative metrics are often based on strong assumptions, they need to be complemented with highly reliable qualitative information. Market information is of the utmost importance. Therefore, Scoring Models have been introduced as a way to incorporate such qualitative factors. This enables companies to rate and rank new product projects.

As an example, the following model was introduced by the pharmaceutical company Hoechst in the 1980’s.

The Hoechst Scoring Model

This model takes into consideration 5 factors:

1.       Business Strategy Fit
2.      Strategic Leverage
3.       Probability of Technical Success
4.       Probability of commercial Success
5.        Reward to the company

    The final score is used for 2 purposes:

1.       Go/Kill decisions Gates
2.      Prioritization

Drawbacks:

·         Imaginary precision: “Scoring models try to measure of soft banana with a micro-meter” (Cooper et al., 2001, p. 69).

·         Halo effect: If a project scores high on a criterion, it tends to score high on all of them.

·          Efficiency in allocation of scarce resources: Scoring models fail to ensure that accepted projects will achieve the highest possible score for the resources used.

Limitations of Value Approach

The resulting list of project for any combination of the above methods may be a very unbalanced portfolio. For example, it can lead to too many short-term projects, or it could fail to fit the strategic direction of the company.