Book Review: Portfolio Management For New Products

This is the second in a series of reviews of books on the reference list of the Project Management Institute’s Portfolio Management Professional (PfMP) Credential Examination. The complete reference is:


R.G. Cooper, S.J. Edgett and E.J. Kleinschmidt. Portfolio Management for New Products, 2nd ed. (New York: NY, Basic Books, 2002; 11 chapters, 382 pp.)

The lead author of this book is Dr. Robert Cooper, creator of the Stage-GateTM project management process. The approaches and performance results presented are the result of a three phase study conducted by the authors. Phase I consisted of an in depth review of the portfolio management practices of 35 leading companies. Phase II was a survey of 205 member companies of the Industrial Research Institute, looking at portfolio management methods being used and results achieved. Phase III consisted of case studies of 40 companies that uncovered difficulties in their portfolio management approaches and were taking action to address them. Results are always presented for Top Performers (top 20%), All Companies, and Poor Performers (bottom 20%), facilitating the identification of best practices.

The research underlying this text was conducted in the late 1990s. The problems faced by companies today are the same as back then; it would be interesting to know how and to what extent portfolio management approaches have evolved over the last 15 years at the companies surveyed. In any case, the fact that the Project Management Institute maintains this title on its PfMP reference list ensures its continued relevance.

The authors of this book assume your company has in place a new product strategy and a Stage-Gate project management process. In case not, information is presented on these topics in Chapter 5 (see “Developing a New Product Strategy”) and Appendices A & B (Stage-Gate Methods). Having a stage-gate process is important because it provides a stream of data used for portfolio analysis.

Cooper et al. identify the three broad goals of portfolio management as: maximizing value, achieving balance and ensuring strategic alignment and dedicate a chapter to each objective. Methods used to achieve each of these goals are described below.

Maximizing Portfolio Value
The first objective of most firms studied by the authors, not surprisingly, was maximizing the value of the portfolio against one or more business goals (such as profitability, strategy or risk). A variety of methods were used to achieve this maximization goal, including financial methods and scoring models. The end result of each method is a rank-ordered list of projects, with the highest ranking projects appearing at the top of the list. Projects are typically funded moving down the list until resources run out.

Financial methods presented for prioritizing projects include: (1) Bang for Buck Index – calculated as NPV divided by total resources remaining to be spent on project, (2) Expected Commercial Value (ECV) – factors technical and commercial risk into the valuation estimate and (3) Productivity Index – a variant of the ECV model that maximizes the financial value of the portfolio for a given resource constraint, (4) Options Pricing Theory – recognizes that projects are not an all or nothing investment decision and (5) Dynamic Rank Ordered Lists – a financial method that overcomes the limitation of depending on only a single criterion to rank projects.

While financial methods are popular, the authors want you to know that financial forecasts of a new product’s value, especially those made at the business case stage, are generally wrong. In fact, in the authors’ large survey of practices versus results, financial methods yielded the worst results on just about every portfolio performance metric (the authors make this point over and over). The valuation method the authors recommend in place of financial data is the scoring model. Scoring models use characteristics of new product projects strongly correlated with success as proxies for success and profits. Scoring models used by Celanese (formerly Hoechst), Dupont and a small hi-tech firm, as well as a best practices scoring model developed by the authors, are presented in Chapter 3.


Figure 1. The six factors in the authors’ best practices scoring model. View full size: (See p. 15)

The authors’ best practices scoring model is based on six criteria (Figure 1): Strategic Alignment & Importance, Product & Competitive Advantage, Market Attractiveness, Leverages Core Competencies, Technical Feasibility and Financial Reward vs. Risk. Each criterion is assigned a score of 0 to 10 and the project attractiveness score, used to rank projects, is the sum of the six factor scores adjusted to make the value a percentage out of 100. Each of the six criteria has sub-criteria used to guide discussion and there is the option to score sub-criteria individually.

Achieving Portfolio Balance

The authors’ large sample survey of portfolio practices and outcomes showed that most companies’ new product portfolios are unbalanced. Aside from having too many projects, portfolio balance was the weakest performing element of six metrics considered in the survey. Companies seek to achieve portfolio balance across a variety of parameters including risk/reward, markets or market segments, product categories or product lines, project types and technology or platform types.

The most popular way to display balance in new product portfolios is with charts. Charts are valued for their ability to visually display the balance of projects in the portfolio, something that the rank-ordered lists used to maximize value fail to do. A variety of chart types are used (see Chapter 4), including histograms, bar charts and pie charts, but most popular are bubble diagrams.


Figure 2. Traditional Risk-Reward Bubble Diagram. Circle size = annual resources. View full size:

In their survey, the authors found the most popular bubble diagrams plot risk vs. reward (used by 44% of businesses); used with less frequency are diagrams that look at newness (11%), ease vs. attractiveness (11%), strength vs. attractiveness (11%), cost vs. timing (10%), strategic vs. benefit (9%) and cost vs. benefit (6%).

Variants of risk vs. reward diagrams include: (1) the standard Pearls-Oysters-Bread and Butter-White Elephants four quadrant bubble chart (Figure 2) that plots NPV adjusted for commercial risk vs. probability of technical success (bubble size denotes annual resources, color-not shown-indicates timing and shading denotes product line), based on an SDG model, (2) 3M’s ellipses model that visually portrays NPVs and probability of technical success as a range, (3) Proctor & Gamble’s 3-D risk reward bubble diagram with axes for Time to Launch, NPV range (calculated using a Monte Carlo model) and probability of commercial success (shapes denote degree of technological fit with company) and (4) Arthur D. Little’s four quadrant plot of Reward (here a subjective estimate ranging from “modest” to “excellent” and considering not only financial prospects, but also strategic importance and impact on the company) vs. Probability of Technical and Commercial Success.

Bubble diagrams can also derive their axes from scoring models, such as (1) Specialty Mineral’s plot of value vs. probability of success, (2) Reckitt-Benckiser’s Market/Concept Attractiveness vs. Ease of Implementation and (3) Royal Bank’s portfolio map of Ease of Execution vs. Project Importance.

While bubble charts offer an excellent way of visually displaying balance, they have some limitations. These include: (1) They do not support project ranking, rather they serve as a starting point for discussion, (2) Charts based on financial projections may suffer the same inaccuracies as financial portfolio ranking models, (3) Be cautious of information overload from use of too many charts, (4) While it is easy to identify a portfolio that is obviously and extremely out of balance, it can be difficult to define what the right balance is.

Ensuring Strategic Alignment

Two examples illustrate ways in which a company’s portfolio can fail to align to strategy. In the first case, a mid-sized company defined its strategic objective in its annual report as “growth through industry leadership in product development.” However, on analysis, the company’s R&D spending as a percentage of sales was half that of the industry average. In the second case, a business unit’s averred strategy was to “…achieve rapid growth through aggressive new product development.” However, upon review of the business unit’s breakdown of R&D spending, the great majority of resources were going to maintenance projects, product modifications and extensions, not new products.

To avoid serious disconnects like those described above, the companies studied by the authors used three general approaches to achieve strategic alignment (see Chapter 5): (1) Top-Down Approaches, (2) Bottom-Up Approach and (3) Top-Down, Bottom-Up Approach.



Figure 3. Strategic Buckets Model by Robert G. Cooper and Scott J. Edgett. The strategic-buckets method splits resources into different buckets to ensure that resource allocations mirror strategic priorities. View full size:


Two Top-Down approaches were used, together or separately: The Product Roadmap Approach and the Strategic Buckets Model (Figure 3). The Product Roadmap approach seeks to answer the question: “If this is our strategy, then what projects must or should we do?” by defining the major initiatives or platforms developments that will be undertaken. The Strategic Buckets Model asks the questions: “If this is our strategy, then how should we be spending our development funds? What splits across various markets, technologies or project types should our investment be?” In response, funds are set aside in envelopes or buckets of money destined for different project types. The shortcoming of this approach is that there may be no promising projects available for a bucket selected for funding.

The Bottom-Up Approach selects the best available projects for funding, regardless of market or project type. Strategic criteria built into the project selection process ensure the organization ends up with a portfolio of strategically aligned projects. The shortcoming of this approach is that it may result in an unbalanced portfolio.

The Top-Down, Bottom-Up Approach is the authors’ preferred solution. It begins with Top-Down allocation of funding into Strategic Buckets. It then proceeds from the bottom with review and selection of the best projects. The two sets of decisions are reconciled via multiple iterations.

Other Topics Covered

Other topics covered in this book include:

  • Challenges and unresolved issues of portfolio management
  • Methods for increasing data integrity
  • Strategic Resource Allocation/Project Prioritization–step-by-step guide
  • Recommendations for designing and implementing a portfolio management process


The authors draw six key conclusions from their practices and performance study: (1) Formal portfolio management methods work, (2) There is no one right portfolio management method – so try a hybrid approach, (3) Beware of over reliance on financial methods and models, (4) Look more to strategic approaches as the way to manage your portfolio – businesses that rely on strategic methods outperform the rest, (5) Consider a scoring model as an effective prioritization tool and (6) Bubble diagrams must be a part of your repertoire of portfolio models.

I like this book and recommend it. It will be particularly useful to those new to portfolio management. Chapter 9 presents a step by step walk-through of a strategic portfolio management exercise for a division of a multinational chemical company, providing a practical illustration of a number of the concepts presented in the text. One critique of the book is that it is repetitive, although this may be by design.

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