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  1. Bringing Objectivity to Market Requirements Locked

    Research | Posted: 2004-09-20

    Since several studies have shown that poor definition and ambiguous specification are the premier cause of development delays, it seems clear that if a company wishes to reduce development time, it should first address this root cause. In this report, David Boger describes how to convert subjective market requirements into objective, quantifiable goals. He presents a brief example from the medical products industry of how metrics can be used to clarify product requirements. Making product requirements measurable, argues Boger, clarifies them for all of the functions involved in product development, while reducing development cycle time. (3 pages)

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  2. Metrics Expert Offers Four Steps to Predictive Process Metrics You Can Use on Monday Morning Locked

    Research | Posted: 2004-09-20

    Metrics expert Wayne Mackey (GM Hughes Electronics, Product Development Consulting, Inc.) offers four steps for creating a metrics program that will predict positive results. "If you can master four things,” writes Mackey, “ you will know more about setting process improvement metrics than 90 percent of the people in your place of business – and you can implement next Monday." Mackey suggests the following steps: define the improvement goal; measure what gets the organization to that goal; align metrics with the appropriate level within the organization; manage the timing of metrics. Mackey presents key questions and action steps that clarify how measurements can lead to predictable improvements. (3 pages)

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  3. The Metrics Dashboard: An Interview with Chris Meyer Locked

    Research | Posted: 2004-09-20

    If you want fast and effective business decisions, those who do the measuring should also do the analysis, and act on that analysis, argues metrics “Dashboard” originator, Chris Meyer. In this interview, Meyer describes his “dashboard” concept as a means of subverting a prevalent trend where measurement is merely a covert form of command and control, that avoids the application of human judgment. Meyer emphasizes that measurements are best used to guide decision-making and should enable the team as much as inform senior management. Since the team is closest to the task, Meyer advocates allowing the team to create its own dashboard. The team then tests its dashboard with senior management for alignment to corporate goals and cross-team learning. In addition to describing the essence of his theory of measurement, Meyer also discusses how an operational mindset hampers innovation. (6 pages)

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  4. Study Identifies Top Product Concept Selection Metrics Locked

    Research | Posted: 2004-09-10

    A study conducted last year by the Center for Innovation in Product Development (CIPD) at MIT, in association with the Laboratory of Machine Design at Helsinki University of Technology (HUT) and participants from industry, identified 26 metrics firms can use for screening and selecting product concepts. The aim was to produce a list of metrics focused specifically on the evaluation of product concepts. The researchers not only created a list of product concept metrics but also prioritized the list to identify the most important questions that need to be answered in selecting winning new products. This brief report contains a table with some of the top metrics identified by the study. (3 pages)

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  5. Portfolio Management: Progress and Opportunities Locked

    Research | Posted: 2004-09-09

    The 2000 R&D Metrics Survey, conducted by Goldense Group, Inc. (GGI) in association with The Management Roundtable, indicated that industry is making progress, albeit somewhat unevenly, in managing R&D investments. In this commentary, metrics expert Brad Goldense summarizes thet state of portfolio management and R&D metrics, and points out where opportunities exist to gain steady and consistent progress. Goldense finds that leading companies are well on their way to systematic product evaluation and selection, product review and portfolio management practices. However, he sees a clear division between a vanguard of R&D leaders and their many followers; the top quartile of R&D companies are as much as 10-30 years ahead of the slowest adopters of modern management science. Based on the survey findings, Goldense cites three pitfalls that teams fall into in their efforts to improve portfolio management and R&D measurement.(3 pages)

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  6. Distinguishing Between Proactive & Predictive Metrics Will Improve Process Maturity Locked

    Research | Posted: 2004-08-31

    In this article, metrics expert Brad Goldense discusses when to apply two different categories of metrics– proactive metrics and predictive metrics– to increase the likelihood of desired outcomes. Goldense points out that the terms “proactive” and “predictive” are often used interchangeably – a usage that is not completely accurate. The author suggests that “proactive metrics” are best applied prior to the Development Approved milestone, while “predictive” metrics are used most effectively after development is approved. Goldense also suggests a process maturity model for metrics based on the premise that “the more variability can be controlled, the more mature the process.” “It follows then,” writes Goldense, “that if the greatest amount of variability is in the early stages of a project, and that variability is supposed to lessen over time, then the earlier that metrics can be reliably applied the more they will enable process maturity.” (5 pages)

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  7. R&D Productivity: Capacity Management Is Paramount Locked

    Research | Posted: 2004-07-01

    In this feature article, Brad Goldense provides a framework for Capacity Management in R&D. He presents a formula that will show,at the highest level, how much the staff is over-extended. Goldense claims that challenges arise at the level of allocating scarce functional resources across projects. Unless there is a consistent process with common milestones, used across all projects for estimating and tracking, it is difficult to attain better estimates for functional disciplines. It is also essential to have common definitions of the functional resource categories used for planning and estimating. Once a company has achieved resource and capacity planning at a function or discipline level, the only practical level of detail that remains is planning at the individual level. Goldense predicts that industry will eventually reach a point where each person in each department will be assessed against an expected and/or standardized productivity rate. (4 pages)

  8. The R&D Effectiveness Index: Performance Metric for Product Development (Part Two of Two) Locked

    Research | Posted: 2004-06-29

    For the second portion of this article, Management Roundtable interviewed Michael McGrath and Mark Deck, of consulting firm Pittiglio Rabin Todd & McGrath, to build a deeper understanding of the application of their R&D Effectiveness Index. The Index is an aggregate measure of the overall success of a company's product development efforts. It serves as an overall metric at a level above individual products and development projects, and provides management with a tool to measure the effectiveness of its product development process. In this interview, McGrath and Deck describe the origins of the Index and outline the ways in which it can be applied to improve R&D performance. (5 pages)

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  9. The R&D Effectiveness Index: Performance Metric for Product Development (Part One of Two) Locked

    Research | Posted: 2004-06-29

    How do you measure your product development effectiveness in the aggregate? Today, with companies spending large sums on development process improvement, a new metric is needed, one that shows what you're getting for your investment. In this article Michael McGrath and Mark Deck, of consulting firm Pittiglio Rabin Todd & McGrath, present The R&D Effectiveness Index. The Index is an aggregate measure of the overall success of a company's product development efforts. It serves as an overall metric at a level above individual products and development projects, and provides management with a tool to measure the effectiveness of its product development process. The R&D Effectiveness Index uses a simple formula to compare profit from new products to investment in new product development. It provides insight into product development process dynamics and how it affects profitability. (5 pages)

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  10. WANTED: Control System for Product Development Locked

    Research | Posted: 2004-06-29

    In this commentary, Don Reinertsen argues that metrics are only one component of an overall control system for product development. Firms look for "good metrics" without a sufficiently deep understanding of the factors they wish to control. Reinertsen claims that very few companies understand why they wish to control processes at all beyond a dogmatic, philosophical position that "variation is bad." Reinertsen argues that it is necessary to understand the drivers of life cycle profits in order to determine what, in the development process, needs to be controlled. The only sound basis for a control system, he maintains, is an economic one. (3 pages)

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