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  1. Choosing the Right Product Lifecycle Automation Software: MS2 Thrives in Rigorous Selection Process Locked

    Research | Posted: 2004-11-11

    In recent years, product developers have seen a wide array of new software tools. A lack of clear differentiation in some areas of the software industry has tended to mask a genuine need – software solutions that truly enable product developers to do their jobs better while helping managers make more effective portfolio management decisions. For Lucent, the need to optimize and accelerate product development pointed toward a Product Lifecycle Automation (PLA) solution. This report describes the steps Lucent took to rigorously identify its lifecycle management software requirements, while incorporating the wider organization into the selection process. Lucent created a robust set of criteria to ensure that the PLA product would both meet the requirements and become an integral part of day-to-day product development operations. After undergoing a rigorous selection process, software vendor MS2 emerged as the preferred PLA solution. (5 pages)

  2. Don't Ask, Don't Tell Locked

    Research | Posted: 2004-11-10

    In this commentary, Don Reinertsen suggests that checkpoint reviews rarely do what they are designed to do – ensure that projects are on track and ready to progress to the next phase. Their actual purpose, says Reinertsen, is to reinforce the belief that management is in control. Reinertsen’s surveys of product developers suggest that at least 75 percent of the companies that claim to work in one phase at a time actually permit out-of-phase work. Work moves forward without formal approval because, when time-to-market is valuable, the benefit of overlapping phases far exceeds the cost. Reinertsen argues that the ritual of checkpoint reviews can be dangerous when actual behavior in the organization differs from its rules, causing wasted energy that saps initiative. Any distortion of reality is potentially dysfunctional. If we attribute product development success to the wrong cause, says Reinertsen, we may optimize the wrong thing. (3 pages)

  3. Metrics for Aligning Strategy, R&D and the Factory Locked

    Research | Posted: 2004-09-21

    Metrics expert, Brad Goldense, outlines two metrics that link Strategy, R&D and the Factory. The first is the 3M metric: "Current Year Sales/Profit Due To Products Released In The Prior N Years." The other is "Current Year Active Products Due To Products Released In The Prior N Years," the Factory version of 3M’s metric, which uses the same logic and is applied in the same way. It calculates the amount of new product in the "operations portfolio" versus the "sales/profits portfolio." If there is alignment between strategy, R&D and Factory capacity, these metrics will also align. Goldense provides real data from a pressure and flow instruments company and an Integrated Circuits company to show the alignment between Business Strategy and R&D and the capacity and resources of the Factory. Goldense concludes that two simple metrics can drive the alignment of these three processes, to optimize revenue and profit-producing capacity. (3 pages)

  4. Platforms and Derivatives: Shooting for the Moon Locked

    Research | Posted: 2004-09-19

    In this commentary, Don Reinertsen argues that there is a subtle trap in the distinction between “platform” and “derivative” projects. He contends that a more powerful way to think of projects is in terms of the magnitude of innovation that we undertake in a particular product. A good portfolio will consist of a mix of large innovations and small ones. Importantly, the large innovations can either precede or follow the small ones. This means that what we call a “derivative” product could actually be introduced before the “platform” upon which it is “based.” Reinertsen provides hypothetical examples from the automotive and software industries to illustrate why sometimes it is more valuable to precede a big innovation with a series of small ones. (3 pages)

  5. RD&E Study Indicates Resource and Capacity Management Practices are Improving Locked

    Research | Posted: 2004-09-19

    In this commentary, metrics expert Brad Goldense presents data from a study of Capacity and Resource Management practices. Goldense’s research distinguished between companies that use a single step process and those that have a two-or-more step process for selecting the concepts that move into the product pipeline. He compares the percentage of proposed projects that are approved at companies that have “one-step” vs. “two-or-more-step” processes. Goldense shows, using two different data analyses, that companies using a one-step process load a greater number of projects into the pipeline than do companies with two or more steps. Based on his research and experience, Goldense’s makes a case that multi-step selection processes are not only improving resource and capacity management practices but are also leading to reduced variability in the outcomes of specific project/product investments. (4 pages)

  6. Roundtable Discussion Notes: Balancing Portfolio Demands and Dynamic Resource Allocation Locked

    Research | Posted: 2004-09-19

    A brief, bullet-level summary of breakout sessions from The Management Roundtable’s “Improving R&D Productivity” conference, March 29-31, 2004, in Atlanta, GA. Practitioners brainstormed on topics related to pipeline and portfolio management. These outlines provide many quick ideas and best practices on the topics of balancing portfolio demands with available resources as well as dynamic resource allocation. Participants discussed such issues as how to assess and effectively manage resource capacity (are tools necessary?), how to get capacity aligned with current priorities, and how to allocate people hours and skill sets to projects. (5 pages)

  7. Using Metrics to Drive Change: The Evolution of R&D Metrics at National Semiconductor Locked

    Research | Posted: 2004-09-19

    National Semiconductor provides a textbook case of how R&D metrics can evolve – from the simplest cost-tracking measurements to driving a relatively sophisticated “learning organization.” National’s experience shows how metrics and process improvement can work together to help guide an organization, step-by-step, from one level of process maturity to another. Along the way, National learned a great deal about how metrics can drive behavioral change; how to gain acceptance at both the senior management and engineering team level; how National targeted portfolio management; and how an emphasis on learning can accelerate improvement activities. (8 pages)

  8. Study Identifies Top Product Concept Selection Metrics Locked

    Research | Posted: 2004-09-19

    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)

  9. Improving NPD Execution: Resource Capacity versus Demand Locked

    Research | Posted: 2004-09-17

    Emery Powell, NPD Manager, Texas Instruments A primary cause of time to market delays for new product development(NPD) is inadequate management ofresource capacity versus the demand, particularly with respect to critical path tasks on a project's schedule. The typical response is to rapidly feed new product opportunities into the pipeline. The expectation is: More IN = More OUT.Yet, exceeding throughput capacity all too often leads to a clogged pipeline. So howcan we manage NPD capacity 3, 6, or 12 months in the future? How can we know what the critical path demand is for a particulartype of resource or for a single resource, months in advance when NPD is inherently a highly variable environment? How can we measure and assess theimpact of the resource demandand our capacity constraints on execution success? This presentation will present theon-going status and findings ofrecent pilots effort to use Enterprise and portfolio level tools atTexas Instruments, theimplementation difficulties, and thepreliminary improvement gains. (32 pages)

  10. A Framework for Integrating Resource Management with Critical Decision Making Processes in NPD Locked

    Research | Posted: 2004-09-17

    Paul R. Bunch, Ph.D., Manager, Capacity Planning and Management, Eli Lilly and Company Resource Management (RM) in NPD has been viewed as something that must be done after other key processes have been completed. For example, Portfolio Management is a cyclical process that helps the organization decide what to work on and how to prioritize its projects. Business Planning is a process in which organizations set functional budgets and headcount targets. Typically, Resource management is viewed as an operational process in which functional groups decide how to apply their resources to optimize the portfolio output given the portfolio selected from Portfolio Management and given functional budgets. This presentation describes Resource management as a process that should anticipate resource constraints and inform portfolio managers and business developers of potential resource deficits in time to develop risk management plans. Download a text summary of this presentation (5 pages) here and then download the presentation slides below. (37 slides)

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