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    Archive for February, 2009

    Excellence in Semiconductor Design Productivity

    by Numetrics | February 23, 2009 | In Best Practices, Case Studies | No Comments

    Summary: Everybody wants to increase productivity. But there’s no free lunch: assigning too few resources to a project increases stress and creates schedule risk.

    Productivity excellence is the process of maximizing productivity by setting the most aggressive targets that are still achievable. Achievable targets mean that you will meet your schedule goals. Aggressive means that everyone will be working really hard to get there. The combination ensures that your products will come to market at the earliest possible time, given hard, focused work from a team no larger than you need.

    The value of productivity excellence is felt in three main areas.

    • First, in these tough economic times, you can be sure you haven’t spent money on resources that are not essential to your project.
    • Second, you have set the bar appropriately for an ambitious, capable engineering team.
    • Third, you have controlled schedule risk, and minimized the likelihood of a schedule slip, with potentially disastrous implications for revenues and market share.

    At the end of the day, productivity excellence means meeting your business goals efficiently, with a motivated workforce doing their best to meet an aggressive, but still feasible plan. Take a look at our customer case study involving Innovasic, which maximized its design throughput by benchmarking
    microcontroller development team productivity.

    What is industry-norm effort for semiconductor designs?

    by Numetrics | February 14, 2009 | In Products, Project Planning, Risk Analysis, Schedule Predictability | No Comments

    Summary: Realistic semiconductor IC project planning hinges on industry-norm effort, which is the comparison of the actual productivity achieved by teams across the industry and the actual complexity of their designs.

    Complexity is a measurement of how difficult it is to complete a design. It’s a measurement based on many attributes of the design, carefully correlated across multiple historical designs. But in order to plan, we need to know the amount of effort it will take to complete a design of a certain complexity. The answer lies in a comparison of the actual productivity achieved by teams across the industry and the actual complexity of their designs.

    From this comparison we can calculate the amount of complexity an average designer can implement in a unit of time. Because this is a normative value calculated across the industry, we call it industry norm effort.

    We can also make the same calculation for your company—assessing the amount of complexity your designers have historically been able to implement in a unit time. By comparing this with the industry norm, you will get a sense of how your team is doing as compared with the industry.

    But the main use of industry norm effort is in conjunction with the complexity data for a proposed design:

    • We can accurately and rapidly calculate the total effort required for that design using either your company data, or the industry norm data.

    This provides a firm foundation for realistic planning, while still allowing you to set aggressive (but not unrealistic) targets for your team.

     
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