How do you know if an organization's performance is best-in-class, especially that of a competitor?
Competition among semiconductor companies has become super-heated, and R&D excellence has never been more important to establishing competitive advantage. But how do you know if an organization's performance is best-in-class, especially that of a competitor? Such accolades are often anecdotal and based heavily on perception, a few unsubstantiated metrics or the halo created by the company's strong financials. High revenue masks much and distorts even more.
Although digging deeply into the numbers seems like the best way to get confirmation, most semiconductor companies do a poor job of tying R&D costs of projects and product lines to corresponding sales figures. Even with good cost-accounting, revenue numbers are easily skewed by the impact of a strong sales force, heavily financed marketing campaigns and long-term customer-vendor relationships. Financially successful companies often have all three working in their favor, which obscures the true efficacy of their R&D organizations.
Even when verifiable metrics such as cycle time are available, it's still easy to be misled into believing a competitor's R&D is best-in-class. For example, let's say a development organization boasts short development cycles and consistently beats competitors to market. The knee-jerk reaction—its R&D must be best-in-class. But peeling back the onion can quickly reveal they staff their projects with a more engineers than the norm.
Putting more resources on a chip project increases development throughput (until the point of diminishing returns), and high throughput is the key to short cycle time. It measures the project team's output per unit of time (e.g. a week). But there's often a price: Higher staffing almost always yields lower productivity—less output per individual—unless the team performs at best-in-class. Best-in-class teams avoid this phenomenon.
Development productivity suffers as team size increases because coordination and communication requirements increase. More people beget greater managerial overhead.
Maintaining high productivity in the face of expanding team size reflects both superior management and design capabilities. It's a core competency whose importance is growing rapidly because IC team sizes are on the rise—to keep pace with soaring design complexity.
Determining whether a particular project is best-in-class thus requires measuring both its throughput and productivity. Best-in-class R&D organizations boast consistently high productivity across the full range of team sizes.
Independent evidence confirms the paradigm's validity. Projects with above industry-average throughput and productivity wield a commanding edge over the norm: cycle times are 23 percent shorter, they have 10 percent fewest spins, first-time silicon success rate is twice as high, they have 51 percent better schedule performance and 68 percent lower cost per unit of output.
Ronald Collett is president and CEO of Numetrics Management Systems, Inc.
It ain't Research in Motion (RIM). This outfit is going the way of my former employer, Nortel Networks; namely, down the tubes. Canada should stay away from high tech industries and concentrate on their competitive advantages in producing hockey players and stand-up comedians.
Or, with slightly different terminology, efficiency vs effectiveness,
I don't know that you can really make useful comparisons. There is far too much variance between different companies and even between different teams in those companies.
For example, how do you compare a team developing an automotive chip (high reliability, high temperatures,...) to one developing a consumer chip (fast, low power). The first team have a lot more emphasis on testing and verification and need to move conservatively but the second group just need to get the next gen chip out there fast.
Great analysis of the difficulties of measuring R&D productivity. The challenge is getting easier, however, with the advent of new toolsets and methodologies, that fundamentally change the way organizations conduct R&D. We've seen customers using a combinatorial R&D approach achieve results in weeks that would have taken months or years with traditional methods. The resulting improvement in efficiency enables project timelines to be met or pulled in without assigning additional staff. While this doesn't provide a direct mechanism for benchmarking against competitors, it does allow you to measure internal progress, both in terms of cost and ultimate success in bringing new technologies to the market.
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