Rumors of the SoC’s impending death have been popping up in the semiconductor and systems industries. Are they exaggerated? Not entirely. A decreasing number of companies are investing in system-on-chips (SoCs). Likewise, the number of concurrent SoC projects that typical R&D organizations can undertake is shrinking. The reason: soaring design cost and poor schedule predictability .That makes SoC development increasingly difficult to justify. But does this foreshadow the SoC’s complete demise? I doubt it, but these factors will surely chase more players from the market and drive greater use of alternative solutions. [More]

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. [More]

What’s the optimal team size for a given IC design project? It’s a question I hear often from engineering managers and senior executives. What they’re actually asking is whether they’re over-staffing projects and therefore wasting resources. Implicitly, they’re also asking “what’s the fewest number of engineers I can put on a given project and still finish on time?” They’re important questions directly impacting R&D ROI. [More]

Engineering utilization, productivity and throughput are among the most important metrics for measuring R&D performance. If you want to improve your R&D capability, focus on these three metrics.

Productivity and utilization directly determine throughput, and throughput is the most important of all R&D performance metrics. It measures the rate at which an R&D team develops production-ready products. The higher the productivity and utilization, the higher the R&D throughput. Higher throughput means the R&D team churns out more products in a given period of time. That usually translates to revenue and profits— assuming the rest of the enterprise pulls its weight. Big assumption, right? [More]