Politics and productivity seem to go hand-in-hand in semiconductor R&D organizations. Perhaps it's natural. No manager or project team wants the low productivity Scarlet Letter. So it's hardly surprising that ostensibly poor performers use politics to avoid scrutiny.
But are these so-called low productivity projects really poor performers? In fact, many are not. Quite the opposite in fact—they often have high productivity (although insufficient throughput) but are mistakenly pigeonholed because their crime was a missed schedule. Moreover, schedule overrun usually is not due to low productivity.
Instead, it usually stems from an unrealistic project plan—one in which the allocated staffing is not commensurate with the chip's design complexity, project schedule constraints, and project uncertainties such as spec stability, new mfg. process, EDA tools, etc.
In my experience, unrealistic plans trace their roots to the organization's executive ranks. Senior management promotes a culture of over-commitment in which R&D takes on significantly more projects than it realistically can handle. The consequence is obvious and ubiquitous: most projects in the portfolio are resource-starved.
It's an all-too-familiar story: Projects are inadequately resourced, whereupon they miss schedule, senior management thinks the culprit was low productivity, the team runs for cover. Sound familiar? Of course, executive management has no proof to support its (often unspoken but implied) "lousy team" hypothesis, but likewise the team has few facts and little data to defend itself. Who wins that battle? As the story repeats, the organization gets steeped in the art of productivity politics, including subterfuge, avoidance of scrutiny and measurement, and internecine feuds that stems from finger-pointing.
The great irony is that measuring productivity preempts much of its politics. That's because measurement gives project managers the data they need to prove projects are woefully understaffed and is the root cause of schedule slip, not poor productivity. When managers argue cases using facts and data, they can do so persuasively, often receiving additional resources for their trouble—at least enough to give them a fighting chance to finish within tight schedule targets. They rarely get all the resources they need, forcing them to boost productivity by ten percent or even more. But they're motivated to go the extra mile—doesn't management want that?
Executives win when they make wise staffing decisions—they get dramatically improved on-time schedule performance. Likewise, measuring productivity ensures R&D performance improves at a competitive rate. It also yields the facts and data to ensure future projects get staffed (reasonably) properly, and this preempts or at least mitigates the politics of productivity.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.