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]

Discussions about R&D return-on-investment (RoI) among semiconductor industry executives often turn to engineering productivity. They’re often surprised when I assert that productivity isn’t that important—at least as far as R&D performance metrics are concerned. A far more important metric is engineering throughput. [More]

Bad news: Steadily declining IC development productivity means more job losses for engineers employed in first-world economies—e.g. U.S. and Europe. Those lost jobs are going to second-world economies because labor costs are much lower. Moreover, the trend is accelerating as chip design complexity outpaces gains in productivity. Don’t shoot the messenger for the message. [More]

You’re frustrated and suddenly stalled on the freeway and what happens in larger organizations is chillingly clear: a chain-reaction crash that creates incredible chaos across the R&D group.

Missing Schedule

Part of the reason so many semiconductor projects miss schedule is that staffing levels are not aligned with the level of complexity that the design team needs to undertake. This is solvable problem.

Fact-based planning provides the team with data for decision-making—ensuring that projects are staffed properly to meet the demands of the design’s complexity. Estimates of design complexity, project-staffing requirements and development cycle time are generated using empirically calibrated models. This is the heart of Fact-based planning, which is used by top semiconductor companies across the industry.

Fact-based planning

• Eases the traditional tension between groups within the enterprise that struggle to communicate in different languages by guiding discussions and strategy with facts and data.
• Enables predictable revenue streams because it yields accurate schedule estimates, therefore there are no surprise shortfalls in revenue or margins.
• Leads to predictable schedules, which is crucial in an era when time to market is more important than ever, and companies can’t afford to miss the market upturn.
• Doesn’t replace bottom-up, detailed planning but complements it.

Boosting Productivity

Fact-based planning is essential to an important productivity boosting best practice: seeing the project execution pipeline clearly and managing it centrally. This best practice—and the tooling behind it—rolls up all project plans to generate a picture that shows the total resources consumed by all project plans. With this bird’s-eye view of all project plans, engineering managers can observe where there are shortfalls and over-subscriptions role by role, month by month. This becomes an essential tool for managing the pipeline.

This isn’t an airbag that protects you in a chain reaction crash. This is a radar system that prevents the crash in the first place and gets everyone to their destinations safely.

Originally published in EETimes http://www.eetimes.com/discussion/other/4205031/The-ripple-effect