By Ron Collett

From the business perspective of a semiconductor company, Numetrics’ solutions are about making substantial improvements in chip development productivity and schedule predictability. But just what is productivity, and how do you first characterize it and then improve it? What’s the outcome?

Productivity drives development throughput in your R&D organization – the higher the productivity, the greater the throughput. And throughput is a measure of how much product the engineering organization churns out during a given period of time.

There are three ways to boost R&D throughput:

• Add headcount
• Increase work-hours per week
• Raise utilization and productivity

The first two have downside: Raising R&D headcount increases cost, and more hours lead to workforce burnout and high turnover.

The only viable long-term strategies for sustaining high throughput are to increase engineering utilization and productivity.

Utilization

Increasing R&D utilization—the percentage of the engineering workforce’s effort spent on revenue-generating activities—is among the quickest and most effective ways to boost throughput. That’s because it essentially increases R&D resources without incurring additional cost.

Organizations struggling with low utilization find their engineers spend more than half their time on non-revenue-generating activities, such as sales, customer support, and product support – all of which should be handled by different groups. In large companies, that means millions of dollars a year are being squandered.

Engineering organizations in best-in-class companies, however, spend 73 percent of their engineering time on activities that generate revenue and create persistent value. By shrinking the amount of time engineers spend on projects that get cancelled, non-core research, myriad internal initiatives, and so forth, companies can significantly raise their utilization rates and, in the process, reduce R&D spending and/or develop new revenue-generating products.

Productivity

 Productivity – the second factor driving throughput – is the amount of engineering output per unit of labor expended to create that output. Productivity is a function of efficiency. Only by improving efficiency will productivity rise. Analysis of R&D efficiency compares the effort a particular set of engineering tasks should consume to what they actually consume. Reducing the effort needed to complete a set of tasks raises efficiency, which increases productivity, and this gives rise to higher throughput.

Boosting productivity requires a reliable measurement system–one yielding accurate baselines and fair comparisons. Additionally, a robust measurement system paves the way for managers to determine the absolute minimum staffing projects need to finish on time. At that point, the projects are “optimally understaffed,” which means the projects can be staffed to levels that assume the teams will meet an improved productivity level.

And there’s where best-in-class companies are pushing the productivity envelope.

Originally published in EE Times http://www.eetimes.com/discussion/other/4201131/How-productive-is-your-R-D-organization-

By Ron Collett

We’re gearing up for DVCon (Feb. 22-25) in San Jose and not just because we’re participating in a panel. DVCon (on Twitter, @dvCon), which has emerged as a increasingly important event in recent years, features as keynoter Cadence CEO Lip-bu Tan. His topic gives a new voice to the mounting productivity crisis in semiconductor and system design.

According to an abstract of his talk:

“…the industry must approach the product development process much differently. The classic ‘brute force’ methods cannot scale to support the complexity of today’s SoCs and Systems. These traditional methods result in mounting costs and unpredictable schedules that are detrimental to profitability.”

• Cadence approaches the problem by giving engineers (among many other things) design exploration options that speed the implementation of the physical architecture of a chip.

• Numetrics approaches the problem by helping teams quantify the complexity of their design effort and build reliable project and staffing plans. This is crucial in an era where most IC projects slip schedule significantly.

Our vice president of professional services, Steve Gary, will speak on a panel just after Tan’s, titled “What Keeps You Up at Night?” It’s moderated by JL Gray from Verilabs, who writes the excellent Cool Verification blog; he’s posted a panel preview this week.  Also in the conversation will be John Goodenough from ARM Ltd., Sheela Pillai of Advanced Micro Devices, Inc., Jim Crocker from Paradigm Works, Inc. and Victor Melamed from Ambarella.

There are plenty of things keeping the industry up at night, but I think we’ll hear a lot of excellent ways to overcome the sleeplessness and drive productivity—and the industry—to the next level. Hope to see you there.

By Jeff Eversmann

Sometimes the simple questions are the most vexing. That hit me this week while participating in a DesignCon panel in Santa Clara, moderated by EDN Executive Editor Ron Wilson.

The title seemed easy enough: “Getting to Design Quality Closure Without Compromising Productivity.”

But really, what IS quality? How do we define it?

My fellow panelist, Camille Kokozaki, president of Design Rivers, quipped “It’s like pornography: you know it when you see it.”

Piyush Sancheti, senior director of business development at Atrenta, came close:

“Quality is meeting the design objectives you have: whether it’s area, power, timing functionality, or, in a broader sense, customer expectations. Productivity is getting there.”

Sancheti then added:

“Being able to measure it (productivity) with tools like Numetrics is important because you want to hit your objectives as fast and effectively as possible.”

Not surprisingly, our panel wrestled with one of the big issues in design quality today: verification. It deeply affects design quality and productivity. Sancheti noted that for some teams, 70 percent of the entire design development is spent on verification.

What I see first hand from customers is they struggle to understand how verification affects their productivity. Some program managers I talk to say:

“I understand the scope of logic design and physical implementation. Verification is an unknown for me. If I give the verification team another two months, they’ll take it, but how do I know that we’re better off?”

So, I think we’re seeing that verification needs to come up with some sort of model of completion so people can move on. And that’s not easy. Our data shows that some companies toggle up the tape-outs as part of a larger verification strategy, but that can hurt overall productivity.

How we fix verification is a broader issue. Do we lean on formal methods at the architectural level as opposed to time- and engineering-consuming test vectors?

For now, our role is to help teams quantify their design effort, properly staff their projects, and understand where they stand with respect to the industry’s best teams. From there they can make fact-based decisions to drive productivity improvements.

That’s our contribution to the broader challenges of verification and design quality, but as we all know, it takes a village (and many future industry panels) to come up with the solution.

(Jeff is Numetrics’ director of professional services and product marketing).

Bright lights in a dimly lit DesignCon room: (L-R) Camille Kokozaki, Design Rivers; Piyush Sancheti, Atrenta; Jeff Eversmann, Numetrics; Michel Tabusse, Satin IP

By Ron Collett

The latest venture capital investment figures are out from PricewaterhouseCoopers’ MoneyTree and the National Venture Capital Association (NVCA). They’re not pretty.

VCs spent just $17.7 billion on 2,795 deals last year. That’s down 36 percent from $27.9 billion in 2008, and it represents the lowest dollar amount and number of investments since 1997.

The chart I pulled together above, based on that data, shows the quarterly VC investment trends for semiconductor companies in just the past three years. Not an encouraging trend line. Total VC investment last year in our industry was $771 million, compared with a peak of $3.4 billion in 2000. What a difference a decade makes.

This realignment of dollars has brought about new expectations from investors and from semiconductor vendors.

Speaking to The Wall Street Journal last week, Bob Ackerman, a venture capitalist at Allegis Capital in Palo Alto, said:

We’re preoccupied by capital efficiency.

Those two words, “capital efficiency,” speak directly to the semiconductor industry’s challenge. This focus on capital efficiency is why semiconductor vendors should be increasingly preoccupied with boosting engineering productivity to get the most from their R&D budget. Lacking an internal fab for differentiation in the fabless era, companies are looking for new ways to gain competitive advantage, and they’re training their sights on their R&D organizations.

The industry’s best-in-class semiconductor IDMs in fact have jumped on this imperative, especially as many of them have shed the last of their owned fabs and now need to compete with fabless companies.

But it works the other way too: Long-time fabless players suddenly find big new competitors that have shed their fabs. They too are looking to boost product-development productivity to stay one step ahead of their new competition.

It’s clear the days of big-time investment are a thing of the past. Today, good companies are those with innovative product ideas; great companies are those that also drive highly productive R&D organizations to get those products completed on predictable schedules and to market ahead of the competition to realize higher returns.

By Ron Collett

In December, we were honored to participate in a Design & Reuse panel in Grenoble, France, titled “IP Reuse vs. IP Leverage: What’s the difference and what are the issues?”

Andrea Fortunato, our European director of professional services, represented us and gave an overview of the particular challenges that design reuse brings. He blogged about it right after the panel (Design Reuse: It’s Harder Than it Looks).

Our friends at D&R have just posted an audio Webinar of that panel. It’s definitely worth a listen if you’re designing with cores and trying to take advantage of reusability.

Have you had design reuse challenges recently? If so, feel free to comment on this post to let us know what they were and how you overcame them. Improving productivity in the semiconductor industry is a communal effort!

By Ron Collett

I like to catch up on reading during the holidays, and I came across a really interesting exchange on the Becker-Posner blog.

Gary Becker, the University of Chicago economics professor, examined some fresh Bureau of Labor Statistics numbers on productivity (see chart below), which showed productivity is soaring as the nation pulls out of recession.

He wrote:

The fast growth in American productivity toward the end of this serious recession is quite unusual because measured productivity often falls during recessions as companies are stuck with excess capacity of their capital.

His take on the economy’s near-term future, based on this data, was positive. Technology, as it does historically, will be leveraged to advance productivity. His blog partner, Richard Posner, a federal judge and University of Chicago lecturer, was not quite so optimistic:

Posner attributed the productivity gains to “old-fashioned cost cutting spurred not by technological advances but by economic distress.”

The only explanations I have seen offered for the productivity surge is cutting wages and working the workers harder. I have found no suggestion of any technological change that might be responsible for such a large, sudden surge in productivity…Productivity gains that are based merely on adaptations to temporarily depressed economic conditions will be lost when conditions improve. As labor markets tighten, a firm will perforce hire workers who are less productive than the workers it had retained in a slimmed-down workforce during the depression; and so productivity will decline.

I don’t think it’s a zero-sum game. Some rehiring is inevitable but so too is exploiting the advance of technology; smart managers look to technology to advance productivity gains.

We’ve seen our own semiconductor industry begin to roar back to life in recent months, and I can tell you that R&D departments are looking to optimize development efficiency as a new way to differentiate themselves and keep the momentum going. That’s why I think 2010 is the Year of Productivity.

Non-farm labor productivity jumped 6.9% in the second quarter of 2009 and another 8.1 % in the third quarter, surprising some economists.

By Ron Collett

(Summary: As the recession’s pain recedes, semiconductor companies have an excellent opportunity to take advantage of the economic crisis to drive productivity improvements throughout their R&D organization.)

The line “never let a serious crisis go to waste” was made famous a year ago by White House chief of Staff Rahm Emanuel, who was speaking to business leaders. For the semiconductor industry emerging from a sharp recession, now is the time to capitalize on the motivation implicit in Emanuel’s quotation.

Consider, first off, the proven benefits that companies get when they take advantage of a recession. A Bain & Company study found that:

• Twice as many companies move from laggards to leaders during a downturn than they do during good times.
• The majority of those companies that take steps to make that move sustained their gains long after business came back.

For those that don’t, the numbers are discouraging:

• One-third of banks and two-fifths of big American industrial companies fell from the first quartile of their industries in the recession of 2001-02, according to a McKinsey study referenced in The Economist.

There’s plenty of advice for companies willing to take advantage of a business slump. Dave Jones and Pierre Loewe, writing on ChiefExecutive.net, advise managers to re-assess “unarticulated” customer needs and redraw their industry ecosystems.

I’d amplify another of their key points: buttress your core competency. Today’s semiconductor industry is a different place than it was before the recession. The search for differentiation in core competencies needs to be focused at product development. This is crucial for fabless companies that don’t have their own manufacturing to create differentiation. But it’s also important for formerly “fabbed” companies making the transition to fabless.

Out with the old?

Some semiconductor companies emerging from this recession will be tempted to apply old templates to new designs. With understandable caution about hiring more engineers in the short-term, the tendency will be to do more with less—to demand more products faster with fewer engineers.

What will happen?

Unrealistic schedules and budget overshoot, for one thing. For another, the urge to crank out more products to take advantage of resuscitated demand will lead to portfolio-management problems.

It doesn’t have to be this way. Productivity improvements and best practices are commonplace in manufacturing; there’s no reason they can’t be employed in R&D. It would be a shame to waste a golden opportunity to exploit this moment in history, and, to finish Emanuel’s quotation, to take the “opportunity to do things you think you could not do before.”

By Ron Collett

The concept seems simple: The more ip blocks you re-use in an IC or system design, the faster and more productively you’ll get your design done. The ITRS roadmap began identifying the benefits as long ago as 1997, showing the industry could reasonably expect 56,000 gates per designer per year when using large ip blocks (75,000-1 million gates). By 2007 that figure was up to 600,000 gates per designer per year, a tenfold increase.

There’s no doubt design reuse is here to stay. In 2007, a third of all logic was reused design blocks. That’s expected to rise to nearly 50 percent by 2015, according to the ITRS.

The numbers and the theory behind it are encouraging, but reality is much different. Making 30 percent of your design from reused IP blocks doesn’t mean you’re going to be 30 percent more productive at the end of the project. That’s because IC design teams tend to underestimate the work needed to implement the reused IP. This can cause project delays and missed market opportunities.

The challenge is that it’s very difficult to estimate design complexity, especially the impact of reuse. IC design schedules can falter because of the inability to estimate the impact of IP modifications on project effort.

Even a small percentage of reuse can add outsized effort to a development project. For example, if you add one new block of 600,000 gates to a 6 million-gate design, you’re adding 10 percent to the IC but increasing the effort required on the project by 24 percent. Adding 10 percent new circuitry to all blocks in that 6 million-gate design—with 90 percent of each block being re-used—doubles the effort required on the project, even though it increases the IC size by just 10 percent to 6.6 million gates.

This issue will be part of a larger discussion Dec. 1 at IP-ESC 2009 in Grenoble. We were invited to sit on a panel—“IP Reuse vs. IP Leverage: What’s the difference, and what are the issues?”—with Kathryn Kranen, CEO of Jasper Design Automation, and Olivier Haller, who manages the design verification team in the Functional Verification Group at STMicroelectronics. Our director of professional services, Andrea Fortunato, will represent Numetrics.

This is a well-timed panel in my opinion because re-use is an issue that transcends the industry and is crucial for its future. And how we go about optimizing design re-use is crucial to manage today.

By Ron Collett

(Summary: As the semiconductor industry emerges from the recession, new ways of thinking are emerging as well to improve what’s becoming a new differentiator for companies: IC design development.)

All indications are the semiconductor industry is rebounding from the painful recession of the past couple of years. The latest upbeat data points include:

• Worldwide third-quarter PC microprocessor unit shipments rose 23% compared to the second quarter, reaching a new all-time high, according to market research firm International Data Corp. (IDC).
• Chip-sales growth should be 10 percent in 2010 and 8.4 percent in 2011, according to the Semiconductor Industry Association. The decline in 2009 chip sales (down 11.6 percent is now less that earlier forecast).
• Individually, companies like Marvell, TSMC and ON Semiconductor are reporting encouraging results.

But, as they say, there’s good news and bad news. The good news is obvious. The bad news is more subtle: Companies are beginning to crank up the product-development dial significantly, and this can become a challenge for R&D organizations.

As a surge of new projects occurs, hiring generally is slow to catch up to demand. This puts stress on engineering organizations. Schedules are difficult to predict, and the engineers can get shifted from one product development team to another in the race to make deadlines. Managing a portfolio of products turns into a torch-juggling exercise—spectacular to watch but done with the knowledge that the risk is high.

This is a significant problem in the fables era—a time in which IC design development is an increasingly important source of differentiation for semiconductor companies. A sudden burst of product-development activity can bring R&D organizations to their knees.

Design development productivity is something to consider as we emerge from this recession. The stakes are high, and there’s little room for error in marshalling engineering resources to get products to market quickly.

All recessions force change on business, and this one is no exception. Old ways of doing things are being replaced by new thinking on productivity—all with an eye toward making “up and to the right” last.

By Alex Silbey

(Summary: We inevitably get questions about Numetrics’ technology after webinars or live event presentations, and we’d like to share some of them in the spirit of helping you understand more about our products and solutions. Here are answers to several recent questions in the virtual mail bag).

Q: How do you define productivity?

A: We calculate complexity of the project and we divide the complexity units by total number of person weeks required to get that product out to volume production. That quotient gives you the productivity number. The typical range is 500 on the low end for a large team to 3000 for a small team.

There’s another measure, which is throughput, and throughput is complexity units per week. That’s a measure of normalized cycle team. Productivity is efficiency of the team and higher number is better.

Q: I’ve heard that in some sectors productivity decreases as team size increases. Is this true in semiconductor product development?

A: It’s a universal effect across pretty much any activity that has to do with building things. When you build larger teams, each person is doing a smaller and smaller slice of the overall work. More work has to be split apart and then put back together. Bigger teams equal more meetings and more management required. It’s universal and it’s inevitable. With the Numetrics approach, you can minimize this effect—decreasing productivity curve is flatter than it would otherwise be.

Q: It’s impossible to predict in a design project how many times customer requirements will change, when your EDA tools go buggy or if a key contributor leaves the team. So how do you quantify schedule risk with so many unpredictable variables?

A: The simple answer is our tools don’t predict things. You have a draw a line between statistical analysis and a crystal ball.

What Numetrics’ tools do is take your inputs of design parameters and measure them against the history of more than 1,500 design projects over eight generations of technology evolution (here’s a link to a demo of our tools). Using the data from those hundreds and hundreds of designs, this builds in realistic effort required to deal with those issues. It’s a way of contingency planning.

Think of it like yield modeling. You know that on each wafer a certain number of dice will fall out. Yield modeling doesn’t tell you which particle is going to hit which die and where. But they give you an accurate assessment of how your design will yield. Numetrics is like a yield model for project plans. It’s saying there’s a certain probability that if you’re going to try to achieve these targets, given what you’ve input you’re going to fail.

It allows you to make a quantitative assessments. It’s a probability model. It’s not a crystal ball.

Q: How does the complexity calculation model handle predictions for newer nodes, such as 45 and 32nm?

A: Numetrics’ IC Industry Database has collected information for eight technology generations. The technology shifts from one generation to another have been observed before. And what we’ve observed is that early users of technology nodes face considerably more complexity than later users of the same node, once the models and such are more stable. The equation has calibrated this effect which repeats from generation to generation. We’ve been able to model what the effect of the extra technology of a new node will be on a new design.

Q: Can your tools get data from existing sources or do I have to input it manually?

A: We’re dealing with milestones, staffing information and complexity information. Typically this information is copy-pasted from existing sources or customers are using XML import to get data into our tools.

(Alex is Numetrics’ director of professional services).