As R&D executives cope with tight financial resources and demands for increasing new revenues, the pressure to measure their organizations increases. Metrics allow R&D leaders to optimize R&D’s productivity and justify to the CFO and CEO their returns on continued funding. There are actually rich sources of appropriate R&D metrics for leaders to select from. By understanding the recent history of such metrics, leaders can use them to set the context for discussions with their CEO. Additionally, it has become evident that managing any form of intellectual capital utilizes common measurement elements. Consequently, R&D leaders are in an excellent position to help the leaders of other corporate functions develop metrics for their respective organizations.

Historically, R&D management has experienced four waves of productivity improvement. Each one has brought improved understanding of how to pick R&D projects (effectiveness) and how to best carry them out (efficiency). Likewise, measures associated with evaluating and improving the effectiveness and efficiency of R&D performance have changed too.

In the early 1990s, companies faced strong global competition and were under pressure to sustain their level of shareholder return against very successful global new product development systems. For example, Asian products captured large shares of profitable growth markets and built entire new ones. For all CTO’s, this made it imperative to learn how to improve a company’s R&D organization, and make oneself a better R&D leader.

1. Re-engineering Drives Incremental R&D
The first wave of change occurred around 1990 and was driven by a re-engineering initiative that swept through all corporate cost centers. CTO’s strove to reengineer all unnecessary costs out of their R&D organizations. Smaller, division-sponsored, research programs replaced large corporate R&D budgets. The focus was on improving incremental R&D and thereby boosting the company’s next -quarter earnings. New or modified metrics were needed to measure results of the new focus. Key questions asked at this time included: When does the corporation receive its money’s worth from its R&D dollars? What size organization is required so that only value-adding functions are left? What are the minimum financial targets that should be considered for a product to be introduced? This was clearly an accountant’s view of R&D.

For this short-term focused, incremental type of R&D project, new product ideas were most likely found by listening closely to customers’ stated needs for new features. For process research, scanning the literature for proven new technology to adopt quickly was a successful strategy. Project selection for this class of development was done effectively by using return on investment (ROI) calculations because most of the numbers were known for such short-term work. Class A, B and C customer lists ensured that key relationships were supported, and risk versus capability charts helped to select R&D project portfolios. Project work was characterized by a “just do it” mentality since incremental research was for the most part easy to define. In knowledge management jargon, researchers and the CTO “knew they knew what to do.”

Developing metrics for R&D organizations was a big issue during this era. The work of Szakonyi, Robb and Leet was built upon by the Industrial Research Institute’s committee and subcommittee work (1-3). From these efforts, it was found that the best overall metric for the outcome produced by incremental R&D was to measure divisional financial performance tracked monthly on a control chart. Output metrics included divisional products mapped on a Value Chart, which maps the relative costs of products and services produced by differing technologies versus the relative performance (quality, service level, unique design features) of the same technologies. In-process results were shared with executives using monthly progress reports. The parties with the most concern and influence over R&D results during this period were divisional general managers and their business teams.

2. Next-Generation R&D Fills the Gap
By the mid-1990s, the reengineering phase had passed and most companies were productive when it came to incremental research. But at the corporate office, gaps were found between what the divisions said they could produce in revenues and the financial returns the CEO had promised “The Street.” Next-generation products and services were needed to fill the growing gap.

For everyone directly involved in corporate R&D, the pressure was on to find and develop new product ideas quickly. The new strategy was to listen and to understand an entire industry, as opposed to the wants and needs of individual customers, in an effort to find good next -generation ideas to develop. Mapping technology trends and forecasting technology platform evolution developed as methodologies to address these needs. Sanderson, Meyer and Cooper each led teams of authors who addressed these issues via either de novo approaches or by borrowing from traditional marketing research programs (4-6). Options came into their own as selection criteria. Portfolios were studied and selected based on their risk-to-reward profiles.

Now the quality aspects of doing R&D effectively became the issue. The key questions being asked were: What are the best methods by which to manage R&D? How do we know if our methods are delivering results? Which technology can best assist us in creating sustainable product lines? During this period, “quality” in product design and R&D also became buzzwords.

To execute next-generation projects efficiently, stage-gate processes were employed and resources were tapped worldwide as the East European countries began participating in the growing scientific community. Project and portfolio progress was tracked with R&D gate reviews. These were expanded as the decade progressed to include cross-functional membership, and extended past product introduction to include follow-up business reviews. Work since the early 2000s has also seen the utilization of post-launch IP gate reviews.

As this period evolved, the quality driver moved onto, “How does R&D provide the best service to the operating divisions, as well as service to customers in the form of new products and services?” Key questions became: How do we shorten the R&D cycle time? How can we access the latest technology globally? The driving person moved from an internally looking Quality Director to the external viewpoint of the VP of Marketing.

“Knowing that we didn’t know” and behaving accordingly characterized such next-generation research. The overall outcome metric was change in market share of the businesses, tracked quarterly on control charts. At the output level, Use Charts and platform road maps showed progress towards company “gap filling.” At the in-process level, projects were tracked by mapping progress in sales and marketing milestones versus milestones for research and manufacturing. Senior group vice presidents, who needed their sales targets matched to systematic introduction of successive next-generation platforms, were now directly concerned with R&D.

3. New Business Demand Fuels Breakthrough Innovation
But of course Wall Street is never satisfied and CEOs kept promising even bigger returns. This was especially so as dot-com companies overtook the market capitalization of companies that had built their businesses over many decades. Filling the need to develop whole new highly valued breakthrough businesses fell mostly to R&D leaders. Christensen, Leifer, and Downes published books on the dilemmas facing companies in need of radical innovation and killer applications (7-9). Key questions demanding answers were: How do we get the most from R&D to spur business growth? How do we access tacit knowledge from around the world? How do we acquire resources on-demand and just-in-Time? The person needing answers to these questions migrated as well, from the Marketing VP to the General Manager, COO and CEO.

We were now clearly in the space characterized by “not knowing what we didn’t know.” However, here again professional society networks and committees shared information so that successful patterns of behavior could be recognized and built upon. Companies found that the odds of finding business ideas are improved when new ventures are utilized. Typically, these are external relationships that are proactively commissioned or in which small equity stakes provide glimpses into future market needs and services. Selection is accomplished by a combination of instinct and experience. Portfolios are mapped using risk and strategic fit. Managing-the-fuzzy-front-end developed as a methodology for internal project management, whereas external R&D and ventures were found appropriate for faster moving fields.

Tracking breakthrough business progress was done with portfolio reviews conducted by venture teams looking at all aspects of the developing market, business, research, and intellectual property. The overall outcome metric became the change in a company’s market capitalization tracked quarterly as a moving average. At the output level, first- year sales of new businesses, tracked again as a moving average, was utilized. The in-process metric was typically the commercialization or “round of funding” progress displayed on venture portfolio maps. The key stakeholder became the company CEO, and a strong relationship between this individual and the R&D leader was critical for continued personal and organizational support.

4. Dot-com Crash Brings On Leveraged R&D
But, of course the world is an ever-changing place. With the collapse of the dot-com’s, 9/11, and the financial scandals that followed, all business came under intense pressure to hold revenues and profits. It is no surprise then that the world has come full circle. With increased knowledge and maturity, reengineering costs out of R&D returned. In the words of P&G’s CTO at the time, Gil Cloyd, “We must find ways to do less with less and get more.” The pressure was certainly on from corporate boards and CEOs, with the CFO at the CEO’s shoulder.

This last challenge is as tough or tougher to manage than the previous waves, and a lot remains to be learned about effective R&D leadership in this environment. Although some of the past behavior that generated success will continue as best practices, it is unlikely that all the lessons from previous waves of change will remain inviolate.

To meet the challenge of more with less, some CTO’s are using more external R&D resources to provide the diversity of thought, flexibility in project staffing, just-in-time development, Agile and Lean product development methods, and lowered total cost. Others are looking to expand the impact of internal R&D discoveries via aggressive “carrot” out-licensing programs to other non-competing, and in some cases competing, companies.

For example, IBM aggressively asked potential infringers to license IBM technology, generating for IBM over $1.5 billion per year in increased before-tax revenues. Dow Chemical and DuPont donated tens of millions of dollars in R&D’s excess intellectual property to universities, using the donation to return more money to their shareholders. These one-time benefits have run out however and more sustaining revenue models replaced these initial one-time hits.

“Carrot licensing” is a dominant form of R&D value transfer utilized extensively in the pharmaceutical industry. Biotech and medical device manufactures target their R&D programs to produce salable/licensable results for other companies to exploit. Procter and Gamble, for instance, puts all of its technology up for license to others, and at the same time was aggressive in seeking 50 percent of its new technology from other companies to fuel its own growth. This effort generated medium term results, but it is now known that the approach was short-sighted, leaving P&G with a new product development gap. Long-term metrics showing investment in new-to-the-world technologies are necessary for long-term corporate sustainability and value.

Over the time periods discussed metrics have evolved. As one might expect, the ability to measure outcomes to the satisfaction of the various stakeholders changed with their level of sophistication and business understanding. Earlier, when reengineering was done from an accountant’s perspective, metrics could be segmented by consequence, timing and activities. This was an outgrowth of the accountant’s view of the world and “activity-based-accounting” concepts in vogue at that time. What this required of R&D was segmentation of the R&D activities by activity type. This was easiest for incremental R&D, wherein activities and timing could be defined accurately enough to meet the financial standards. But for long-term research, these efforts lead to frustration. The trick was to segment activities to a level of detail that could be tracked without such a heavy overhead investment of time that people were “spending as much time recording their activities as doing the activity itself.”