- R&D 100 Awards
Thursday, November 15, 2:50 - 3:40 PM
Room #: Grand Ballroom I
The management science behind R&D spending decisions had been stagnant for decades. With the advent of big data and associated analytical capabilities a decade ago, progress is now being made.
There are high-level challenges. First, how does one overcome the long periods of time between initial investment and the realization of results? For fast-cycle companies, the elapsed time is at least five years—and it can range to a dozen years or more for more advanced technologies. Second, how does one define success? Revenues, profits, units sold, market share gain, customer satisfaction, technology leverage, return on investment or innovation, share price or market cap increase are all considerations.
There are also mid-level challenges. Can one underspend for a year or two without affecting the overall product portfolio? What are the effects of consistent underspending? Can one overspend to offset underspending periods, or to catch a competitor? At what point does spending start to yield decreasing returns? Is there such a thing as a "right amount" to spend?
There are operational challenges that may also have strategic implications. What is the best allocation of funds for a company with certain core competencies and technologies in relation to its current business strategy? What amount of funding should go to organic innovation, open innovation, joint ventures/alliances or the in-licensing of existing IP? If there are choices, what should our decision criteria be? How should we allocate our funds across basic research, applied research, advanced development, product development and product enhancement? What metrics should we use?
Inclusive of government, academia, non-profit and industry, almost 70% of all R&D funds are spent by for-profit corporations, the focus of this General Session.
• Learn how big data and analytics will advance the management science of R&D spending.
• Understand the effects of downward and upward swings in R&D spending on business results.
• Critique the considerations of make vs. buy vs. ally innovation.
• Investigate the subtleties of pipeline decisions on spending effectiveness and efficiency.
• Explore the merits of the alternative parameters that constitute R&D success.
• Inventory the most-used metrics and KPIs for R&D spending and its results.
• Identify new-to-industry KPIs that companies are currently trying out.