Rigorous, critical questions are the hallmark of R&D professionals. We welcome your questions and look forward to discussing how R&D Manager can add value to your bottom line. The FAQs below feature some of the key questions previously asked by other clients during their due diligence. Still have questions? Please Contact Us to discuss in greater detail.
Why should I trust RQ™?
RQ has a solid economic foundation. In fact, it is based on the most common method economists use to measure R&D productivity at the industry level. The only thing new with RQ is extending the measure to the firm level. Because RQ has this solid foundation, it also affects three important outcomes predicted by economic growth theory for firm level R&D productivity. When testing over 40 years of data for public firms, Professor Knott found that 1) optimal investment increases with RQ, 2) firm growth increases with RQ, and 3) market value increases with RQ. Moreover, RQ was the only measure for which these predictions hold.
In addition to the solid economic foundation and empirical support for the RQ measure itself, the knowledge linking RQ to firms’ R&D practices stems from rigorous National Science Foundation (NSF) funded studies across the spectrum of US firms conducting R&D. In 2010 the NSF awarded Professor Knott a grant to identify firms’ practices associated with high RQ. In 2012 they awarded her a follow-on grant to quantify the impact on RQ of firm R&D practices in the NSF’s annual Business Research and Development and Innovation Survey (BRDIS). This was the first study to quantify the impact of their R&D practices on firms’ financial performance.
Finally, proof that RQ affects market value is evident from the fact that the RQ50 portfolio (the top RQ scoring companies in any given year) outperformed the stock market by over 900% from 1973 to 2015.
How can I use RQ™ to choose how to allocate R&D?
RQ is a universal measure which can be applied at the firm or divisional level. Firms can model different investment possibilities at the corporate or divisional level, using the same algorithm in all cases. Indeed, firms gain greater insight into their business by comparing the RQ of different divisions or projects and can then make funding allocations based on the full knowledge of which divisions are most productive.
Visibility into the more granular division levels provides the solution to the old "peanut butter" problem of spreading R&D evenly across all divisions. Higher RQ performance divisions can produce even more, given more investment. A major Fortune 100 company recently employed RQ to set their annual divisional budgets, and without changing the overall investment level, saw a 70% increase in revenues based on the reallocation of resources to the highest performing divisions. RQ is what provides visibility into which divisions or projects are most deserving, as well as which divisions business practices might be best replicated in other parts of the corporation.
RQ is based on past data, how can it help me make investment decisions for the future?
RQ is a firm’s average R&D productivity over the past 7 years, and unless the firm or its market is changing dramatically, RQ is fairly stable from one year to the next—in the same way other capabilities are fairly stable. For example, you have a pretty good sense of how long it will take to run a marathon from taking the average of your last several marathons. Unless you dramatically change your weight or your training, the prior scores are reliable predictors of future scores.
Some of my R&D is for inventions that are ten years away from commercialization. How does RQ respond to my development cycle?
RQ is actually based on lagged R&D spending. However, it is only lagged one year. While that seems short, we found that a one-year lag was a better statistical fit to firms’ data than any longer lag we tested. The intuition for why that’s true is that even though some R&D investment is for long-range benefit, it comprises only a small percentage of firms’ R&D. If you were to take all the R&D done by a firm in a given year, and analyze it by time-to-market, the “centroid” of that distribution is typically 1 to 2 years from commercialization.
My company has several divisions, that are in different industries. Knowing the RQ for my diversified company doesn't help when my divisions are like comparing apples and oranges.
R&D Manager from amkANALYTICS provides RQ not just at the corporate level, but at the divisional level as well. While a diversified company may have businesses or markets that vary widely, each business unit's RQ can be compared to each other in order to optimize R&D investment across the corporation. The RQ value itself is a universal score, so that the results from different divisions can be compared regardless of the variances in industry or underlying business dynamics.
Knowing the respective RQ scores of various divisions also opens up the opportunity for management to promote best practice dissemination among the different divisions. Unlike human IQ, which is relatively static throughout an individual's lifetime, organizational RQ can grow, leading to increasing levels of profitability. Over the past forty years, a 10% increase in RQ corresponded to a 4.3% increase in market value.
What can I learn about my competitors?
R&D Manager subscribers can track up to three publicly traded rivals per company or division, and can see their competitor's RQ trend lines right alongside their own. Note that all subscriber data is confidential, and that any competitive data is based exclusively on publicly available 10Q data..
Additionally, R&D Manager subscribers who participate in quarterly best practices benchmark surveys will receive best practices analysis comparing their own practices to the average of their industry peers.
You claim that the average firms is leaving $182 million in profits on the table. It seems highly unlikely that my firm's spending is that far off. Why should I believe those numbers?
The average is just that. We expect that results will vary.
But the reality is that in fiscal year 2015, 95% of all firms were spending sub-optimally, with 33% underinvesting in R&D, and 63% spending too much. The average amount of over-investment was $258 million, and for those who underinvest, they could increase profits by $36 million by increasing their R&D investment by 10%.
As a simple test of whether these estimates are plausible, Professor Knott looked at the investment prescriptions she made in the Harvard Business Review article, “The Trillion Dollar R&D Fix” two years after the article was published. She found that only 9 of 17 firms followed her prescriptions, but for those firms, profits increased 16.4% on average; while for those firms who deviated from the prescription, profits decreased14.1% on average.
But you don’t need to fully correct R&D investment immediately. Using R&D Manager's interactive modeling feature, you can test investment levels you feel most comfortable with, as you forecast the impact of your R&D investment on future revenue and profits.