How Can Companies Predict The Effectiveness Of R&;D?

The world of industry needs R&D investments. According to one study by Breakthrough Energy

• While the most significant value of R&D is realized over the long term, federal funding in the health, energy, and defense sectors has a tangible benefit for the economy and jobs today. In 2018, public R&D investment, directly and indirectly, supported more than 1.6 million U.S. jobs, $126 billion in labor income, $197 billion in added economic value, and $39 billion in federal and state tax revenue.
• The 446,000 jobs directly provided by public R&D investment across the U.S. are good-paying jobs, with 83 percent higher average compensation than the overall economy in 2018.
• If the nation increased R&D spending to 1 percent of GDP by 2030 (approximately $315 billion per year), that investment would support 3.4 million U.S. jobs and add $301 billion in labor income, $478 billion in economic value, and $81 billion in tax revenue.
• R&D investment also spurs productivity, invention, and patenting activity over the long term, bringing us closer to solutions for challenges like Alzheimer’s Disease and cancer as well as climate change.

We need to invest in R&D now—to create good jobs, make a down payment on America’s long-term economic health and competitiveness, and position ourselves to address the most significant challenges of our time, especially climate change.

Other articles claim that there is a way to impact industrial profits based on R&D investments by more than a trillion dollars. The challenge for all businesses is how to predict the effectiveness of the investment in Research and Development.

There is no one formula for predicting R&D return, as it depends on various factors such as market demand, competition, and technological advancements. However, there are several methods and metrics that companies can use to measure the effectiveness of their R&D investments and predict potential returns.

One such metric is the “research quotient” (RQ), as proposed in “The Trillion-Dollar R&D Fix Calculating RQ” article published in the Harvard Business Review in May 2012. RQ is calculated by dividing a company’s R&D spending by its revenue and then raising the result to an exponent that varies by industry. The higher the RQ, the more effective a company’s R&D investments are. Companies can use RQ to guide their R&D investments and predict potential returns.

The Trillion-Dollar R&D articles state it does not require new math, instead as a ratio, this formula can be applied to any company’s R&D investment. “RQ is estimated entirely from standard financial data, so it can be calculated for any firm doing R&D. And because RQ is a ratio, its interpretation is uniform across firms regardless of currency. Most important, RQ is reliable. It confirms what you would expect it to (1) that firms with higher RQ—those that are better at R&D—spend more on R&D than firms with low RQ; (2) that R&D spending beyond the optimal limit identified by RQ reduces firm market value; and (3) that firms with higher RQ have higher profits and market value for a given set of inputs.”

Another method uses data analytics tools to make informed predictions about the potential returns on R&D investments. Companies can use market research, consumer insights, and other data analytics tools to predict the impact of R&D on profits.

Overall, predicting the impact of R&D on profits is not a straightforward process and depends on various factors. However, using metrics like RQ and data analytics tools can help companies make informed decisions about R&D investments and predict potential returns.