It was 1980 when Jack Rothman wrote Social R&D: Research and Development in Human Services.  His big idea was the application of knowledge from industry into social services.  Specifically, he was focused on approaches and patterns that resulted in new solutions to problems.  His insight was the application of these approaches to human services when people didn’t believe that human services could have innovation.

Scientists and Practitioners

The walls have come down somewhat between the ivory towers of academia and the gritty reality of the way things get done.  Schools have learned that all the valuable wisdom and studies that they’d been developing weren’t what industry wanted – and it’s not what they’d pay for.  The result was a focus on what might be called implementation science or application research as opposed to primary research, which was purer.

Despite this narrowing gap, there’s still a bit of disdain that reflects the different values and focuses between the pure researcher, who is interested in controlled environments and predictable results, and the practitioner, who just needs to solve a problem – even if the answer isn’t pure.

Social Science

Another gap that must be addressed to get to social research and development is to accept that the two terms are compatible.  While science seems to have clean edges and rigorous proof, social interactions appear to be messy, unstable, and beyond reduction to the levels of science.  However, this perspective ignores the chaos that the physical sciences had prior to the introduction of the periodic table of elements.  Marie Curie received Nobel prizes for both physics and chemistry, but her work with radioactive materials likely led to her death.  It’s not that the “hard” sciences were without complexity, it’s that through hard work, dedication, and persistence, we continue to peel back the complexity to reveal the obscured rules of operation that govern the field.

Decades after Rothman published his work, we still struggle to find the core patterns in social work that drive towards science.  Rothman reminds readers that 90% of all scientists who ever lived were alive at the time of his writing.  Obviously, there’s no statistical measure here.  His statement is likely as true today as it was then not because people haven’t died but rather because the rate of expansion in the number of scientists far exceeds the number of previously living scientists.

This gives us enormous capacity to pursue social sciences and better understand the drivers that create the richness of life.

The Role of Technology

Rothman explains that when Everett Rogers wrote Diffusion of Innovations, he did so using manual indexing and research techniques.  By the time he co-authored Communication of Innovations with Floyd Shoemaker, the process had already converted to being electronically supported in 1971.  In the intervening 50 years, we’ve seen the rise of personal computers, the internet, search, and artificial intelligence that make the problems of conducting secondary research (discovering primary research) more about being able to consume the overwhelming amount of research being done and synthesize it into a coherent whole.

Where databases were complicated and access to research was severely limited, we can now find mountains of data while sitting in our offices by merely flicking our fingers across the keyboard.  We can find rare and out-of-print books – like this one.  The world of research that I live in would have been unimaginable to Rothman and his contemporaries.  Fredrick Kappel of Bell Laboratories said, “I would say that the prime need in modern technology is for wiser, smarter thought and action about what we have…”  His comment is a stark balance against the concerns today that AI will somehow take away jobs and livelihood.

Profitability

The hidden force that drives research and development is profitability.  Organizations (and individuals) make investments, which means short-term sacrifice is made with the hope of long-term gains.  There is, of course, the opportunity for great rewards, but those rewards are not guaranteed.  This game of chance is what underlies all investments in corporate research and development.  Academic research based on pure science is based on curiosity about a topic.

In a sense, the payoffs for the academic are even longer term than the corporate research and development team.  The academic researcher may find something useful – or they may not.  Largely, they’re not expecting their gambles to pay off.

One of the challenges as we bridge the gap between the earliest forms of research and the corporate world is the need to find good probabilities for future returns.  We can’t blindly explore every interesting path – it must be connected to some prediction of future success.

This means that the best academic researcher, who is able to find great things, may be lousy at corporate research and development when that future focus must be held.  It also means that, in social research and development, we must remain cognizant of the desired outcomes and how we believe we can achieve them through the work being done.

Better Research and Development

The goal is better research and development in the social space.  To get it, we can lean on what we know about innovation (see The Art of Innovation) and creativity (see Creative Confidence).  We know that there are multiple components to creating results.  It starts with psychological safety (see The Fearless Organization) and it is better when people come from diverse backgrounds.  (See The Difference.)  Collectively, this creates an engine for innovation.

To really make a difference, we must interact with the world to do what would today be called implementation science.  What we know about this is, when it comes to efficacy, experts are naturally drawn to high-intensity interventions that completely immerse the recipient in a new mindset.  (See The Art of Explanation.)  However, what is often much more effective are low-intensity easy interventions that can be deployed more widely.  Like all generalizations, there are exceptions, but by-and-large, we need to find interventions that are just good enough – not excellent.

Ultimately, when we’re working with social sciences, what we need is to leverage what we know about other industries and areas of study.  It’s through integration that we get to Social R&D.