Why research will remain a human activity

The future of business research– thoughts among peers see and search

Last Friday, July 20, I convened my monthly ad-hoc gathering of diverse professionals to talk about strategy. This month’s topic was the business of research and its future. As is our customary practice, participants reviewed in advance a series of articles to focus on and spur their thinking on the topic.

As moderator and convener, I’m always eager for a thought booster, and the conversation never disappoints me and to my delight, the participants find their time well spent. Opportunities to think aloud and have my own thinking challenged makes up for my time and effort to share selected articles, invite and then engage participants to deliberate on any topic.

Did my own thoughts on the future of research shift today? The answer is yes.  It’s challenging to do justice to a broad topic in 75-90 minutes, and still, we tapped several of the critical themes.

My synopsis follows of key thoughts I had neither considered prior—what motivations beyond curiosity generate research, and the approach affects and ultimate effects the future of research.  Note, participants occasionally chose to distinguish references to general terms by referencing the term via its first capital letter.

Beyond curiosity

I don’t expect people to stop being curious, and to my surprise, others pushed back on that premise. The growing conveniences mobile technologies’ afford to make new knowledge easy to access. The change in human behaviors and growing dependence they produce create efficiencies that limit or encourage us to forego active direct observation and discovery efforts. The changes may or may not affect the inspiration for further research or press the distinctions between general theory and accepted principles and specific cases that currently drives research.

The general conversation began by unpacking the presumption that research is a human activity inspired by curiosity.  Machines may accelerate, assist or be a subject of research but they don’t initiate research by themselves.

Big R-Research as a broad concept historically lays out a path to build knowledge.  Its value grows as the research is shared— its methods, raw input and the means that produce synthesis and transform the raw inputs into findings.

Sadly, the current state of the world reflects dilution of the term research and makes its application indistinguishable across a range of activities. Automated data systems generate volumes of research for consumption by both people and machines. The meaningfulness of findings now synonymous with results spit out all too often as visualizations—the new euphemism for graphical depictions of data.  Research results when they appear only in this form builds little actual knowledge. The capture of the latest observation and its addition to a trend line or as a portion of a whole does little to explain the how or why, fails on its face to challenge, enhance or enrich the general or standing understanding.

Alternatively, pure research falls into the Big R-research category that follows an open exploratory, investigative, discovery path. Commercial research can follow a similar path but its focus and test of determination must satisfy specified objectives determined to support, grow the business. Google Search team’s research development fits this latter category.

Even Google’s moonshot too because at the end of the day all the development and proceeds are owned and controlled by a commercial entity/patron. Any patents or new methods that result in these environments are not contributing to general knowledge but benefit the owners. Corporate research labs offer research academics environments flush in resources and data, but limit and control the distribution of their findings.

Sponsored business research appears to have a little more flexibility around its distribution and we discussed the benefits of two distinctive forms.

    1. Privately sponsored research by VCs, Google, or historically Bell labs whose activities often followed the lines of pure research contributed academic papers but not everything was published—needs verification.

A journalist asked Thomas Edison: “How does it feel to have failed 9,999 times.” Edison said, “I haven’t failed, I have had great success, finding 9,999 ways that do not work.”

The strategic meaning of this message?  Rather than share the failings, Edison preserved competitive advantage by holding onto 100 percent of his learnings from failure. Which is akin to the slow progress being made in pharma and other industries who seek to gain and preserve a competitive advantage, for the sake of slowing advanced development.

No one had an example of an industry who plays differently.

2. Government or foundation sponsored research manages to overcome some of these obstacles.  The coffers of US basic research advances general knowledge in multiple sectors, and again its use may hold some restrictions—the details need nailing down. Still government initiatives fund numerous advances in technology and other fields that both support the creation and ongoing survival of multiple businesses. For example, DARPA sponsored several Self-driving car competitions, Star Wars project by the Reagan administration work helped grow GPS capabilities, and NASA, who can forget TANG. Recent investments by the Chinese government seeks to create national strategic advantages over other countries and grow its domestic capabilities both human and technical.

These descriptions of research variations resemble geologic strata—where basic research or foundation research is the common denominator and each layer of specialization distinguishes and separates from subsequent layers while denying the integration. Perhaps the layers reflect the barriers of ownership that limit the spread of research and its findings within or across sectors by turning it into a property.


When I worked in banking, I learned that without risk there was no reward.  Risks associated with research naturally attach to its scale, scope, the degree of ambition, as well as the uncertainty of results. Planning and the approach an organization takes in its research activities can mitigate and help an organization strike an acceptable balance.

Curiosity clearly is not the only inspiration for research, as was mentioned purpose and Big V-vision plays a role.

As mentioned, sometimes businesses establish a research arm hopeful these investments’ preserve the growth or survival of the firm.  The time horizon, the presence of a vision or a clear picture of opportunity often determines leaders’ expectations as well as their approach to research.  Leadership focused on near-term growth requires sharp clear means to quantify and justify their investments. They are more likely to seek incremental improvements or small differences and advantages, both easier to sustain and convert the investments into value.

Striking the right balance depends on your ability to understand both the timing and quantification of overall market demand, as well as your competitor behavior –capacity and capability to take market share. Intel’s research investments guided by Moore’s law exemplify this approach.

Understanding your competition, the concern of strategy departments’ research activities also contributes to the quantification of risk. Operationalizing SWOT using research fits this approach.  Rather than a one-shot if played out continuously, each stage benefits from contributions from research which also fuels its progression. Here’s how that would work.

Internally, research can turn known business weaknesses when supported and developed into strengths. Additional research benefits from these new strengths to seize external opportunities and ideally knock out external threats. A variety of research activities contribute to the momentum of this W to S to O to T quashing cycle. Similar research activities afford discovery or wider awareness of emergent external Threats while also furthering self-recognition of corresponding internal weaknesses that create momentum for never-ending review and invest cycles.

Another approach I’ll call Comparative research reflects business leaders’ ongoing preoccupation to produce goods and/or services faster, better and/or cheaper. Note this approach resembles Deming and Toyota Production Systems focus on incrementalism and continuous improvements while also engaging and focusing internal attention to improve singular value measures.

A third approach mimics the scientific approach in which the research objectives are very narrowly drawn and success and failure clearly defined. In the digital environment, many teams engage in A/B testing of a change designed to enhance performance at very low levels but potentially lead to bigger results.

All three of these approaches are Evaluative—in that all produce measurable changes in value. The comparison of an idea’s value and its worth to the organization when measured justifies the research activity.  If the idea’s value can be assessed, then conversely, the risks of not developing or pursuing the idea are measurable too.

Efforts to achieve bigger R research that produces more ambitious results requires additional justifications. Their additional risk may reflect a wider set of leadership capabilities and strategic agendas. Venture capital hopes their investments turn into unicorn businesses rely heavily on research and analytic assessment capabilities.

The reliability and predictability of timetables to results slide in proportion to the size of the ambition to achieve Big R research characteristic of the unknown domains or even the unknown unknowns.  The greater the gap or risk reflects several things: one, the distance between what the organization knows and/or is knowable and what it doesn’t; two the extent of discovery needed; and three the level of organizational ambition.   [Note, this might reduce to the time value of money calculation, rather than a more elaborate justification for research as risk clearly factors into organizations decision, research and likely research activities. ]

The Big V-Value aspect 

Conceptually,  the discussants also recognized other aspects of research along with a different continuum that doesn’t lend easily to quantification.  That’s when research inspirations resemble discovery. Both relate to finding, becoming aware of something previously unknown to either the seeker or the wider world.

This is an experiential aspect, in which emotions and brain processes not fully understood play a critical role—this is what I’ll call the Big V-value aspect of research.

Philosophers focus on bigger questions that humans ponder and may be alone in their pursuit, but none the less persistent in their search. I  mention the eternal questioning that humans experience and undertake, such as:   “Why are we here? ” “What’s my purpose, what difference can /should I be making?”

The ideas, activities we value don’t always equate to a market value, or its economic utility and/or price.

It would be remiss to talk about research and its future without acknowledging that inspiration and deeper motivations drive our behaviors and often cause us to reverse direction. Here are a few examples of research revisiting the initial assumptions;

Two engineers now at Google –Asa Razkin and Tristan Harris, realized their efforts to improve and increase convenience on mobile devices also led to over-consumption. As a result, they gave rise to a revolution to return control to the users.


Similarly, the decision theorists and the behavioral economists who recognized that valuations were not the only consideration when people were facing economic decisions.  This has also given rise to designers recognizing that removing friction or simplifying a path prevented people from having to collect their thoughts before proceeding—thus removing barriers or friction was not always an optimal approach. To learn more about positive friction, I recommend this piece https://www.slideshare.net/secret/NPcI5mCnlpvYsR

It’s impossible to avoid the realization of research as circular versus the approach of increasing that we sense to trend linearly.

Would welcome your thoughts, or reactions!

ARTICLES that were previewed in advance follow:

1.What happens when data scientists and designers work together (~7-8 min read)
HBR March 2018

2. Tom Peters True Confession (~20 min read)

FastCompany 2001

3. Google-X and the science of radical creativity (~40-50 min read)
The Atlantic, November 2017

4.Why is the insights startup community exploding? (4-5 min)

5.How Disruptions are Born and How It Applies to the Market Research Discipline (7 min)
Greenbook June 2014

6. see and search7-8 min)