Pandemic life and productivity

Are we “post-pandemic”? The epidemiological data say we are most definitely not past the pandemic. Yet, most of are already experiencing a “post pandemic” way of working. What does work after the pandemic look like?

A few weak signals to consider:

 

Qualitative research and innovation

Qualitative research is not generally considered “real” research, and this has terrible implications for innovation. Companies’ thirst for operational effectiveness begs for quantitative data. But quantitative data does not and cannot form strategy. Qual data are a key ingredient to strategy, or the development of new and differentiated products.

Many people are familiar with Michael Porter’s famous paper, “What is strategy?”  Porter famously argued that many companies mistake operational effectiveness for corporate strategy. Operational effectiveness, according to Porter, is about quality, productivity, and speed. It is about doing the same thing as others, but doing it better.

Strategy, by contrast, is about being different. It is about doing entirely different activities to deliver value to customers. Other authors have called this the “blue ocean” or finding a place in the market that is calm, unoccupied, and yours for the taking.  A “red ocean” is full of competitors, doing exactly the same thing as you are, and demanding ever higher performance.

porter

Framed this way, it is clear that operational effectiveness relies heavily on quantitative data. How efficient are we? How do we stack up against the competition? How good are our products? How fast do we make them?

Operational effectiveness simply begs for quantitative data, and now that we have access to petabytes of passively collected data relating to productivity, quality, and speed, it is easier than ever to be operationally effective.

Or it should be. We know that quantitative data requires a great deal of cleaning, massaging, and managing, not to mention analysis, to make it useful for operational effectiveness.

The shift to data-driven operations has demanded a great deal of companies’ attention, mostly because data collection and analysis is not as easy as most think it to be.

But let us not mistake this for strategy.

There is nothing inherent to benchmarking performance that lends itself to strategic advantage. Quantitative data does not reveal how or in what ways customers are making their own workarounds. Quantitative data shows us how many products meet a particular standard, how many products are produced or sold, or how fast a company makes them. It can tell you the average satisfaction a customer may have, but it cannot reveal any of the detail behind that satisfaction.

In their insightful Harvard Business Review article, “An Anthropologist Walks Into A Bar,” Christian Madsbjerg and Mikkel Rasmussen argue that qualitative research gives companies the ability to bridge the “complexity gap,” or what a study of 1500 CEOs revealed as their main challenge. Why do customers do what they do? You must do qualitative research to find out. And, by extension, you must do qualitative research to innovate.

mads

 

Qualitative research is explicitly about revealing detail. Qualitative research shows how people are using products, or how these products sit and gather dust in the corner of the kitchen. Qualitative research, particularly field-based research like ethnography, offers that path to delivering truly different products.

Companies that do ethnography regularly uncover entirely new or different ways to deliver value to customers. Oftentimes, this is done unsystematically. Skillful product and brand managers know that observing everyday life can reveal the how and the why of product failure.

Nike is a great example of a company that is in touch with culture. Its marketers are largely acknowledged to be among the best in the world. Its product innovation is continual, and its brand equity is unparalleled. Even their lab-based researchers like the fabulously named Gordon Valiant are active members of the running community.  His lab-based practice is complemented by regular participation in running events, where he comes into contact with other runners.

Valiant conducts in-lab studies systematically, but observes human behavior in an ad hoc way. Imagine the advantage to companies that do this research systematically. Imagine having a steady stream of insight into real people and why they do what they do. Imagine having thick description of painful workaround work, and regular replenishment of unmet customer needs.

That can only come from systematic, regular, and rigorous qualitative research.

Compare that to a company tirelessly benchmarks its quality, productivity, and speed. The company with qualitative insight into human behavior will have almost limitless potential to do things differently, to deliver new products or services, to find entirely unexamined oceans of product innovations.

Yet we spend almost nothing on qualitative research.  Esomar, the international market research association, estimates that in 2013, corporations spent $6.6B USD on qualitative research, worldwide. The vast majority of money spent on qualitative research is on focus groups, but Esomar estimates almost $1.6B is spent on the more interpretive methods of in-depth interviewing and ethnography. This amount is dwarfed by the $32.4B USD spent on quantitative market research.

It could be argued that many companies need to start with operational effectiveness. Fair enough. But no company can survive on quality, productivity, and speed alone. It is too competitive a marketplace. Qualitative research, therefore, is a cheap way to guide the company toward different product offerings, and ultimately, toward innovation.

 

Design researchers must think fast and slow

Research into brain science some surprising insights for guiding research practice. These findings suggest that the scientific method constrains our natural creativity.
Too often, researchers take their cue from the scientific method. While this method undoubtedly changed the world and our knowledge of it, it is antithetical to the creative needs of a well-rounded researcher. It is especially problematic for design research, which requires creative solutions to existing problems.

Design researchers should embrace less structure and more openness at the early stages of product design, and rigor and structure in the mature stages of product sales. As sales drop off and the product loses its natural match to the culture, design researchers should once again embrace openness in their research approaches.

research phases

Generally, we think of research as the focused, systematic collection of data, over time, in keeping with a given framework or theory. In this view, research is intended to confirm or deny given hypotheses, and incrementally improve our knowledge about a given topic.

We know from the book Thinking Fast and Slow, however, that this research approach only serves one type of thinking. Thinking Fast and Slow author Daniel Kahneman tells us that “Type 2” or “slow thinking” is a disciplined, focused, kind of thought that roughly matches the deductive reasoning of the scientific method and other traditional forms of research. It is structured and deliberate, requiring the cerebral cortex.

But Type 1 or “fast thinking” is less structured, more instinctual, and involves the more reptilian parts of the brain. At first glance, fast thinking appears to be undisciplined or even lazy – the antithesis of the scientific method. But fast thinking produces creative and intuitive leaps that are impossible with the iterative, deductive, and controlled manner of slow thinking.

Design research both thinking fast, and thinking slow. Thinking fast entails creating novel combinations, unusual interpretations, or unique syntheses. Thinking slow entails systematic evaluation and the structured contribution to a body of knowledge.

Gifted researchers engage in both thinking fast, and thinking slow. As sociologist C. Wright Mills describes, a researcher must have her “files,” which is a set of unstructured, messy, and without order:

mills

C. Wright Mills

“…You will notice that no one project ever dominates [the files], or sets the master categories in which it is arranged. In fact, the use of the file encourages expansion of the categories which you use in your thinking. And the way in which these categories change, some being dropped and others being added – is an index of your intellectual progress and breadth. Eventually, the files will come to be arranged according to several large projects, having many sub-projects that change from year to year. [1, p. 3]”

Anthropologist Bronislaw Malinowski echoes this messy disorder when he describes what will eventually become his masterwork The Argonauts of the South Pacific:

malinowskiBranislaw Malinowski

“I estimate that my future publication will be voluminous, roughly three volumes of 500 pages each at 500 words per page. It will take me about two years to get the [manuscript] ready and see it through the press. My material is now a chaotic mass of notes. To work it out and put it into the right theoretical frame is perhaps the most difficult, exacting, and important stage of research. To work it out efficiently I must give it all my time. [2, p. 582]”

Malinowski recognizes the “chaotic mass of notes” must be whipped into shape to become a manuscript, but he must first grapple with the disorder. This is precisely what psychotherapist Rollo May describes as the “creative encounter,” or the unstructured time an artist (or researcher) spends with her subject of study.

may

Rollo May

“The first thing we notice in a creative act is that it is an encounter. Artists encounter the landscape they propose to paint – they look at it, observe it from this angle and that. They are, as we say, absorbed in itOr scientists confront their experiment, the laboratory task, in a similar situation of encounter.  [3, p. 39] P. 39″

Consider also the “commonplace book,” or the kind of notebook great thinkers like John Locke and Charles Darwin used to organize their thoughts. As innovation author Stephen Johnson tells us, early modern readers did not read sequentially, but jumped around, setting the stage making creative connections.

 

johnsonSteven Johnson

“The tradition of the commonplace book contains a central tension between order and chaos, between the desire for methodical arrangement, and the desire for surprising new links of association….Each re-reading of the commonplace book becomes a new kind of revelation. [4, pp. 109–110]”

In other words, researchers who allow themselves to read out of order, or to collect without regard for structure, are able to make creative, intuitive leaps. But researchers who fail to methodically manage their knowledge fail to close the loop of production. Researchers need to think fast and to think slow. They need to think broadly and think narrowly. Type 1 and Type 2 thinking translates into 3 kinds of research: exploratory (thinking fast), evaluative (thinking fast and thinking slow), and experimental (thinking slow).

Frequently, social scientists in particular focus on “rigor” as the solution to good research. But rigor without creativity adds little to our collective knowledge.  As Heideggerian scholar Carol Steiner argues, this “fore-structure” – or predetermined way of looking at the world – stops us from conducting innovative research and producing innovative things. Instead, innovative researchers, she found, are open to “Being,” or the ability to have experiences, people, and objects reveal themselves to them.

steinerCarol J. Steiner

“The innovators I studied seemed sometimes to be attuned to that old understanding of the relationship between Being and people…Losing faith in the scientific method has allowed them to understand themselves as other than knowledge-makers. Consequently, they often project an openness that allows them a different world to shine through for them, the public world. “[5, p. 594]

In other words, researchers in particular must struggle against the “fore-structure” or their extensive theoretical and methodological training which interferes with receptivity. As Rollo May argues, being receptive does not mean lacking in rigor.

“The receptivity of the artist [or researcher] must never be confused with passivity. Receptivity is the artist holding him or herself alive and open to hear what being may speak. Such receptivity requires a nimbleness, a fine-honed sensitivity in order to let one’s self be the vehicle of whatever vision may emerge. [3, p. 80]”

Rigor must be introduced later in the process – after the researcher becomes open to a vision, after the researcher grapples with the complexities of the data and their incongruence. Rigor often comes after a period of unconscious processing of the data.  Taking walks, playing, napping, and engaging in unstructured activity have all been shown to allow synthetic ideas to emerge.

Researchers should therefore use the scientific method with caution. Be aware of when you need rigor, and when you need creativity.

 

 

 

 

References

[1]      C. W. Mills, The Sociological Imagination. New York: Oxford University Press, 1959.

[2]      M. W. Young, Malinowksi: Odyssey of an Anthropologist. New Haven, CT: Yale University Press, 2004.

[3]      R. May, The Courage to Create. New York: WW Norton, 1994.

[4]      S. Johnson, Where Good Ideas Come From: The Natural History of Innovation. New York, NY: Riverhead Books, 2010.

[5]      C. Steiner, “Constructive Science and Technology Studies: On the Path to Being?,” Soc. Stud. Sci., vol. 29, no. 4, pp. 583–616, 1999.

 

Why I decided to self-publish my second book

You know it’s true what they say — the second baby is much more of a blur than the first. My good friend Carol likes to tell the story about giving birth the second time with her cardigan still buttoned up. There she was, in the delivery room, bundled from the waist up. When the baby comes, it comes.

And by baby, I mean book. Yes, my second book took me a little by surprise too. Sure, I had enough time to make a cup of tea and change into slippers (sorry, Carol) but I didn’t have the time for a publisher.

Way back in 2012, I began writing my first book. I had secured what was known as a “book deal” with a small social science publisher that had a good reputation among people I knew professionally. I knew nothing about publishing, of course, except that someone would put my ink on some sort of pages and paste them all together. Or would they sew them together? That’s a thing, isn’t it? Given my total ignorance, I thought it was acceptable to earn only 8% of every book sold. That’s right 8%.

I still earn only 8% on Practical Ethnography.

I fought harder for the 15% I now earn on all Kindle copies of Practical Ethnography but I thought it was worth it to learn how to publish a book. In retrospect, I don’t know if it was. The publisher hired a copyeditor for me, but I found we mostly argued about emdashes and doubt quotes instead of making my actual copy better. The design of the book was…well it was okay. The marketing was abysmal. I had the good sense to buy the domain name myself, and several years after publication, when my little West Coast publisher got purchased by British Behemoth, I told myself I never wanted all that hassle again.

So when my second “baby” was ready to arrive, of course I tuned to my friend Carol for help! Luckily, Carol is also a professional journalist and has a cadre of colleagues who are fantastic freelance copyeditors. Her old buddy Rebecca came on board and managed to midwife this book so quickly that my tea never even got cold. But then what? Do I sew together the pages like before? The prospect of a print book almost sent me to another publisher. Almost.

I bit the bullet and learned how to make a print book.  I got on Reedsy.com. I hired a designer. I hired a web designer. I took the cover photo myself. I released it on Kindle to finance the whole shebang. And now, here we are. Book Number 2 is now available in paperback and Kindle, and it’s a 100% Sam Ladner Production. Special thanks to Carol, Rebecca, book designer Sarah Beaudin and web designer Derek Moore. It really does take a village to raise a child.

I’m a proud momma. Please check out my beautiful baby on her own beautiful web site.

Mixed Methods Guide Web Site Screenshot

New book alert: applied mixed methods research

My latest book is now available on Kindle! The book is a short guide to doing applied mixed-methods research. It’s ideal for people who work in applied research role in industry, but may not have a broad, methodological training in both qual and quant research methods.

What’s inside:

Table of Contents
Introduction: Understanding The Qual/Quant Divide
A Mixed Methods Example: Stories as a Network
What Are Mixed Methods? Mixing Objectivism and Constructivism
    • A constructivist view of technology
    • How the qual/quant divide plays out
    • Abandoning the scientific method: the creative encounter
    • Mitigating the weaknesses of qual and quant research

Why mix methods?

Ways to mix methods

How to mix methods, step by step

    • Project kick-off and framing
    • Developing shared understanding about research needs and resource constraints
    • Framing your approach: inductive or deductive frame?
    • Social Infrastructure: preparing teams for mixed methods
    • Research design
    • Priority or dominance
    • Data collection: simultaneous or sequential
    • Sequential designs
    • Simultaneous designs
    • Clarifying concepts or variables
    • Data analysis and interpretation: mixing Induction and Deduction
    • Can analysis and interpretation be a team sport?
    • During reporting

New Horizons for Mixed Methods Research

Conclusion: To Mix or Not to Mix?

References

What even IS this? Why tech companies are still failing us

Why do we know so little about the social implications of technology? It plays a starring role in everyday life, as essential as food, shelter, and clothing. A huge share (70%) of Americans use social media, and even 65% of senior citizens use Facebook  – that’s more than the number of people who eat family dinner at home, attend church, or have a pet.

Yet, we know so little about technology’s impact on everyday life. We are only just now recognizing problems like coordinated disinformation, breaches of personal data, and algorithmic discrimination.  Clearly, technology companies are falling short on understanding the social implications of their tools before and after they build them. But why? Why are tech companies failing us?

Woman in kitchen.
Woman in kitchen. Source: Art Institute of Chicago

Sadly, it is all too predictable that technologists underestimate, misjudge, or otherwise underappreciate how humans will interact with their technology. This is for one simple reason: engineering, as a discipline, does not bother to ask:  “What is this?”

Engineers are not scientists, much less social scientists. They typically have no knowledge of basic human behavior such as loss aversion or impression management, even though these are the building blocks of social interaction – and entry-level knowledge for social scientists.

Engineers could ask, “What is this?” but instead choose to ask: “Does this work?”

“Does this work?” underpins research within tech companies. Once upon a time, tech companies hired engineers they called research scientists and stuck them in labs to tinker endlessly with pieces of hardware and scraps of computer code. Even today, there are over 7800 job postings for “research scientist” on LinkedIn, which are typically engineers or computer scientists. A posting for an Uber research scientist intern is instructive. In addition to having a Master’s degree in a “technical field,” the intern is also encouraged to engage in “risk taking” and to “turn the dreams of science fiction into reality.”  Another job posting for a research scientist at Facebook asks for skills in the scientific method, but then specifically narrows that down to “evaluate performance and de-bug.” In other words: Does this work? Notably not mentioned: the ability to develop basic knowledge.

Academics would see much of this activity as more akin to prototyping than to scientific inquiry. Indeed, these engineers produced many technology prototypes, but not much in the way of generally applicable knowledge, or what the rest of us might call “science.” In other words, they never seem to stop and ask, “What is this?”

Painting by Salvador Dali
Inventions of The Monsters

Today, tech companies need to ask things like “What is a digital public sphere?” and “What is the nature of privacy?” and “What is artificial intelligence versus human intelligence?” Tech companies need typologies of human-computer interactions, motivations, fears, and human foibles. They need to create a system of knowledge around key questions of technology like artificial intelligence and social media.

Some argue that technology development doesn’t have time for “understanding,” that asking “What is this” takes too long and is too expensive. But this is a false economy. Philosopher Martha Nussbaum tells us plainly that we need that understanding, not for understanding’s sake but because it guides our planning:

“Understanding is always practical, since without it action is bound to be unfocused and ad hoc.” — Martha Nussbaum

In other words, if you don’t know “What is this” you’re probably going to build the wrong thing.

We can see this pattern of building the wrong thing in technology, over and over again. The term “user friendlywas invented way back in 1972. Curiously, “user hostile” wasn’t invented until 1996, just before Microsoft’s infamous Clippy appeared in 1997. Clippy’s abrupt entre onto the desktops of the world indicated that technology “researchers” had no idea what they had made. Word famously exploded from what appeared to be a digital typewriter, to a swollen behemoth that did everything from create a newsletter to automate mailing labels. Pick a lane, people. Clippy was there to tell users how to make Microsoft Word work, but no one bothered to find out much less explain what Microsoft Word actually was.  Word is still so swollen that a new user today can credibly ask “What even IS this?”

Clippy the paperclip
Source: NYMag.com

Flash forward to today, and the so-called “lean startup” approach to building technology is really just a faster, even more facile way to ask “Does this work.” In reality, tech companies still don’t know, “What is this?” even after they’ve built a working prototype.

In my former role as a hiring manager at a major tech company, it took an average of 100 days to hire just one ethnographer and more often than not, the job remained open much longer than that. These are the very people who can tell us, “What is this?” The demand for these social scientists only grows. Yet, the tech industry as a whole has not yet figured out they need to ask “What is this?” before they build something.

Were tech companies to ask, “what is this,” they would learn the basic properties of their tools, their coherence, intelligibility, performance, and affordances. Instead, they are fully occupied with “does this work,” and create horrific blights on our collective consciousness like Tay, the racist AI Bot on the relatively innocuous end of the scale, and Compass, the racist parole algorithm at the full-on evil end of the scale.

Technologists do not know what they do not know. Ethnographers hope for the day when they can just ask “What is this” without worrying about whether it works, because it doesn’t even exist yet. But tech development continues apace.

It’s time for ethnographers to stop this sad venture, and instead insist on asking: What IS this? Before another Tay, before another Compass. Technologists too must take responsibility because if we don’t, the 21st century will become even more technocentric, and even less intelligible. Let’s find out what’s going on before we build anything else.