BEST BUSINESS BOOKS 2017: Innovation
Innovation is an obsession. Companies spend
hundreds of billions of dollars every year on R&D. Yet studies find little correlation between how much a company
spends on R&D and its financial performance. Most products fail to make it
past two years. And even in this time of rapid technological change, the
difference between success and failure in innovation seems, if anything, more
random than ever. So it’s not surprising that the year’s best business books on
technology and innovation promise to discern the order beneath the chaos, and
to make building a new product or service something more than taking a shot in
the dark.
In Competing against Luck: The Story of
Innovation and Customer Choice,
Harvard Business School professor Clayton M. Christensen and his coauthors
(Taddy Hall, Karen Dillon, and David S. Duncan) start with the assumption that
at most companies, innovation is “a hit-or-miss process,” and they want to
change it. Christensen’s 1995 book, The Innovator’s
Dilemma, in which he coined the term disruptive
innovation, was a theory of why dominant companies fail to innovate. In his
new work, Christensen lays out a theory of what real innovation requires, one
that he terms Jobs Theory.
Jobs Theory rests on a deceptively simple
concept: Customers aren’t really interested in products and services in and of
themselves. Instead, they buy them to solve a problem — or, in Christensen’s
parlance, to do a job. Successful innovation, then, demands identifying exactly
what that job is, and offering something that will help. Competing
against Luck discusses five different routes to identifying the jobs
that customers need help with — including looking at the jobs you yourself want
to do, and looking at what customers are trying desperately to avoid doing. But
the real key is a focus on context and circumstance.
Jobs Theory is a well-developed articulation
of legendary marketing guru Theodore Levitt’s famous line (which he attributed
to an advertiser named Leo McGivena), “Customers don’t want to buy a
quarter-inch drill bit. They want a quarter-inch hole.” But Christensen says
companies should ask, “What do customers want a hole in the wall for?” To
answer this question, companies must uncover a rich and fully developed definition
of what customers seek that goes beyond the classic market research into
customer needs, engaging with the social and emotional dimensions of why
customers purchase products and services. One of the most compelling sections
of Competing against Luck is a careful dissection of the
complex thought process a buyer went through while taking six months to decide
to replace his mattress.
One interesting aspect of Christensen’s
theory is that many consumer problems have a range of plausible solutions. Jobs
Theory also inverts a conventional model of innovation: Instead of building a
product and then figuring out how to sell it to consumers, you start with the
consumers. That helps avoid the problem of an overemphasis on features for
features’ sake, and the tendency of tech products, in particular, to succumb to
feature creep as companies add more and more features to their products simply
because they can.
Christensen makes a case that you can turn
his theory into a systematic, rigorous process for driving innovation. But the
leap from identifying a job to helping consumers do that job is obviously a
huge one, and even identifying jobs seems harder than Christensen makes it out
to be. Still, Jobs Theory offers an essential insight, which is that successful
products are, in some sense, services. Corporations are already coming to terms
with this reality, in part because of digitization. That’s why PwC has
projected that R&D spending on products will
have fallen 19 percent by 2020. Christensen’s book provides an intellectual
framework for understanding that shift, and in the process helps explain why it
will, if anything, accelerate.
Technological Futurism
On the surface, it’s hard to imagine a book
less like Competing against Luck than futurist Kevin Kelly’s The Inevitable:
Understanding the 12 Technological Forces That Will Shape Our Future.
Where Christensen’s book is resolutely concrete and is replete with such homely
examples of innovation as mattresses and milkshakes, Kelly’s book is — like
most of his previous works — oracular in tone, riddled with high-flying
sentences such as “People of the Book favor solutions by laws, while People of
the Screen favor technology as a solution to all problems.” Kelly’s job title
is senior maverick at Wired, and what he’s written here is a
quintessential work of technological futurism, laying out 12 broad trends that
will play a crucial role in shaping the future. Yet for all of the airy
pronouncements, The Inevitable remains usefully tethered, at
least most of the time, to reality; its real focus is the way humans use and
will use technology in an always-on, always-connected world where devices are
increasingly intelligent and increasingly networked. Kelly’s trends are
all in the form of verbs — flowing, filtering, sharing, and so on.
Although a bit of a shtick, the framework embodies Kelly’s view of where
society is going: Processes are ultimately more important than products, even
as products themselves are becoming processes.
The rise of artificial intelligence, the
cognification of our surroundings (such that the physical world will respond
and adapt to our needs and desires), the replacement of ownership by access (or
the “Spotification” of the world), the tendency for individuals to self-track
and to be tracked: These things are, in Kelly’s mind, inevitable. As the flood
of information and data continues to rise, methods of filtering and organizing
that flood will be more essential and more valuable. Consumption, particularly
of information and entertainment, will become more active and dialogic. Our
experience of the world will, in large part, be mediated through screens.
Because Kelly views these developments as
inevitable, he says comparatively little about companies or entrepreneurs, and
how they are supposed to bring this glorious future about. In that sense, his
futurism has something in common with Marxist theory: Innovators almost seem to
be mere vehicles, driven by the deeper forces of history. What’s valuable
about The Inevitable, from a business perspective, is less what it
says about how to innovate, and more what it says about where to
innovate.
There’s something exhilarating about Kelly’s
optimism — no dystopian view of AI or the robot apocalypse for him. At the same
time, he often treats any new technology as necessarily worth using, even when
it doesn’t appear to represent much of an improvement over what we use today.
He talks about how we’ll screen bowls to see if they’re clean from the
dishwasher — is that a meaningful improvement from just looking at the bowl to
see if it’s clean?
Kelly’s specific predictions often seem to
reflect the kind of future someone like Kevin Kelly would like to live in. And
in that, they may tell us less about the future than about Kelly himself. His
macro view of the future, though, offers a convincing, and rigorous, picture of
how technologies that we can see today will have a profound effect on our
tomorrow. And that makes The Inevitable an essential text in
thinking about how to take advantage of — and simply prepare for — the
transformation of everyday life.
Platform News
If Competing against Luck is
a classic work of business theory and The Inevitable is an
inspiring ride into the future, Andrew
McAfee and Erik Brynjolfsson’s Machine, Platform, Crowd: Harnessing Our
Digital Future, the best business book of the year on technology and
innovation, is an insightful and powerful blend of the two. McAfee and
Brynjolfsson, both of MIT’s Sloan School of Management, became gurus of the
digital era with their seminal book, The Second
Machine Age (Norton, 2014), in which they argued
that we were on the cusp of nothing less than a new industrial revolution. And
although they were relatively optimistic about the long-term implications of
that revolution, they also argued that in the short term, the impact would be
wrenching, as new technologies decimated old job categories and threw millions
out of work.
Clearly, in specific industries,
digitization, the rise of AI, and the growing ability to tap the crowd are
creating a host of new opportunities — and posing a new set of
challenges. Machine, Platform, Crowd is McAfee and
Brynjolfsson’s guidebook to this new world, focusing concretely on how
organizations can best leverage the new tools the digital age offers. And its
real subject is innovation in the broadest sense: not just innovations that
bring new products and services to market, but also innovations in the way we
make decisions and solve problems, in the way we collaborate, and in the way we
organize work.
The book focuses on three shifts: from humans
to machines, from products to platforms, and from the core to the crowd. Some
of the book will be familiar to anyone who’s paid a little attention to the digital
economy: It’s hardly a revelation, after all, that platforms have become
central to the tech economy. But the authors’ discussion of the economics of
platforms and how platform companies price their services is nonetheless
fascinating. And they raise an especially interesting question: If so-called
sharing platforms end up massively increasing the degree to which existing
assets, such as cars, are shared (thereby reducing the number of cars that need
to be individually owned), what happens to the companies that make the cars,
and that have built entire businesses around the idea of individuals owning
them?
Even stronger is the book’s analysis of how
machine learning is changing the way companies not only analyze data but also
make decisions. As the sheer amount of data that machines can now analyze has
grown (thanks to the Internet), so too has the value of machine learning. It’s
not just that patterns become more robust (and more significant) the bigger the
sample you’re looking at. It’s also that the more data you give machines, the
better they become at learning. If you want computers to be able to recognize
pictures of a cat (something that was beyond them not very long ago), showing
them millions of tagged cat pictures is a great way to do it.
McAfee and Brynjolfsson argue that machine
learning can be used to, in effect, make decisions. They emphasize that
algorithms are a good way of avoiding the biases that we know plague human
decision makers. And a host of studies, dating back decades, show that
algorithms can outperform human experts in a wide range of fields. Rather than
continue with a decision-making model that ultimately boils down, in their
words, to the highest paid person’s opinion (or HiPPO), companies should
outsource a big chunk of the work of analysis, evaluation, and prediction to
the machines. And although Machine, Platform, Crowd may
overstate just how powerful machine learning has become and understate the
organizational hurdles to going all in on algorithms, the book does an excellent
job of showing how technological innovation is changing the way decisions are
made.
Technology has made it far easier for
companies to appeal to what McAfee and Brynjolfsson call the crowd. Although
more suggestive than definitive, this section of their book makes a convincing
case that companies that open themselves up to working with people outside the
company (including customers and suppliers) can radically improve performance
and drive innovation. In such companies as Quantopian, which is trying to build
an investment tool by tapping the collective wisdom of traders; GE, which has
used customers to help generate new products; and Topcoder, which provides
companies access to coders around the world, the crowd is increasingly
influential. People have been talking about the potential virtues of tapping
the wisdom and work of the crowd for almost two decades. But its moment seems
to have arrived.
Machine, Platform, Crowd is, then, an invaluable look at the impact of new
technologies. But beneath all the concrete problems it raises, an intriguing
question lies at the heart of the book: Given the rise of algorithmic decision
making, the ability to outsource tasks to the crowd, and such technologies as
blockchain, will the corporation as we know it become obsolete? As transaction
costs fall, after all, the reasons to put everything under one corporate roof
become less important, and it should become easier for groups of people to come
together (virtually) to solve a problem without bosses or formal hierarchies.
And yet, as McAfee and Brynjolfsson argue,
big companies don’t seem to be on their way out. Instead, by some measures,
they’re more powerful than ever — especially in the tech world. And the
companies that have been most successful at trying to drive new technologies
also tend to look a lot like traditional companies.
So what gives? Some of these apparent
contradictions have to do with the predictability and efficiency of having
everyone connected to the same organization — which also makes it easier to
obtain long-term commitments to new projects. But what’s also essential, Machine,
Platform, Crowd argues, is that management matters and management
creates value — from the CEO down to the much-maligned middle manager. That’s
because if you want to get things done, leadership still matters. Organization
still matters. And helping people work together smoothly and efficiently still
matters.
This doesn’t mean that companies will go back
to the traditional top-down, command-and-control model. On the contrary, McAfee
and Brynjolfsson find, the best managers tend to be egalitarian — they
listen to and take seriously ideas from people throughout the organization. And
they also tend to be cognizant of their own decision-making limitations, open
to using machines and crowds in helping inform their choices, and transparent
in the way they share information. But their core job — managing people — is
still much the same. Even as the world around it changes, the company, it turns
out, is an innovation that endures.
by James Surowiecki
https://www.strategy-business.com/article/Best-Business-Books-2017-Innovation
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