Sunday, June 25, 2017

Early Indications June 2017 Review essay: Scale by Geoffrey West

Review Essay: Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies by Geoffrey West

Why are things the size they are? That is, why can’t a mammal be as small as an ant? Why are cities, social and kinship networks, and elephants not 100 times their current sizes? Why are school districts, park districts, policing areas, statistical metropolises, and counties sized a) as they are and b) not consistently or uniformly? Finally, why and when do things stop growing and when do they die?

Geoffrey West trained as a theoretical physicist, migrated into biology, and then pursued network analysis of things, people, and places. Scale is a great book: West is asking important questions, at a broad scale, in almost complete opposition to current academic tendencies toward hyper-specialization. Further, the answers to the questions are not of arcane interest, as one would expect from a theoretical physicist. Instead, a parent who today gives birth to an infant who will likely have a life expectancy of about 100 years (given some early breaks in the right direction) should be asking the same ones on behalf of the newborn:

-Where does planetary population doubling each its limit?
-How fast will humans run out of critical natural resources, whether water, titanium, or animal protein?
-Will science crack the code of human aging?

For all the potency of West’s big questions, he brings plenty of fascinating new answers to this book. Indeed, the science of scaling has advanced extremely rapidly in just 20 years or so, providing tantalizing insights into the essential nature of many natural and human-made phenomena alike. All mammals have a life span of about the same number of heartbeats. The network structure of tree branches and the human aorta share mathematical proportions and relationships. Similarly, the networks underlying biology and urban infrastructure such as electricity and plumbing are uncannily similar, down to their exponent. The book is full of such causes for wonder.

The book’s chapter on the “science” of companies was for me the weakest link. As West states, streets and sewers don’t make cities: people do. Thus he wonders why cities don’t “die” the way whales or companies do, but companies aren’t organic: they are humanly created entities designed to fit within tax codes, government regulations, artificial geographic boundaries, and other constraints. Imagine one nation that requires companies to pay dividends to shareholders, for example. A second country that allows Amazon-like reinvestment of profits will give rise to very different business practices and structures. Change a parameter like differential voting rights of shares (as at Google/Alphabet), taxation of offshore profits (as at Apple), or capital requirements (JP Morgan), and once again, the “metabolism” of the corporate body will change markedly. Given the extensive and malleable artifices within which they operate, to liken a company to an organic life form is a quest with limited utility.

The material on cities, however, is compelling and original, at least to me (an admitted non-student of urbanist scholarship). I hadn’t realized the sheer velocity of global migration to cities, for one thing: over the next 35 years, he asserts, 1.5 million people will be urbanized every week. The other stunning discovery, to me, was that the increasing size of cities scales reliably with the speed of city life. That is, spatial density changes the experience of time. Finally, the analytics behind a predictive model that addresses such variables as crime, patent creation, and disease as a function of population are thoroughly impressive. This model gains some of its power by drawing on the literature of complex adaptive systems, as befits a senior member of the Santa Fe Institute: cities and bacteria are remarkably similar fractal structures, for example, as are flow rate maps of trucks from central distribution hubs and cardiovascular arteries. Similarly, West’s analysis of cities by their “metabolism” (energy use) is enlightening and concerning.

West did not write Scale to be beach reading, or to generate buzzwords with a half-life of a few months. Rather, the scaling of the planet will require more and more frequent game-changing innovations that reset the field of play (life is speeding up, remember?). The printing press and the steam engine were introduced about 300 years apart; the personal computer and the smartphone hit mass markets about 30 years apart. What will be the next innovation with Internet-sized impact? Given the impending global population increase to 9 billion people, West argues we need something in the next two to three decades, and then another breakthrough about 25 years after that. The relentlessness of superexponential growth curves was well summarized in a puzzle: If we have a bacterium that doubles its volume every minute, and it starts doubling from a single cell at 8:00 am with the goal of filling a 2 liter container by noon, at what point is the vessel half full? The answer is nowhere near 10:00 am but instead 11:59; consider that the vessel will be only 1/32 full at 5 minutes to noon. 

Thus West, in my experience, successfully resets the reader’s worldview, giving the current scattered and underpowered efforts at “sustainability” new urgency. “Continuous growth and the consequent ever-increasing acceleration of the pace of life have profound consequences for the entire planet,” West states in his conclusion. The rate of change “is surely not sustainable, and if nothing changes, we are heading for a major crash” of a sort we’ve never seen before (p. 425). Given the current lack of broad mathematical literacy (West’s book is equation-free but you have to grasp logarithmic scales), however, it’s hard to say who will read this and change his or her mind.

Before I started the book, I was thinking about scale in a different realm: representative democracy. Just as banks grew “too big to fail,” have modern democratic nation-states become too big to govern? Consider the House of Representatives: in 1804, a Congressman represented, on average, about 40,000 people. Today, the average California Congressional delegate represents 677,000 people: an impossible number. Both by objective counts of bills passed and opinion polls, the U.S. Congress is not working for its people. The European Union is hardly a robust counter-example; China is run, to the degree it has its successes, under completely different principles.

Thus the two scale cases reinforce each other in a particularly unfortunate feedback loop. At the time when science needs to be multidisciplinary, multinational, and theoretically rigorous and predictive (in a way the social sciences have rarely ever achieved), we have a system of governance that generally devalues science and scientists, balkanizes constituencies within and across nations, and accelerates rather than decreases energy intensiveness: think of how much energy is used to pump water to Los Angeles, or to cool Phoenix, or to power all the cars in metro New York. At the same time, changing climate means higher water levels, changing crop yield patterns, and new winners (ships that use the North Pole to cut transit time) and losers (many ski resorts are already rebranding as snowfalls decrease and become less predictable). If anything, as urgently and eloquently as he makes his case, West’s concern is understated to the extent that legislative gridlock, remove from constituents, and symbolic agendas render government largely incapable of leading (or even following) the discussion that needs to happen sooner than later.

Tuesday, May 30, 2017

Early Indications May 2017: Education for a world of bits + atoms

The physical world and the digital world are converging. 2-d bar codes and RFID tags serve as physical hyperlinks, connecting a physical object to its digital data heritage. Amazon merges deep data expertise with unparalleled physical logistics to promise same-day delivery in some areas. The so-called Internet of Things connects sensors on physical devices to powerful data analytic capability to increase fuel efficiency, prevent unexpected breakdowns, and smooth traffic flows. Waze, Uber, Airbnb, and many other startups are building new business models at the intersection of mobile apps and the cars, houses, and other attributes of private citizens.

The changes wrought by this combination of digital and physical attributes will be massive. My distinguished engineering colleague Monty Alger suggests two big buckets: 
1) Disruptive innovation, in which incumbents are attacked from outside their traditional competitive realm. Content industries are already in disarray: record labels from MP3s and streaming, newspapers from Google and Facebook, non-sports television from streaming, etc. Looking ahead, who knows what Google + Lyft could do to GM in time-shared autonomous electric vehicles, for example? 
2) New economies of scale and scope as digital expertise with big data and hyper-scale infrastructure encounter metal-benders and other traditional “atoms” companies. Again, recent history is instructive: Facebook photos vs Kodak; Google searches vs library reference desks; Uber’s 1.5 million drivers vs Kelly Services, the former with 3x the number of contractor/workers and 1/7 the longevity. 

We will soon see more companies or other organizations that dwarf the giants of the 20th century: AT&T, IBM, Exxon Mobil, GM. A recent example: last week Peloton achieved “unicorn” status with a $1 billion+ valuation. Its innovation is a $2000 connected stationary bike that lets people join unlimited spin classes (for $39 per month) from their homes. Note that Dorel, Trek, ASI, QBP, and the rest of the traditional bike world were absent from the effort.

How is this combined world different?

This world of bits + atoms has many characteristics that distinguish it from the world of only a few years ago. First, the speed of change has never been so rapid. Uber is valued at $69 billion (bigger than GM and Lockheed Martin, and about the same size as Goldman Sachs) after less than eight years of operation. Nokia and Research In Motion lost the global lead in smartphones, becoming irrelevant in less than five years after the launch of the iPhone. Instagram was acquired by Facebook for $1 billion in 2012, two years after being founded but with 200 million users and only about a dozen employees.

Second, innovations are building on each other; we now have a set of building blocks that can be reconfigured. Tiny high-resolution digital cameras, created by the millions for smartphones, can be used in game consoles, robots, or medical applications. GPS finds its way into everything from missile systems to social network games. The same machine learning algorithms that helped a Google company beat a Go grandmaster are being used to manage energy consumption in the parent company’s data centers.

Third, more and more domains look like Wall Street: sub-second algorithmic trading governs mobile ad placement, while high-speed digital markets are coming into play in energy markets and even at Amazon, where items can change price multiple times a day. (See this story.) Few companies are ready to manage such speeds and volumes of market information, much less to respond accordingly.

Skills shortages

The talent needed to invent, manage, and succeed in this world is scarce. The CEO of Symantec predicts there will be 6 million cybersecurity jobs in the global market by 2019, with a quarter of them going unfilled. (One scary implication: the already pathetic state of Internet of Things security will get worse.) Digital tools are becoming more prevalent at all levels of manufacturing, and many entry-level employees currently lack the skills to use CNC machines, 3D printers, and workflow automation software. Looking ahead, robot programming is beyond nearly all industrial employees, even engineers with graduate degrees. But given the speed of digital disruption, internships and entry-level hires often serve to perpetuate the skills gap rather than close it as companies recruit new workers who look a lot like the existing ones. “Big data” is a case in point: many job postings ask for a worker the existing managers cannot define, so buzzwords can replace concrete skills, software packages, and work achievements in the interview, with predictable results.

College curricula are lagging farther and farther behind. Pure bits people in computer science are doing well, as are students with pure atoms skills in domains such as hospitality management or fitness instruction. In the middle -- where many engineering fields, several business majors, and, increasingly, the hard sciences are being challenged to integrate physical and digital processes – several factors combine to prevent learning innovation to address the skills shortfall.

First, curriculum change is shepherded by the very people who succeed under the current regime. Time after time, bold changes get abraded and segmented in committee, and the outcome is incremental shifts to existing turf, fiefdoms, and reward systems. Second, in a research-driven university, professors with grants and publication hurdles often teach what they know and are investigating (push) rather than what companies are figuring out they need to hire (pull). Related to this mismatch, real-world challenges rarely align with academic silos, and interdisciplinary problem-based instruction is rare. Finally, many students bear responsibility for not digging deep or hard enough into their prospective fields of employment until an internship after the junior year, far too late to fine-tune the shape of a major, or to get mentoring in that field. If students don’t know what they need to succeed in the market, professors aren’t incented to know, and company recruiters screen for younger versions of themselves, the status quo gets perpetuated further.

What about STEM, you might ask? Parents, governors, and lobbyists from many corners of the economy hope to improve how the U.S. trains and measures its primary and secondary students. We have computers in more classrooms, Internet connections to most schools, and, slowly, teacher training to make instruction better. Certainly education in quantitative reasoning needs to improve to prepare students for the many complexities posed by the intersections of bits and atoms. But STEM programs, or even STEAM (including the arts) efforts, are necessary but not sufficient.

Because of the mixing of the physical and digital domains, and the increasing speed of change, skills for what some are calling “hybrid jobs” are proving to be in short supply. How many engineers can prepare a project budget that accounts for spare parts, currency effects, and price volatility in raw materials? How many programmers can manage a team? It used to be that only senior executives needed to learn cross-domain skills: marketers learned data analytics when a new division was acquired, engineers learned finance when they got promoted to run a line of business, statisticians learned interviewing techniques as they became responsible for instrument design, not just scoring. But no longer is it a mid-career transition to learn outside one’s educated domain. Now, even entry-level employees must cross disciplines, understand different cultures, and merge “soft” and “hard” skill sets.

Where in college or university does this happen? The notion of general education distribution requirements, in theory, should allow biologists to study materials science or architecture, or roboticists to study psychology. In practice, the combination of loose requirements, student convergence, and minimal incentive for interdisciplinary faculty collaboration means that students learn little outside their major. In one college of business, the two most popular general education courses were introductions to astronomy and to the history of popular music. You can guess the average grade earned in these courses.

Consider the field of robotics as a counterpoint. On a self-driving car team, in humanoid robotics, and in factory automation, the following disciplines intermingle:
  • computer science (architectures and programming)
  • metallurgy (what can we make this piece from?)
  • physics (lidar)
  • electro-optics (machine vision)
  • material science (batteries)
  • mechanical engineering (how can we make the bot strong and light?)
  • psychology (how do co-workers understand the robot? How does the robot signal its co-workers?)
  • math (path planning is highly complex).

That astronomy course isn’t doing anyone a favor in this marketplace.

What do we propose instead?

Let us begin with a list of objectives, then propose possible ways to achieve them.

1)    Education cannot be confined to the traditional K-12, 2-yr college, 4-year college, masters degree, Ph.D. model.
2)    Students (who can be defined as anyone with need and desire to learn) will need to learn or re-learn what they need close to when they need it.
3)    Students need to learn how to learn over a lifetime, how to express themselves in various ways (words, numbers, animations/simulations, videos, etc), and how to assess the validity and quality of both argument and evidence (classic critical thinking). That is, the core of a liberal arts education has never been more necessary.
4)    Students need both hard skills and soft skills, and the ability to tell when each is applicable.
5)    Students need to learn self-awareness, both to manage their contributions to a team and to frequently reposition themselves relative to workforce demands and opportunities.
6)    Students need to learn the differences between skills advancement in a particular domain and skills integration across domains, and how each is to be achieved.

The ultimate solution to this wish list is a decade or two away. In the interim, we propose as a starting point a model of integrated education that uses student internships as a test bed for industry-student-university collaboration. (Details are being worked out this summer.) Going forward, we foresee a model of integration moving across university departments and even colleges, in line with the robotics example noted above: when companies seek skills rather than majors, the university will have to respond with new course design and delivery models, new skills certification practices, and new funding streams. Those are outside the scope of the initial project, but we feel it is important to position the integrated internship as the initial step in a long, fundamental transition that more adequately supports the need of a global economy, our students and graduates, and the employers who will hire them.

Sunday, April 30, 2017

Early Indications April 2017: A Great Deflation?

In agricultural and industrial economies, price inflation has historically been a major concern. High interest rates make borrowing money, for everything from housing to highways, unappealing or impossible. Rising prices for essentials force more and more people on society’s margin to choose between heating oil and food, literally or figuratively. Business planning and government administration become difficult when the future picture is fuzzy. In extreme cases like present-day Venezuela, where prices rose 741% in the year to February, the country becomes nearly ungovernable.

In the U.S., the official inflation rate has been 2.1% or lower seven of the past eight years, including years of -.4% and .1%. My starting point for this newsletter was a chart of prices over the 1996-2016 span by the economist Mark J. Perry of the American Enterprise Institute. He shows that college tuition far outran any other economic good in its 20-year cost increase, while new cars held pretty steady and televisions got significantly cheaper. 

If we look back to about 1985, wages for middle-income U.S. earners have been stagnant, so low overall inflation is not a surprise. One reason companies can re-shore factories is that U.S. labor is pretty cheap, by global standards, especially if health benefits are somehow removed from the calculation. One way to do this is use automation, getting more work per human (and insured) employee. Thus the current boom in US manufacturing plants benefits from a lot of advanced manufacturing technology: over the past five years, Rockwell Automation (which makes assembly lines and related stuff) has seen its share price shoot from $62 to $157.


Moore’s law and technology economics more generally — such as mass production of smartphone camera sub-assemblies — are partially responsible for some of this price compression, but not all of it. One example: the Apple II sold in 1977 for the equivalent of 5100 current USD. Globalization (including low offshore manufacturing wages and the low costs of containerized ocean freight) is absolutely in play, but again, is only part of the answer. 

Consider toys. The original Barbie cost about $23 (2011 dollars) at its launch in 1959. Wal-Mart currently sells at least three different versions of the doll, without accessories, for $5 apiece. And while televisions have come down in price, cable TV service costs have skyrocketed, in part driven by rights holder fees: subscribers pay more to Comcast, which pays more to ESPN/Disney (and adds players like Food Network and other new channel providers), and ESPN bids up the price for sports rights from leagues and college conferences. The average monthly revenue per Comcast user in 2001 was $35; it’s now nearly $84.

Cars are complicated because apples-to-apples comparisons are impossible. A 2017 model has features including stability control, remote tire pressure monitoring, Bluetooth, and the like that have no counterpart on a 1967 or 1987 model. Also, even the same model is typically bigger and heavier over time: a 2017 Honda Accord is about 8 inches longer and 400 lb heavier than its 1990 predecessor. A standard-configuration Ford F-150 pickup in 1990 was a foot and a half shorter than today’s equivalent and had almost exactly half the horsepower. Are cars getting cheaper? Counting parking, insurance, and the like, most certainly not. But there’s increased content to the vehicle as well.

And the story gets even more complex, Energy, for example, was priced historically low in 2016 as natural gas far underpriced coal, with or without Obama-era EPA standards factored in. One estimate suggested a generation switchover point from coal to gas at about $2.50 per million BTUs of gas; in March 2016 the price hit a low of $1.64, but 13 months later, the price has doubled to $3.19. Power generators must balance a portfolio of generation and storage options, at the same time that alternative energy is quietly but rapidly making an impact. Last December, Texas used wind power for 40% (or more) of its power for 17 hours straight, while California met 40% of its power needs with solar for three hours on March 11 of this year. Electric rates momentarily turned negative on the wholesale exchanges, in part because a wet winter is helping hydro plants run at high levels of output. Thus it’s impossible to say there’s large-scale price depression in electricity, but clearly downward price pressure is a factor in specific locales.

Digital deflation

Moving back into digital markets, think of all the free content we get via the Internet. Each of the following is a source of deflation and, importantly, job loss:

  • news
  • investment information
  • music (compared to $16 CDs)
  • streaming video (Amazon’s Prime is not technically free, but psychologically Prime membership is a sunk cost)
  • tech support, training, instruction (how many things can YouTube NOT teach you to do?)
  • reference services
  • maps.

Michael Dell famously lowered prices across the PC sector 20 years ago when his company applied supply-chain efficiencies to the segment. His successor in margin destruction, Jeff Bezos, has affected the value and service expectations of tens of millions of shoppers (including those in the market for Dell’s servers who now buy cloud computing instead). Publishing and bookstores are obvious victims; now the focus is on mall retailers, who are dropping by the wayside on a nearly weekly basis.


Again, it’s not a simple story. The U.S. has substantially more retail real estate, measured on a per capita yardstick, than any other country on earth: at about 24 square feet per person, that’s twice as big as Australia (#2 on the list) and six times the space of the UK. Correction was inevitable, and enclosed malls are a common starting point. With department store consolidation, there are fewer potential anchor tenants, especially as Sears, a common standard-bearer, publicly expresses doubt it can remain afloat. Sporting goods has been hit hard as Sports Authority closed 423 stores while shutting down operations and outdoor specialist Gander Mountain filed for bankruptcy in March. In apparel, Bebe will close all stores by the end of next month, following the lead of Payless Shoesource. Credit Suisse projects a total of 8,600 U.S. store closings this year, which would be an all-time record.

Consumer electronics is an already-difficult category to win in, with the luxurious high-touch Apple Store at the top of the segment and Amazon and Wal-Mart hammering prices downward at the bottom. If you’re Best Buy or Staples in the middle, what can you do? After they reset the electronics market, Amazon has emerged as the #2 U.S. apparel merchant, barely trailing Wal-Mart according to Morgan Stanley estimates. The company is adding its own brands of men’s and women’s clothing, I’ve noticed, following its Amazon Basics electronics accessories and store-brand snack foods. In the stationary store category, Office Depot already merged with Office Max, while Staples lost half a billion dollars last quarter and is closing 70 stores on top of 242 locations shut down in the prior two years. As big as Amazon is, and as fast as it is growing, there are still many categories where it could increase its imprint. Thus far it has only scratched the surface of grocery, and big-box home centers seem, for the moment, to be faring reasonably well: a gallon of paint is a tough item for online retail, as is a wheelbarrow or sheet of plywood.

The big picture

Thus we have a story with very different messages for different populations. Amazon investors continue to bid its share price up at the same time that truly good local bookstores are continuing to survive and thrive long after Borders went away. As mobile telephony replaced wirelines, AT&T and Verizon shed tens of thousands of jobs while nobody seemed to notice. And when L.L. Bean wants to increase production of its signature leather/rubber boots in the U.S., finding both skilled labor and onshore suppliers constrains production: 50 years ago, 98% of shoes worn by U.S. consumers were made here. 

Yet as Noah Rothman notes in a recent article, job losses in declining industries sometimes make for potent political theater. President Trump has focused on coal mining, which employs only about 16,000 “extraction workers or helpers,” according to BLS data quoted in the Washington Post. More generally, the St. Louis Federal Reserve Board counted 65,000 coal workers in 2015. Whatever the number, consider how much more potential political attention might be devoted to disappearing retail clerks and salespeople, whose ranks number in the 14 million range — about one job in ten in the U.S. Like miners, many retail workers — about a quarter of hourly retail employees, according to one estimate — live close to the poverty line. What will be the dominant narrative? A) Efficiency and convenience benefit enough people that a lost Circuit City or Bebe or Sears isn’t widely mourned. B) The enclosed mall was an American social center (rather than a blip in the long history of public space), and the shopping experience deserves to be propped up somehow even as demand for that experience is plummeting.

Deflation is a complex business. The customer benefits of falling prices or “free” stuff often have a social cost, in part of inefficiently designed business processes populated by working people who lose their jobs through “structural dislocation” or some such abstraction _that isn’t their fault_. In some cases, technological improvements deliver a free lunch, saving time, money, and worker dignity or some version thereof. Elsewhere, we see very long cycles in play: Britain recently witnessed its first day with no goal-generated electricity since the 1880s. 

Who’s next? As Mark Perry noted at the beginning of this note, higher education is prime for a reset. Local teacher and police pensions are bankrupting some municipalities. The common thread is government involvement: how often have we seen public goods be disrupted, with significantly lower costs passed through to customers, the same way that commercial innovations like containerization, Moore’s law, or air travel have lowered prices of formerly expensive goods or services? Should it actually happen, the deflation of the bureaucratic state could be one of the biggest stories of the 21st century.

Sunday, February 26, 2017

Early Indications February 2017: B2B Websites a year later

A year ago this month I published the results of a survey of 100 business-to-business websites. (You can review those findings here.) I recently repeated the exercise, staying with the 100-company sample rather than expanding to 250 as I had planned. While there were no shocking surprises, year-over-year trend data suggests some unexpected 
macro directions.

I. What stayed the same

The companies that used video well (Corning, Haas machine tools, Bobcat) are still relatively lonely as front-runners. Given the complexity of many B2B applications, training and troubleshooting videos were relatively rare despite many potential use cases. (Schneider Electric has more than 200 vendor-neutral training videos and certifications in their “Energy University.”) While many companies post corporate overview videos, these were generally of little concrete help and long on a “Successories”-inspired aesthetic in both aural and visual look and feel.

Many good site architectures were the same — there’s no compelling reason why something that works well would need to be overhauled on an annual basis. Leaders here included Cisco, GE, Caterpillar, NXP semiconductors, and Rockwell Automation.

Very few websites included live chat, something I see as essential if a company is dealing with a) millennials or b) loud shop floor customer service scenarios. There was a modest rise in adoption over the year, but it’s still a tiny minority.

Customer value propositions were striking in their rarity. This bothered me more last year: in many cases this time around, the website is addressing so many constituencies (including investors, retirees, and recruits) that a customer focus may legitimately be more appropriate deeper in the site. I’ll say more about this later.

Many sites still presume a desktop user who can print long PDF product catalogs, rather than support mobile-first product data functionality. 

Most sites were organized by corporate org charts (industries, geographies, functional areas) rather than by customer questions. Similarly, many questions were answered by “call your sales representative or local dealer.” There are times when this process makes sense, but there are also instances in which the past default is carried forward solely by institutional inertia rather than using new technologies and behaviors to reinvent customer service from the outside looking in.

II. What changed?

Operational execution has improved. Many sites I had compiled into a list of “Don’ts”  were relaunched in 2016, while others got facelifts. Genuine howler-class errors were hard to find (minor chuckle: one paper company wished everyone a happy Chinese New Year in the year of the “roaster.”) Some sites haven’t been updated in nearly 15 years (hello Nutrasweet), but generally, content was relatively fresh, social media posts were rarely stale, and overall execution was solid, albeit from a Web-centric perspective. Only a small minority of sites (7%) were not mobile-friendly, down from a third last year, and of those 7, at least one (DHL) is in the midst of a site re-launch that addresses the mobile user quite well.

Apart from that, little changed dramatically in terms of site features, customer access, or integration with other marketing functions, particularly trade shows. The change that most interested me was more qualitative, a gradual migration of the online presence from being a storefront to being a broader window into the company. To oversimplify, I see a shift in many B2B sites from online commerce to digital business more broadly conceived. 

Part of this transition is a subtle shift in emphasis: plenty of companies have had “jobs” buttons or  tabs on their websites since day 1. Stock prices are not new additions to many front pages. Fedex has provided package tracking since the early days of their site. I do feel, however, that the best B2B websites I saw provided a richer representation of what the company _is_ (rather than “sells”) than in my past experience; your mileage may vary. One data point I’m watching: hardcore engineering-driven companies including GE and Parker Hannifin linked to Pinterest for the first time that I’ve seen.

This more holistic representation might be a function of the need to attract millennial recruits. In B2B especially, selling microprocessors, ball bearings, or industrial lubricants is not intrinsically appealing to people who typically lack familiarity with the industries and scenarios in which those products are used. Then to compound the difficulty of recruiting college students, many B2B websites were, to be charitable, limited in their digital adeptness. Thus students were being asked to help market products they didn’t use, understand, or relate to, using trade shows, newsletters, paper catalogs, and 50-something sales reps. Thus, my hypothesis goes, some of the increased use of social media, online video, and smartphone apps by B2B marketers is driven by a) younger staff and/or b) the recognition of the need to attract younger staff.

It’s no surprise that web presences appeal to investors: CEOs get paid not for selling widgets but for selling the stock. In chemicals in particular (Air Liquide, Dow, BASF, Henkel), I saw significant attention paid to investors, far more (at the top level of site organization) than to customers. In many more cases, the front page was a mixture of missions. Carried out well, such a heterogeneous approach gave a holistic sense of a company. Carried out poorly, it was design-by-committee without a central organizing design theme, organizational logic, or navigational rubric. 

An example of the former can be found at DB Schenker, a German logistics provider. News items related to the logistics industry, a corporate acquisition, and environmental impact all appear, alongside a conference invitation. The rotating photos “above the fold” relate to a new facility on the US-Mexico border, a smartphone app, careers, cargo insurance, and an outdated piece from November on holiday shipping and the retail sector. Thus multiple functions (public relations, investor relations, HR/recruiting, marketing, and sales) are represented, along with database connections to operations for shipment initiation and tracking.

In many ways, we are heading “back to the future,” to the e-business days of 20 years ago. Looking at B2B sites from 1996 in the Internet Archive’s Wayback Machine reminded me that much like today’s millennials, some companies were “born digital” while others migrated to this way of doing business. Thus Cisco’s embedding of business processes in digital backbones represents a different ethos, investment landscape, and demographic than does most B2B companies’ migration. As more paper/analog-based executives retire, as digital content platforms improve, as interactive agencies understand the uniqueness and complexity of B2B, and as mobility forces a re-architecting of many companies’ online presence, I believe the survey results in 2020 will look significantly different.

For all this conventional talk about a gradual evolution, however, there is major change afoot: many industries are embracing and/or struggling with the notion of embedded, networked sensors and actuators populating massive data stores of machine-to-machine traffic, the so-called “Internet of Things.” This new emphasis is probably the biggest change I saw between 2016 and 2017. It isn’t literally true that every company I surveyed had IoT on the front page, but it was WAY more common than just a year ago. Most accounting and consulting firms are highlighting it, as are industrial controls companies like Rockwell, infrastructure providers including Belden (which has an IoT phone conference scheduler on the front page) and power systems companies, hardware companies such as Cisco and Intel, and analytics software providers led by SAS and SAP. Thus market trends (along with the aforementioned demographics) will drive “digital nativism” deeper into the corporate hierarchy of many companies, demanding cross-functional collaboration, intelligent risk awareness and mitigation, new privacy policies and processes, and operational integration in something close to real time. Given the ever-expanding IoT market size estimates for 2020 (now in the hundreds of billions of dollars), I know what I’ll be watching for doing the next web census in 2018.