This is a recent podcast in which Lou Zacharilla, co-founder of the Intelligent Community Forum, interviewed me about how communities prosper in this century.
© 2018 Norman Jacknis, All Rights Reserved
This is a recent podcast in which Lou Zacharilla, co-founder of the Intelligent Community Forum, interviewed me about how communities prosper in this century.
© 2018 Norman Jacknis, All Rights Reserved
This year I created a new, week-long, all-day course at Columbia University on Strategy and Analytics. The course focuses on how to think about strategy both for the organization as a whole as well as the analytics team. It also shows the ways that analytics can help determine the best strategy and assess how well that strategy is succeeding.
In designing the course, it was apparent that much of the established literature in strategy is based on ideas developed decades ago. Michael Porter, for example, is still the source of much thinking and teaching about strategy and competition.
Perhaps a dollop of Christensen’s disruptive innovation might be added into the mix, although that idea is not any longer new. Worse, the concept has become so popularly diluted that too often every change is mistakenly treated as disruptive.
Even the somewhat alternative perspective described in the book “Blue Ocean Strategy: How to Create Uncontested Market Space and Make Competition Irrelevant” is now more than ten years old.
Of the well-established business “gurus”, perhaps only Gary Hamel has adjusted his perspective in this century – see, for example, this presentation.
But the world has changed. Certainly, the growth of huge Internet-based companies has highlighted strategies that do not necessarily come out of the older ideas.
So, who are the new strategists worthy of inclusion in a graduate course in 2018?
The students were exposed to the work of fellow faculty at Columbia University, especially Leonard Sherman’s “If You’re in a Dogfight, Become a Cat! – Strategies for Long-Term Growth” and Rita Gunther McGrath’s “The End Of Competitive Advantage: How To Keep Your Strategy Moving As Fast As Your Business”.
But in this post, the emphasis in on strategic lessons drawn from this century’s business experience with the Internet, including multi-sided platforms and digital content traps. For that there is “Matchmakers – the new economics of multisided platforms” by David S Evans and Richard Schmalensee. And also Bharat Anand’s “The Content Trap: A Strategist’s Guide to Digital Change”.
For Porter and other earlier thinkers, the focus was mostly on the other players that they were competing against (or decided not to compete against). For Anand, the role of the customer and the network of customers becomes more central in determining strategy. For Evans and Schmalensee, getting a network of customers to succeed is not simple and requires a different kind of strategic framework than industrial competition.
Why emphasize these two books? It might seem that these books only focus on digital businesses, not the traditional manufacturers, retailers and service companies that previous strategists worked at.
But many now argue that all businesses are digital, just to varying degrees. For the last few year we’ve seen the repeated headline that “every business is now a digital business” (or some minor variation) from Forbes, Accenture, the Wharton School of the University of Pennsylvania, among others you may not have heard of. And about a year ago, we read that “Ford abruptly replaces CEO to target digital transformation”.
Consider then the case of GE, one of the USA’s great industrial giants, which offers a good illustration of the situation facing many companies. A couple of years ago, it expressed its desire to “Become a Digital Industrial Company”. Last week, Steve Lohr of the New York Times reported that “G.E. Makes a Sharp ‘Pivot’ on Digital” because of its difficulty making the transition to digital and especially making the transition a marketing success.
At least in part, the company’s lack of success could be blamed on its failure to fully embrace the intellectual shift from older strategic frameworks to the more digital 21st century strategy that thinkers like Anand, Evans and Schmalensee describe.
© 2018 Norman Jacknis, All Rights Reserved
We hear and read how the very largest cities are growing, attractive places for millennials and just about anyone who is not of retirement age. The story is that the big cities have had almost all the economic gains of the last decade or so, while the economic life has been sucked out of small towns and rural areas.
The images above are what seem to be in many minds today — the vibrant big city versus the dying countryside.
Yet, we are in a digital age when everyone is connected to everyone else on the globe, thanks to the Internet. Why hasn’t this theory of economic potential from the Internet been true for the countryside?
Well, it turns out that it is true. Those rural areas that do in fact have widespread access to the Internet are flourishing. These towns with broadband are exemplary, but unfortunately not the majority of towns.
Professor Roberto Gallardo of Purdue’s Purdue Center for Regional Development has dug deep into the data about broadband and growth. The results have recently been published in an article that Robert Bell and I helped write. You can see it below.
So, the implication of the image above is half right — this is a life-or-death issue for many small towns. The hopeful note is that those with broadband and the wisdom to use it for quality of life will not die in this century.
© 2018 Norman Jacknis, All Rights Reserved
[This article is republished from the Daily Yonder , a non-profit media organization that specializes in rural trends and thus filling the vacuum of news coverage about the countryside.]
April 11, 2018
When they live in remote rural areas, millennials are more likely to reside in a county that has better digital access. The findings could indicate that the digital economy is helping decentralize the economy, not just clustering economic change in the cities that are already the largest.
Sources: USDA; Pew Research; US Census Bureau; Purdue Center for Regional Development This graph shows that the number of Millennials and Gen Xers living in the nation’s most rural counties is on the increase in counties with a low “digital divide index.” The graph splits the population in “noncore” (or rural) counties into three different generations. Then, within each generation, the graph looks at population change based on the Digital Divide Index. The index measures the digital divide using two sets of criteria, one that looks at the availability and adoption of broadband and another set that looks at socio-economic factors such as income and education levels that affect broadband use. Counties are split into five groups or quintiles based on the digital divide index, with group №1 (orange) having the most access and №5 (green) having the lowest.
Cities are the future and the countryside is doomed, as far as population growth, jobs, culture and lifestyle are concerned. Right?
Certainly, that is the mainstream view expressed by analysts at organizations such as Brookings. This type of analysis says the “clustering” of business that occurred during the industrial age will only accelerate as the digital economy takes hold. This argument says digital economies will only deepen and accelerate the competitive advantage that cities have always had in modern times.
But other pundits and researchers argue that the digital age will result in “decentralization” and a more level playing field between urban and rural. Digital technologies are insensitive to location and distance and potentially offer workers a much greater range of opportunities than ever before.
The real question is whether a rural decline is inevitable or if the digital economy has characteristics that are already starting to write a different story for rural America. We have recently completed research that suggests it is.
While metro areas still capture the majority of new jobs and population gains, there is some anecdotal evidence pointing in a different direction. Consider a CBS article that notes how, due to high housing costs, horrible traffic, and terrible work-life balances, Bend, Oregon, is seeing an influx of teleworkers from Silicon Valley. The New York Times has reported on the sudden influx of escapees from the Valley that is transforming Reno, Nevada — for good or ill, it is not yet clear.
Likewise, a Fortune article argued that “millennials are about to leave cities in droves” and the Telegraph mentioned “there is a great exodus going on from cities” in addition to Time magazine reporting that the millennial population of certain U.S. cities has peaked.
Why millennials? Well, dubbed the first digital-native generation, their migration patterns could indicate the beginning of a digital age-related decentralization.
An Age-Based Look at Population Patterns
In search of insight, we looked at population change among the three generations that make up the entire country’s workforce: millennials, generation X, and baby boomers.
First, we defined each generation. Table 1 shows the age ranges of each generation according to the Pew Research Center, both in 2010 and 2016, as well as the age categories used to measure each generation. While not an exact match, categories are consistent across years and geographies.
In addition to looking at generations, we used the Office of Management core-based typology to control by county type (metropolitan, small city [micropolitan], and rural [noncore]). To factor in the influence of digital access affects local economies, we used the Digital Divide Index. The DDI, developed by the Purdue Center for Regional Development, ranges from zero to 100. The higher the score, the higher the digital divide. There are two components to the Digital Divide Index: 1) broadband infrastructure/adoption and 2) socioeconomic characteristics known to affect technology adoption.
Looking at overall trends, it does look like the digital age is not having a decentralization effect. To the contrary, according to data from the economic modeling service Emsi, the U.S. added 19.4 million jobs between 2010 and 2016. Of these, 94.6 percent were located in metropolitan counties compared to only 1.6 percent in rural counties.
Population growth tells a similar story. Virtually the entire growth in U.S. population of 14.4 million between 2010 and 2016 occurred in metropolitan counties, according to the Census Bureau. The graph below (Figure 1) shows the total population change overall and by generation and county type. As expected, the number of baby boomers (far right side of the graph) is falling across all county types while millennials and generation x (middle two sets of bars) are growing only in metro counties.
But there is a different story. When looking at only rural counties (what the OMB classification system calls “noncore”) divided into five equal groups or quintiles based on their digital divide (1 = lowest divide while 5 = highest divide), the figure at the very top of this article shows that rural counties experienced an increase in millennials where the digital divide was lowest. (The millennial population grew by 2.3 percent in rural counties where the digital divide was the lowest.) Important to note is that this same pattern occurs in metropolitan and small city counties as well.
Impact on the “Really Rural” County
“Urban” and “rural” can be tricky terms when it comes to demographics. The Census Bureau reports that 80% of the population lives in urban areas. Seventy-five percent of those “urban” areas, however, are actually small towns with populations of under 20,000. They are often geographically large, with a population density that falls off rapidly once you leave the center of town.
On the other hand, some rural counties are adjacent to metro areas and may benefit disproportionately from their location or even be considered metropolitan due to their commuting patterns. Because of this, we turned to another typology developed by the U.S. Department of Agriculture Economic Research Service that groups counties into nine types ranging from large metro areas to medium size counties adjacent to metro areas to small counties not adjacent to metro areas.
Figure 3 (below) shows counties considered completely rural or with an urban population of less than 2,500, not adjacent to a metro area. Among these counties, about 420 in total, those with the lowest digital divide experienced a 13.5 percent increase in millennials between 2010 and 2016. In other words, in the nation’s “most rural” counties, the millennial population increased significantly when those counties had better broadband access.
Sources: USDA; Pew Research; US Census Bureau; Purdue Center for Regional Development. This graph shows population change by generation and “DDI” quintile in the nation’s most rural counties (rural counties that are farthest from metropolitan areas). In rural counties with the best digital access (a low digital divide index), the number of Millennials and Gen Xers increased.
The New Connected Countryside: A Work in Progress
To conclude, if you just look at overall numbers, our population seems to be behaving just like they did in the industrial age — moving to cities where jobs and people are concentrated. Rural areas that lag in broadband connectivity and digital literacy will continue to suffer from these old trends.
However, the digital age is young. Its full effects are still to be felt. Remember it took several decades for electricity or the automobile to revolutionize society. Besides, areas outside metro areas lag in broadband connectivity and digital literacy, limiting their potential to leverage the technology to affect their quality of life, potentially reversing migration trends.
Whether or not decentralization will take place remains to be seen. What is clear though is that (while other factors are having an impact, as well) any community attempting to retain or attract millennials need to address their digital divide, both in terms of broadband access and adoption/use.
In other words, our data analysis suggests that if a rural area has widely available and adopted broadband, it can start to successfully attract or retain millennials.
Roberto Gallardo is assistant director of the Purdue Center for Regional Development and a senior fellow at the Center for Rural Strategies, which publishes the Daily Yonder. Robert Bell is co-founder of the Intelligent Community Forum. Norman Jacknis is a senior fellow at the Intelligent Community Forum and on the faculty of Columbia University.
A virtual mirror allows someone to use a camera and have that image displayed on a large LED screen. Better yet, with the right software, it can change the image. With that ability, virtual mirrors have been used to see what new glasses look like or to try on dresses – a virtual, flexible fitting room.
Virtual mirrors and their equivalent as smart phone apps have been around for the last couple of years. There are examples from all over the world. Here are just a couple:
Marketers have already thought of extending this to social media, as one newspaper reported with a story titled “Every woman’s new best friend? Hyper-realistic new virtual mirror lets you to try on clothes at the flick of the wrist and instantly share the images online”.
This all provides a nice experience for customers and may even help sell a particular item to them. But that’s only the beginning.
Virtual mirrors are a tremendous source of data about consumer behavior. Consider that the system can record every item the consumer looked at and then what she or he bought. Add to that the information about the person that can be detected – hair color, height, etc. With the application of the right analytics, a company can develop insights about how and why some products are successful – for example a particular kind of dress may be what short or tall women are really looking for.
With eye tracking devices, such as those from Tobii, connected to the virtual mirror, even more data can be collected on exactly what the consumer is looking at – for example, the last part of a dress that she looked at before deciding to buy or not to buy.
Going beyond that, an analysis can be done of facial (and body) expressions. I’ve written before about affective computing which is the technology is developing to do and to respond to this kind of measurement.
By fully gathering all the data surrounding a consumer’s use of the virtual mirror, its value becomes much more than merely improving the immediate customer experience. In a world of what many consider big data, this adds much more data for the analytics experts on the marketing and product teams to investigate.
Alas, I haven’t seen widespread adoption and merger of these technologies. But the first retailer to move forward this way will have a great competitive advantage. This is especially true for brick-and-mortar retailers who can observe and measure a wider range of consumer behavior than can their purely e-commerce competitors.
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© 2017 Norman Jacknis, All Rights
Among the more ambitious and expansive CEOs, there’s a special kind of holy grail – transforming their organizations into learning organizations. Jack Welch, former and famous CEO of GE, put it this way in the 1990s:
“an organization’s ability to learn, and translate that learning into action rapidly, is the ultimate competitive business advantage.”
The Business Dictionary defines a learning organization as an
“Organization that acquires knowledge and innovates fast enough to survive and thrive in a rapidly changing environment. Learning organizations (1) create a culture that encourages and supports continuous employee learning, critical thinking, and risk taking with new ideas, (2) allow mistakes, and value employee contributions, (3) learn from experience and experiment, and (4) disseminate the new knowledge throughout the organization for incorporation into day-to-day activities.”
Or as Peter Senge, one of the founders of the learning organization movement, has famously said in 1990:
“A learning organization is an organization that is continually expanding its capacity to create its future.”
As you can see, this dream started more than 25 years ago.
By the first decade of this century, however, Mark Smith wrote:
“[W]hile there has been a lot of talk about learning organizations it is very difficult to identify real-life examples.”
The companion in thought of the learning organization movement was the knowledge management movement. Its goal was to capture, organize and distribute knowledge among the members of an organization.
But, in his 2014 paper, “A Synthesis of Knowledge Management Failure Factors”, Alan Frost was already conducting autopsies for the failure of knowledge management initiatives in many organizations.
In some ways, this reminds me of the first great wave of Artificial Intelligence in the 1980s when a lot of effort went into trying to codify the knowledge of experts into expert systems by extensively questioning them about their decision processes. It turns out that it is hard to do that.
Often experts – the knowledgeable ones – can’t really articulate their decision rules and to make matters worse those rules are at times probabilistic. Like other humans, experts often seek to develop rubrics to simplify a problem, which unfortunately can limit their ability to continue to observe what’s happening. Human perception, in general, in an imperfect instrument.
Thus, even if an organization is successful in widely distributing the knowledge developed by its staff, it may be just propagating ideas that are, at best, only partly true.
All of these factors, and many others, has slowed down the march to the dream of learning organizations.
But now we are possibly at the beginning of a rebirth of the learning organization.
What’s different today? Analytics and big data make the process of organizational learning much easier and better. Indeed, it is perhaps time to add analytics as a sixth discipline to Senge’s Five Disciplines of a learning organization.
After all, it’s not that people don’t know things that are important to an organization’s success – it’s just that they don’t know everything that is important and they can’t or won’t keep up with the torrent of new data vying for their attention.
The traditional gathering of the human knowledge combined with the continuously improving analytics models can achieve the dream so nicely stated by the executives and visionaries of twenty-five years ago.
For example, instead of trying to interview experts at length to capture their knowledge, today, someone in analytics would prefer to review the thousands of cases where the characteristics of the case, the decision by an expert and outcome was known. Then some kind of machine learning would search for the underlying patterns. In that way, the expert’s tacit understanding of the world would arise out of the analytics.
Nor does this cut out experts in the knowledge acquisition process. It just changes their role from being a memoirist. Instead, the experts can help kick off the building of the model and even assist in interpreting the results of the analytics.
Once the learning has begun, there is still much to learn (no pun intended) from the pioneers of this field. While they had great difficulty obtaining the knowledge – feeding the learning organization – they knew the rules of distributing that knowledge and making it useful. That is a lesson that today’s folks specializing in analytics could learn. Among these:
For an illustration, see “Evidence in the learning organization” from the National Institutes of Health, in which these issues are focused on the medical profession.
If a marriage of the learning organization and knowledge management movements with the newer focus on analytics takes place, then all of those fields will improve and benefit.
© 2017 Norman Jacknis, All Rights Reserved
Even though the Internet can connect people around the world, it’s surprising how little news in the tech community gets exchanged across national borders. I’m not referring to things like computer languages and algorithms, which the engineers exchange with each other – although mostly in the direction of north to south. Rather, it’s particularly knowledge of the business of tech and potential partners that doesn’t cross borders well.
Silicon Valley and North America is frequently covered in other parts of the world. And Americans will periodically get tech and entrepreneurial news from Europe and Japan and now China.
But there’s a big world out there that most people are unaware of who live in the northern hemisphere that includes North America or Europe or East Asia. Among the places where you might not expect a thriving tech scene is 6,500 miles from Silicon Valley, even further away than Beijing or Shanghai. That city is Buenos Aires, which I visited last month.
In Buenos Aires and throughout Latin America, there is almost a parallel universe of tech activity – except it is conducted mostly in Spanish which may be part of the reason it is less well known outside of Latin America (and perhaps tech centers like Barcelona, Spain).
There is so much entrepreneurial and tech activity going on in Buenos Aires that I was only able to sample a part of it. A good example is Startup Buenos Aires (SUBA). By providing “community, education and resources”, SUBA aims to
“connect members locally and globally, while providing resources to grow a strong and sustainable startup ecosystem in Buenos Aires and around the world.”
Their calendar shows two or three events of interest to the tech and startup community every day.
Along with ten thousand other tech folks, I attended ExpoInternetLA, which declares that it is
“the biggest Business & Technology Event in Latin America, focused on B2B and M2M and many other technologies that are applied in every day and especially in business, virtually and/or physical. It is the first event of its kind in LATAM, where it promotes and stimulates the sector, businesses and investments that will influence the IoT & IoE in the region. During the 3 days of it, you can see innovation, new developments and releases as well as attend the conference program with top experts in the field, live different experiences offered by exhibitors and sponsors, make the business round and do networking at its best.”
Three days of presentations, that could have easily taken place in North America, covered a wide range of topic like Digital Transformation, IOT, biometrics and Bitcoin. And the exhibition area looked very similar to tech trade shows in the US, with the range of products and services you’d expect to see, except that the vendors were unfamiliar names, almost all from Latin America.
While ExpoInternet was conducted in Spanish, some of the presentations were in English and there were a large number of English speakers on the floor. Thus, they know what’s happening in English-speaking tech, although English-speaking tech may not know what’s happening here.
I also saw the two locations of AreaTres which calls itself “the meeting space of the Buenos Aires entrepreneurial ecosystem. Together with our partners, in the year 2015 we hosted 120 events focused on technology, innovation, design and entrepreneurship in which more than 100,000 people participated.”
Of the many events and meetups, one especially interesting to me was the local Digital Innovation Group with about a hundred in attendance (obviously including an out-of-towner, me). The presentation was on “Conversational UX: The Interface Dialog”, a topic you’d expect to have in Silicon Valley or New York. And the presentation was very much up to the current state of the art. It even ended with a demo of Albert The Bot as an interface to devices like Alexa Echo.
This particular meeting was hosted by at Solstice Consulting, a tech company that was started in Chicago, but set up an office in Buenos Aires to take advantage of the tech talent pool there and the time zone (only two hours difference at this time of year, compared to the 10-12 hour time differences with Asia).
By the way, they’re not alone and it’s not just tech, but also a strong design community. R/GA, the award-winning digital ad/film/product firm headquartered in New York that describes itself as “combining creativity with the power of disruptive technology”, also has an office in the same district of Buenos Aires. And near one of the two AreaTres locations, there is also a Design Center.
And the city government itself is quite sophisticated with excellent and innovative citizen-facing technology and support for all this private sector activity. Just one illustration when I was in town, on June 27th, the City government’s department for innovation ran InnovatiBA 2017, the fifth annual, all-day event for residents to “experience the future, today.”
Argentina’s economy has had its ups and downs recently.
Unfortunately, over the last hundred years or so, it has also fallen far
from its perch as one of the richest nations in the world.
Yet there is still considerable wealth here among some and there are professional and educational traditions that are still strong. That legacy, along with the entrepreneurship, hard work, innovation and tech skills that I witnessed, are all positive signs for the future here
— as the welcome mat to one of the tech offices
© 2017 Norman Jacknis, All Rights Reserved @NormanJacknis
Last week, at the end of my class in Analytics and Leading Change, one of the required courses in Columbia University’s Masters Program in Applied Analytics, my students asked for books I’d recommend that provide more detail than we could cover in the course. It turns out that others are also interested in a good library of books about analytics from the viewpoint of an organization’s leaders.
You’ll see that these are not textbooks about analytics or machine learning techniques – there are plenty of those. Instead, this reading list is the next step for those folks who understand the techniques and now want the insights from their work to have an impact on and provide value to their world.
Although most of these books were published in the last decade, there are also some classics on the list going back fifty years. And I’ve chosen mostly popular books because frankly they are written in a compelling way that is accessible to all leaders.
With that introduction, here are my recommendations.
1. On the experience of doing analytics and seeing its impact:
Moneyball by Michael Lewis
The movie, Moneyball, starred Brad Pitt as the hero of the first and most storied use of analytics in professional baseball. For people in the field of analytics, what could be better than a movie about your skills helping the underdog. But like all movies, it tended to gloss over or exaggerate situations for the benefit of a good, simple plot.
The book that Lewis wrote originally is subtler and is a good case study of the human side of introducing analytics in a tradition-bound field. Tying it all up, his more recent book, The Undoing Project: A Friendship that Changed Our Minds, is the story of the collaboration between Kahneman (see below) and Tversky.
The Signal and The Noise: Why So Many Predictions Fail — But Some Don’t by Nate Silver
Nate Silver is probably the best-known analytics practitioner by those not in the business themselves, due to his work over the years, especially for the New York Times and in relation to high visibility elections. This is his review of the ups and downs in using analytics, offering lessons especially from sports and politics.
Victory Lab: The Secret Science of Winning Campaigns by Sasha Issenberg
Although sometimes a bit over the top and now five years old, it is a thorough description of the use of analytics in election campaigns. Election campaigns are good examples of analytics because they are both well-known and there is a huge amount of data concerning elections and the voters who determine their outcomes.
Dataclysm: Love, Sex, Race, and Identity — What Our Online Lives Tell Us about Our Offline Selves by Christian Rudder
The author is the co-founder and former analytics lead for OkCupid. Not surprisingly, much of the book is about dating choices, but he goes way beyond that to uncover insights about various social attitudes, including racism, from the large amount of data he had in his hands both at his former company and elsewhere.
How Not To Be Wrong: The Power Of Mathematical Thinking by Jordan Ellenberg
Since analytics is essentially a mathematical art, Ellenberg’s book about mathematical thinking is important preparation for the field. It also provides numerous examples of how to present quantitative insights in a way that non-experts would understand.
2. On expanding the normal range of analytics:
Unobtrusive Measures: Nonreactive Research in the Social Sciences by Eugene Webb, et al
I’ve added this fifty year old classic to the list because even in a world of big data we don’t necessarily have all the data we need, either in our computer systems or in the physical world. This book reminds us to observe indications of phenomenon that are not already available – such as the influence of an individual measured by the wear and tear on the entry to his/her office space. It also points out the need to always include metadata in our analysis since that is often revealing.
How to Measure Anything: Finding the Value of Intangibles in Business by Douglas Hubbard
Somewhat picking up the same theme, this book helps both the business executive and the analytics practitioner to be more creative in measurement, especially when it comes to things that people haven’t so far been able to offer good metrics for.
Connected: The Surprising Power of Social Networks and How They Shape Our Lives by Nicholas A. Christakis and James H. Fowler
This is a book about how social networks influence us in ways we hadn’t considered before. As they say: “How your friends’ friends’ friends affect everything you think, feel and do.” I suppose a good example is how their observation that you’ll gain weight by being connected to overweight people in a social network has itself become a meme. In its own way, this book is an interesting work of analytics.
Just as important is its elaboration of how to study social networks since an understanding of the network of influencers in any organization is essential to anyone who wants to change the behavior of the people in that organization.
Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic
The author was part of Google’s analytics team, which is the analytics equivalent of working at the Vatican if you’re a Roman Catholic theologian. Her emphasis in on how to show the insights of analytics work and to tell a story about those insights. In a world of all kinds of data visualization tools and fads, her advice is clear and evidence-based.
3. On the way that the human mind perceives the insights of analytics and might or might change as a result:
Payoff: The Hidden Logic That Shapes Our Motivations by Dan Ariely
Professor Ariely, formerly of MIT and now at Duke, is one of the more creative experimenters in psychology and he quickly reviews both his own and others’ research results. The theme of this short book is that the payoff which often makes a difference in human behavior is not necessarily a financial reward and that sometimes financial incentives even backfire. This is important for leaders of change in organizations, particularly big corporations, to understand.
Thinking, Fast And Slow by Daniel Kahneman
I’ve written about the work of Nobel Prize winner and Princeton Professor Kahneman before, most recently in “What Do We Know About Change”. This describes what Kahneman has learned from a lifetime of research about thinking and decision making. His work on how people process – distort – quantitative statements is especially relevant to analytics experts who need understand the cognitive biases he describes.
Switch: How to Change Things When Change Is Hard by Chip Heath and Dan Heath
The Heath brothers, popular business writers, have done a good job in this book of explaining what’s been learned in recent psychological research – see Kahneman and Ariely, for instance – without dumbing it down so much that the key points are lost. In doing that well, they also provide the leader of change and analytics some good ideas on how to present their own results and getting their organizations to switch to a more analytics-oriented outlook.
4. On the strategic linkage between leading change and analytics
The Dance of Change by Peter Senge, et al
This is another classic that goes beyond the usual cookbook approach found in most books on “change management”. Yet, Senge and his colleagues anticipated the more recent approaches to change management which is about something more than just getting a single project done. For Senge, the goal he established was to help create learning organizations. While he does not focus on analytics, this book should particularly resonate with analytics professionals since they now have the tools to take that learning to new and more useful levels than in the past.
I could easily expand this list, as could many others, but this “baker’s dozen” books will provide a good rounded education to start.
© 2017 Norman Jacknis, All Rights Reserved @NormanJacknis
Next week, I’m teaching the summer semester version of my Columbia University course called Analytics and Leading Change for the Master’s Degree program in Applied Analytics. While there are elective courses on change management in business and public administration schools, this combination of analytics and change is unusual. The course is also a requirement. Naturally, I’ve been why?
The general answer is that analytics and change are intertwined.
Successfully introducing analytics into an organization shares all the difficulties of introducing any new technology, but more so. The impact of analytics – if successful – requires change, often deep change that can challenge the way that executives have long thought about the effect of what they were doing.
As a result, often the reaction to new analytics insights can be a kneejerk rejection, as one Forbes columnist asked last year in an article titled “Why Do We Frequently Question Data But Not Assumptions?”.
A good, but early example of the impact of what we now call “big data”, goes back twenty-five years ago to the days before downloaded music.
Back then, the top 40 selections of music on the “air” were based on what radio DJs (or program directors) chose and, beyond that, the best information about market trends came from surveys of ad hoc observations by record store clerks. Those choices too emphasized new mainstream rock and pop music.
In 1991, in one of the earliest big data efforts in retail, a new company, SoundScan, came along and collected data from automated sales registers in music. What they found went against the view of the world that was then widely accepted –
old music, like Frank Sinatra, and genres others than rock were very popular.
Music industry executives then had to change the way they thought about the market and many of them didn’t. This would happen again when streaming music came along. (For more on this bit of big data history, see https://en.wikipedia.org/wiki/Nielsen_SoundScan and http://articles.latimes.com/1991-12-08/entertainment/ca-85_1_sales-figures .)
A somewhat more recent example is the way that insights from analytics have challenged some of the traditional assumptions about motivation that are held by many executives and many staff in corporate human resource departments. Tom Davenport’s Harvard Business Review article in 2010 on “Competing on Talent Analytics” provides a good review of what can be learned, if executives are willing to learn from analytics.
The first, larger lesson is: If the leaders of analytics initiatives don’t understand the nature of the changes they are asking of their colleagues, then those efforts will end up being nice research reports and the wonderful insights generated by the analysts will disappear without impact or benefit to their organizations.
The other side of the coin and the second reason that analytics and change leadership are intertwined is a more positive one. Analytics leaders have a potential advantage over other “change agents” in understanding how to change an organization. They can use analytics tools to understand what they’re dealing with and thus increase the likelihood that the change will stick.
For instance, with the rise of social networks on the internet, network analytics methods have developed to understand how the individuals in a large group of people influence each other. Isn’t that also an issue in understanding the informal, perhaps the real, structure of an organization which the traditional organization charts don’t illuminate?
In another, if imperfect example, the Netherlands office of Deloitte created a Change Adoption Profiler to help leaders figure out the different reactions of people to proposed changes.
Unfortunately, leaders of analytics in many organizations too infrequently use their own tools to learn what they need to do and how well they are doing it. Pick your motto about this – “eat your own lunch (or dogfood)” or “doctor heal thyself” or whatever – but you get the point.
© 2017 Norman Jacknis, All Rights Reserved. @NormanJacknis
Last week, I gave a presentation at the Premier CIO Summit in Connecticut on the Future of User Interaction With Technology, especially the combined effects of developments in communicating without a keyboard, augmented reality (AR) and machine learning. I’ve been interested in this for some time and have written about AR as part of the Wearables movement and what I call EyeTech.
First, it would help to distinguish these digital realities. In virtual reality, a person is placed in a completely virtual world, eyes fully covered by a VR headset – it’s 100% digital immersion. It is ideal for games, space exploration, and movies, among other yet to be created uses.
With augmented reality, there is a digital layer that is added onto the real physical world. People look through a device – a smartphone, special glasses and the like – that still lets them see the real things in front of them.
Some experts make a further distinction by talking about mixed reality in which that digital layer enables people to control things in the physical environment. But again, people can still see and navigate through that physical environment.
When augmented was first made possible, especially with smartphones, there were a variety of interesting but not widespread uses. A good example is the way that some locations could show the history of what happened in a building a long time ago, so-called “thick-mapping”.
There were business cards that could popup an introduction and a variety of ancillary information that can’t fit on a card, as in this video.
A few years later, now, this audience was very interested in learning about and seeing what’s going on with augmented reality. And why not? After a long time under the radar or in the shadow of Virtual Reality hype, there is an acceleration of interest in augmented (and mixed) reality.
Although it was easy to satirize the players in last year’s Pokémon Go craze, that phenomenon brought renewed attention to augmented reality via smart phones.
Just in the last couple of weeks, Mark Zuckerberg at the annual Facebook developers conference stated that he thinks augmented reality is going to have tremendous impact and he wants to build the ecosystem for it. See https://www.nytimes.com/2017/04/18/technology/mark-zuckerberg-sees-augmented-reality-ecosystem-in-facebook.html
As beginning of the article puts it:
“Facebook’s chief executive, Mark Zuckerberg, has long rued the day that Apple and Google beat him to building smartphones, which now underpin many people’s digital lives. Ever since, he has searched for the next frontier of modern computing and how to be a part of it from the start.
“Now, Mr. Zuckerberg is betting he has found it: the real world. On Tuesday, Mr. Zuckerberg introduced what he positioned as the first mainstream augmented reality platform, a way for people to view and digitally manipulate the physical world around them through the lens of their smartphone cameras.”
And shortly before that, an industry group – UI LABS and The Augmented Reality for Enterprise Alliance (AREA) – united to plot the direction and standards for augmented reality, especially now that the applications are taking off inside factories, warehouses and offices, as much as in the consumer market. See http://www.uilabs.org/press/manufacturers-unite-to-shape-the-future-of-augmented-reality/
Looking a bit further down the road, the trend that will make this all the more impactful for CIOs and other IT leaders is how advances in artificial intelligence (even affective computing), the Internet of Things and analytics will provide a much deeper digital layer that will truly augment reality. This then becomes part of a whole new way of interacting with and benefiting from technology.
© 2017 Norman Jacknis, All Rights Reserved. @NormanJacknis
I’ll be speaking at the Rural Summit for Europe to be held in Eindhoven, Netherlands tomorrow — I’ll be writing more about that later. Coincidentally, last Friday, the Aspen Institute’s Community Strategies Group and Rural Development Innovation Group hosted a very good panel on rural entrepreneurship in the US.
In addition to the Aspen folks, the panel consisted of:
• Lupe Ruiz, Co-Owner, Wing Champs
• Ines Polonius, CEO, Communities Unlimited
• Dennis West, CEO, Northern Initiatives
• Jeffrey Lusk, Executive Director, Hatfield McCoy Regional Recreation Authority
There are many potential entrepreneurs in the countryside. If you think about it, the family farm is an example of entrepreneurship.
Even more so today, entrepreneurship is essential for the economic viability of rural areas in the face of the relatively shrinking rural population in the US because the traditional approaches aren’t working well.
Two or three decades ago, some manufacturing plants moved to rural areas to save costs, but then manufacturing shifted further to low cost countries. And now, with the increasing use of robotic devices, factories aren’t big employment generators.
Moreover, the use of incentives to get big companies to move to rural areas has been shown to be of limited and ever decreasing value in helping long term economic development. Unlike multinational businesses that rural areas have tried to attract, local entrepreneurs are committed to their communities.
Ms. Polonius noted that every dollar of sales that go to local entrepreneurs is spent several times over before it leaves the area, whereas sales at multi-national companies in rural areas leave much more quickly. As a case in point, Mr. Ruiz noted that when it came time to build his restaurant, he felt an obligation to buy lumber from another local entrepreneur rather than make the drive to Home Depot or Lowe’s where he might have saved a few bucks.
The panel went on for than an hour, so I can only highlight what struck me as the most critical points.
First, without any prompting from me or anyone else, the panelists stressed the importance of broadband for both local business success and also being able to reach markets beyond the local area. Mr. Ruiz was especially proud of the fact that his small town of Raymondville in the Rio Grande Valley of Texas had better broadband than the state capital of Austin did. The service is provided by the Valley Telephone Cooperative – in yet another example of how cooperatives have moved broadband forward in rural areas as the big telecoms companies abandon those areas.
Second, creativity and counter-intuitive thinking are necessary to turn around rural areas. Mr. Lusk pointed out how his area of southern Virginia had a concentration of some of the longest lasting poverty-stricken counties in the US. Where once extraction industries, like coal mining of the mountains, provide some boost to the local economy, that had been on a downturn since the 1950s. Local people wanted to have factories come there, but highway transportation wasn’t great and the land wasn’t flat – it was the Appalachian Mountains after all, very pretty, but not great industrial territory.
They finally turned things on their head and realized that the thing that was preventing industrial development – the mountains – was the basis for future growth of rural tourism. Mr. Lust described the ingenious ways that the Hatfield McCoy Regional Recreation Authority went from ATV off-road trails to encourage other economic development.
Third is the need for risk capital. Although local business folks often think first of going to the bank for funds, there are many fewer local banks around and banks of any kind aren’t generally in the business of helping startups. So, other sources of funds are needed. That’s where non-profits like Northern Initiatives come in. The non-profit organization proclaims that it
“provides loans to small business owners and entrepreneurs in Northern Michigan that might not qualify for loans from traditional banks for a variety of reasons.”
Fourth, the development of rural entrepreneurship cannot end with the money, also needs training and coaching. Communities Unlimited offers a cash flow tool to keep entrepreneurs on an even keel. And, as with Wing Champs, they provide a variety of other services to help new business get over the inevitable rough spots.
Similarly, Northern Initiatives puts it this way:
“Each one of our loans comes with access to business services which includes a suite of practical trainings, tools, and resources on topics that matter to every business owner.”
And they even provide a coach to each company they give money to.
Mr. West also noted that some coaching comes from modeling – seeing other local people making money by starting businesses provides both encouragement and education to potential entrepreneurs.
Although these efforts don’t have quite the focus on gazelle second-stage growth companies that the Economic Gardening movement does, they share in common the idea that long term economic growth comes from entrepreneurship and entrepreneurs need help.
Here’s the overall lesson of this panel:
The seeds of entrepreneurship are in the countryside already. For economic growth, those seeds need to be fertilized by the combination of broadband, creativity/counter-intuitive thinking, risk capital and training/coaching.
[You can see a recording of the event at https://www.youtube.com/watch?v=lMIjJMEbzsI ]
© 2017 Norman Jacknis, All Rights Reserved
The NTCA-Rural Broadband Association held its annual meeting and expo this week in San Diego with more than 2,000 people in attendance.
I was on a panel to discuss the idea of a Virtual Metropolis, a topic I introduced to the Rural Broadband Association and have written about here.
The idea is simple. In the pre-internet days, cities — especially big cities — brought together lots of people. Because these peoople were near each other and could casually interact, these cities became hotbeds of innovation and economic production. Along with increased agricultural productivity, this led to the shift of population from rural to urban areas that has threatened many small towns.
As a sort of last gasp, after World War II, many small outlying towns tried to substitute factories as a source of employment. In the face on increasing automation and cheaper labor markets elsewhere, that strategy crumbled too. In the last couple of decades, the drop in small town and rural population has increased. Many bright, ambitious young people can’t wait to move away to a big city.
And, if you’re an entrepreneur with some great new product or service, it’s easier to start up in New York or Silicon Valley or some other equivalent place. Why? Because no single person has all the skills they need to succeed and it’s easier to find skilled people in those cities than in your small town.
When I write this, you may be thinking about high-tech entrepreneurs. But the historic limitations of small town life affect everyone, even artisans or those in other low-tech businesses.
This all may sound bleak and many people share that bleak outlook. Even some of the members of the Rural Broadband Association can be overwhelmed by this picture.
But what I’ve described is about the past, not the potential for the future. In this digital age, if you’re connected by broadband you can live anywhere. If you enjoy country living and love the quality of life there, you no longer need to compromise your economic prospects by continuing to live in the country.
We’ve seen some of the positive impact that broadband can have on those rural communities who have invested in broadband, but that impact has not been widespread enough for people to take notice.
Partly this reflects the lack of reasonably priced broadband in many rural areas. The Rural Broadband folks are working hard to fix that.
More important, there hasn’t been a digital platform devoted to the needs of people in the countryside that would provide a substitute for the casual face-to-face interactions and the breadth of the skill pool that people in big cities take for granted.
That’s where the Virtual Metropolis comes in. We are building this platform to make it easier for people in small towns and rural areas to see and talk to each other about how they can work together for mutual economic benefit.
Broadband makes this possible because it provides the bandwidth that’s necessary for visual chat. Visual chat is especially critical in helping to establish trust, compared to email, messaging and other forms of communication that are limited to text.
The shared small town experience is also an essential basis for mutual understanding and trust. That common experience gets drowned out in the overwhelmingly urban outlook of much larger social media and job services.
If even 10 or 15% of the people living in more rural areas join in for business purposes, they will be virtually part of a metropolis of more than five million people. In that way, they can achieve many of the same benefits of physically residing in a big city.
(While my focus is on economic opportunity, broadband will also give these folks access to great educational, cultural and medical resources.)
In addition to creating and setting up the technology for a Virtual Metropolis, we need to build a community — to get people to participate.
In part, that’s where the NTCA plays a key role. They can reach out to the early adopters, the innovators in their regions and let them know that the days of isolation are over. Clearly, from a business viewpoint, the Virtual Metropolis provides their customers and potential customers with a strong business justification for increasing their bandwidth.
One of the panelists, Dusty Johnson of Vantage Point Solutions in Mitchell, South Dakota. Despite Mitchell’s selection among the ICF’s Top 7 most intelligent communities in the world, he was initially skeptical as a self-described “cranky old man.” But as he thought about others in Mitchell, particularly his own children and other young people, he realized the value of the idea.
The other panelist, Michael Burke, CEO of MTA, the local broadband provider for 10,000 square miles of Alaska is already an unusually innovative leader. MTA goes way beyond merely providing connectivity in many ways, for example providing customer training on new technology and funding coding classes in the schools.
Mr. Burke quickly championed the Virtual Metropolis. Of course, considering the distance from the lower 48 and the nature of winter in Alaska, the necessity of being part of a much larger virtual community is crystal clear.
[If you’re interested in joining and helping to build this virtual metropolis, please contact me.]
© 2017 Norman Jacknis, All Rights Reserved
The book, “Team of Teams: New Rules of Engagement for a Complex World”
by retired General Stanley McChrystal and his associates Tantum Collins,
David Silverman, and Chris Fussell has been out for
more than a year. I hadn’t gotten around to reading it partly because I
wasn’t sure I wanted to read what I thought would be yet another
general’s exercise in self-promotion. I’ve also been through too many
conferences filled with speeches from high ranking executives that are
essentially war stories in which they are the heroes of the story.
So, when I finally had the time to read it at the end of last year, I was surprised to find that this book is one of the best recent books on management. It has been criticized by some as not really having anything new in it and merely reflecting the undue length of time it has taken a general to figure out these things.
While there is some truth to that, the fact remains that most large corporate and public sector organizations operate in the old style that McChrystal finds inadequate for a new era of change, complexity, and creativity. This includes even highly touted tech companies who reach a certain size and stage of maturity, even while they profess to be using agile approaches.
For General McChrystal, it’s a question of what the organization is designed to achieve. Traditional “Taylorism”, which has been the model of most large organizations, aims to maximize efficiency. As part of that goal, he writes “organizations have implemented as much control over subordinates as technology physically allowed.” That certainly sounds like the traditional image of the Army and many large corporations.
Instead, he argues that in today’s world, adaptability is much more important. This is a necessary response to deep and widespread technological changes. He also notes that those same technologies make possible a more modern, more adaptable organization.
Although much of what it’s in the book isn’t exactly new, the authors synthesize the material and lay it out to build a story that should be compelling to any senior executive.
The value of teams and the use of the intelligence of team members, rather than considering them cogs in a large machine, is explained well. But the real challenge in leading large organizations is how to scale those benefits.
That’s where McChrystal and co-authors make a real contribution.
Here are some the key take-aways:
This book is an excellent guide to effectively managing large-scale operations to implement a strategy. But, much like the wars that General McChrystal was part of, it doesn’t focus on whether the larger strategy makes sense. That’s not a criticism of the book, just a realization that there are important considerations beyond its scope.
© 2017 Norman Jacknis, All Rights Reserved
Much has been written about how the results of this year’s Presidential election reflected the feeling on the part of people who live in rural areas and small towns that they have been overlooked and that the severe problems in those areas have not received sufficient attention by public and business leaders.
This Washington Post story, sub-headed “How an electorate fed up with the elite propelled Donald Trump to victory”, is a good example.
Although we frequently hear that 80% of Americans live in cities now, that still means there are 60,000,000 Americans in the countryside – not an insignificant number as we saw last month.
Even the news stories that feature broad economic trends don’t highlight the uneven nature of those trends in these areas. For example, the decline in manufacturing employment was a standard talking point on the recent campaign trail. But many observers seem to have forgotten that many bigger manufacturing plants had long since departed cities for the countryside. So when manufacturing employment declined, it hit the countryside more deeply, even while that pain was less visible.
So, sadly, the feeling in rural America of being forgotten is not unfounded.
To make matters worse, in too many small cities and rural areas, many people speak negatively of the prospects for the area. This helps create a downward spiral by persuading the brightest young people to leave.
As sociologists, Patrick J. Carr and Maria J. Kefalas, wrote in their 2009 book, “Hollowing Out The Middle:
“The biggest question facing anyone who grows up in a small town is whether he or she should leave or stay. A little further down the road, those who make the initial decision to leave, usually after graduating high school, must decide whether to return to the cozy familiarity of their hometown or to continue building lives elsewhere. The fact that this small-town rite of passage should be so intimately bound up with the very future of the Heartland allows us to see how the hollowing-out phenomenon plays out in the lives and decisions of young people, and how their pathways are shaped by the communities and people who surround them as they grow up.”
“The Heartland’s most valuable export is not crops or hogs but its educated young people.”
For the last couple of years, I’ve been working with the Intelligent Community Forum helping these communities to take advantage of new opportunities open to them in a new century in which close physical proximity of millions of people is not necessarily the only strategy for economic success.
I’ve written before about how technology enables rural residents to take advantage of the kind of resources that you used to be almost exclusively available to residents of big cities — global economic connections, education and culture, even world-class health care — while maintaining the quality of life that draws them or keeps them in the countryside.
With all this on my mind a few weeks ago, I was asked by the Aspen Institute to keynote a community dialog in Sutter County (Yuba City), California. This was part of my participation in the small working group advising Aspen’s project on the future of libraries.
Although Sutter County is not, by any means, among the most devastated of rural communities, it is still concerned about its future. My observation was that they had some strong assets that are otherwise underappreciated in the conventional economic development perspective.
First, I was impressed by the local leadership, which seemed to have its act together. Leaders who have vision and an understanding of where the world is going are essential for community development.
Second, they have a diverse population, with a variety of experiences including an understanding of entrepreneurial success. Like some other flourishing small cities around the country, Yuba City also has its immigrant groups. It is, for example, known all over North America and India for its long-established Sikh community, which draws tens of thousands of people to the city each year – and can be a connection to the global economy.
Third, they have a library that is prepared to play its role as the central institution of the knowledge economy and help the residents of Sutter County take advantage of new opportunities that I see in a new connected countryside. Much of the Aspen workshop/dialog was focused on the steps the library can take to make this a reality.
It will be interesting to see how well Sutter County achieves its vision and what other communities can learn from it.
And, perhaps for a short time, the situation in the countryside will get a little attention among public officials and the media. But even being remembered, once in a while, really isn’t much of a program.
While Sutter County and places like it across the country are trying to assure their future, it would be easier if national policy recognized and helped them respond to the socio-economic-technological challenges and opportunities facing them. More than merely reducing the sense of being forgotten, it could help accelerate a renaissance in the countryside.
© 2016 Norman Jacknis, All Rights Reserved
In previous elections, prediction markets were relatively accurate and were touted as competitors to public opinion polling. So how did they do this time?
The Iowa Electronic market had two prediction markets concerning the Presidential election. One was for the percentage of the popular two-party vote, which over the course of betting predicted Clinton 50% and Trump 48%. [These were individual contracts, which may be why the numbers add up to more than 100.] According to the most recent actual vote count, the result of the two-party split was Clinton 51% and Trump 49%.
The other was for the winner of the popular vote, which over the course of betting was 97% for Clinton and 1% for Trump. This was correct as current estimates show her getting over two million more votes than him.
Alas, winning the popular vote wasn’t enough this time and this was where the prediction markets seem to have run into a problem.
In one of the few markets that focused on electoral votes, a German betting market ended up predicting Clinton 300, Trump 237. (The real result was almost the reverse.)
PredictWise’s betting market had Clinton “winning” with an 86% probability. (In their defense, of course, that also means a 14% chance for Trump, which has to happen some time if we’re talking probability, not certainty, after all.)
The folks at the Campaign Workshop observed:
“Polls aren’t perfect, but neither are political betting markets. Since these markets have gained credibility in predicting elections, they have started taking changes in public opinion polls less seriously. Overconfidence in betting markets makes the markets look misleadingly stable, and that false sense of stability makes it harder for them to predict events that shake up the status quo — such as the outcome of the Brexit referendum, or Trump’s success in the Republican presidential nomination process. As Rothschild himself has pointed out, ‘prediction markets have arrived at a paradoxical place: Their reliability, the very source of their prestige, is causing them to fail.’ ”
In looking at these markets and, more generally, crowd predictions of events, it’s worth going back to James Surowiecki’s book, “The Wisdom of Crowds”. He described both the rationale for prediction markets — which have been well publicized — and the characteristics of accurate prediction markets — which have received less emphasis.
“The premise is that under the right circumstances, the collective judgment of a large group of people will generally provide a better picture of what the future might look like than anything one expert or even a small group of experts will come up with. … [Prediction markets] work much like a futures market, in which the price of a contract reflects the collective day-to-day judgment either on a straight number—for instance, what level sales will reach over a certain period—or a probability—for example, the likelihood, measured as a percentage, that a product will hit a certain milestone by a certain date.”
“[F]or a crowd to be smart, it needs to satisfy certain criteria. It needs to be diverse, so that people are bringing different pieces of information to the table. It needs to be decentralized, so that no one at the top is dictating the crowd’s answer. It needs to summarize people’s opinions into one collective verdict. And the people in the crowd need to be independent, so that they pay attention mostly to their own information and don’t worry about what everyone around them thinks.”
Did the prediction markets in 2016 meet Surowiecki’s criteria? Not really.
One problem with betting markets is that they are not diverse, not representative of a broad spectrum of the population. As a CNBC report noted: “Another issue that may have contributed to the miss [on Brexit and now the US election] is the relatively similar mindset among bettors generally.”
Since all bettors can see what others seeing, it’s hard to argue that their judgments are independent. And while, in a way, the decisions are decentralized, to the extent they mirror the current polling results and news reports from national media, there is less decentralization.
So do we just decide that the results of this year’s election call into question the value of crowd predictions? I think not.
But rather than focusing on predicting who wins the White House or the Super Bowl or the number of coins in a large bottle, there is another use of prediction markets for business and government leaders — testing the likelihood that people will respond positively to a new program or offer.
No matter how much market research (aka polling) is done, it is often difficult to assess how the public will react to a proposed program. I’m suggesting that prediction markets be used to estimate the reaction ahead of time, as long as they match Surowiecki’s criteria and don’t depend on money bets. At the very least, this would require a large and diverse set of people responding and keeping their judgments secret (until “voting” stops).
Over the last year or so, there have been several reports that rates for Affordable Care (aka Obamacare) had to be raised because there are fewer young, healthy people enrolling than expected. Putting aside the merits of the policy and its goals, this is an ideal case where prediction markets could have helped assess the accuracy of an underlying assumption about the implementation of a very consequential piece of public policy.
Some experts are skeptical of prediction markets because the average person doesn’t have professional expertise. But this use of prediction markets draws on the perceptions of people about each other.
Implicit in the diversity of views that Surowiecki notes is that enough people need to care about the planned program or policy. The reason they care may be to win money, in some cases, but that’s not the only reason. They might care because the market deals with something that affects their lives.
And the nice thing about this is that if only a few people care about a planned program that also tells you something about that plan — or, at least, whether the range of outcomes might be something between a yawn and deep trouble.
It may well be that this more experimental basis to predict behavior will illustrate the deeper value of prediction markets. What do you think?.
© 2016 Norman Jacknis, All Rights Reserved
[This is a follow up to my post last week.]
Even if we understand that what seems like resistance to change is more nuanced and complicated, many of us are directly or implicitly being asked to lead the changes in places of work. In that sense, we are “change agents” to use a well-established phrase.
Consider the number of times each day, both on the job and outside, that we hear the word “change” and the necessity for leaders to help their organizations change in the face of all sorts of challenges.
There has been a slew of popular business books providing guidance to would-be change agents. Several consultants and business gurus have developed their own model of the change process, usually outlining some necessary progression and steps that they have observed will lead to success.
Curiously, the same few anecdotes seem to pop up in a number of these, like burning platforms or the boardroom display of gloves.
While these authors mean well and have tried to be good reporters of what they have observed, change agents often find that, in practice, the suggestions in these books and articles are at best a starting point and don’t quite match the situation they face.
Part of the problem is that there has been too little rigorous behavioral work about how and why people change. (In fairness, some authors, like the Heath brothers, at least try to apply behavioral concepts in their recommendations on how to lead change.)
And on a practical level, many change agents find it difficult to figure out the tactics they need to use to improve the chances that the desired change will occur. In this post, I’m suggesting that we first need to understand the unique and sometimes unexpected ways that the human brain processes information and thus how we need to communicate.
(These are often called cognitive biases, but that is a pejorative phrase that might put you in the wrong mindset. It’s not a good idea starting an effort to convince people to join you in changing an organization by assuming that they are somehow irrational.)
As just one example, some of the most interesting work along these lines was that done by the Nobel-prize winning psychologist Daniel Kahneman and his colleague Amos Tversky.
They found in their research that people exaggerate potential losses beyond reality – often times incorrectly guessing that what they control (like driving a car) is less risky than what they don’t control (being a passenger in an airplane).
Moreover, a person’s sense of loss is greater if what might be lost has been owned or used for a long time (aka entitlements). Regret and other emotions can also enhance this sense of loss.
The estimate of losses and gains is also affected by a person’s reference point, which can be shifted by even random effects. The classic example of the impact of a reference point is how people react differently to being told either that they have a 10% chance of dying or a 90% chance of living through a major disease. The probabilities are the same, of course.
In general, they found that there is an aversion to losses which outweighs possible gains, even if the gains might be worth more.
This makes it sound like change is very difficult, since many people often perceive proposed changes as having big risks.
But there is more to the story. Indeed, Kahneman found that there is no across-the-board aversion to change or even merely to risk. Indeed people might make a more risky choice when all options are bad.
As one summary states:
“When faced with a risky prospect, people will be: (1) risk-seeking over low-probability gains, (2) risk-averse over high-probability gains, (3) risk-averse over low-probability losses, and (4) risk-seeking over high-probability losses.”
In just this brief summary, there is some obvious guidance for change agents:
I’ve just touched the surface here. There other findings of behavioral and social science research that can also enable change agents to get a firmer grasp on the reality of the situation facing them and suggest things they might do to become more successful.
© 2016 Norman Jacknis, All Rights Reserved
As I’ve been going through articles and books for the course on Analytics and Leading Change that I’ll be teaching soon at Columbia University, I frequently read how leaders and other change agents need to overcome resistance to change. Whenever we aim to get things done and they don’t happen immediately, this is often the first explanation for the difficulty.
Resistance to change is a frequent complaint of anyone introducing a new technology or especially something as fundamental as the use of analytics in an organization.
The conflict that it implies can be compelling. You could make a best seller or popular movie out of that conflict, like that great story about baseball, analytics and change “Moneyball”.
There have been cartoons and skits about resistance to change — https://www.youtube.com/watch?v=XTLyXamRvk4
This is an idea that goes very far back. Even Machiavelli, describing Renaissance politics, is often quoted on the subject:
“There is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, than to take the lead in the introduction of a new order of things. For the reformer has enemies in all those who profit by the old order, and only lukewarm defenders in all those who would profit by the new order, this lukewarmness arising partly from fear of their adversaries … and partly from the incredulity of mankind, who do not truly believe in anything new until they have had actual experience of it.”
It’s all awful if you’re the one trying to introduce the change and many have written about the problems they saw.
But is that word “resistance” misleading change agents? Going beyond the perspectives and anecdotes of change agents and business consultants, there has been over the last two decades some solid academic research on this subject. And, as often happens when we learn more, there have been some important subtleties lost in that phrase “resistance to change”.
In perhaps a refutation or an elaboration on Machiavelli’s famous quote, Dent and Goldberg report in “Challenging ‘Resistance to Change’” that:
“People do not resist change, per se. People may resist loss of status, loss of pay, or loss of comfort, but these are not the same as resisting change … Employees may resist the unknown, being dictated to, or management ideas that do not seem feasible from the employees’ standpoint. However, in our research, we have found few or no instances of employees resisting change … The belief that people do resist change causes all kinds of unproductive actions within organizations.”
Is what looks like resistance something more or something else?
More recently, University of Montreal Professor Céline Bareil wrote about the “Two Paradigms about Resistance to Change” in which she compared “the enemy of change” (traditional paradigm) to “a resource” (modern paradigm). She noted that:
“Instead of being interpreted as a threat, and the enemy of change, resistance to change can also be considered as a resource, and even a type of commitment on the part of change recipients.”
Making this shift in perspective is likely harder for change agents than the changes they expect of others. The three authors of “Resistance to Change: The Rest of the Story” describe the various ways that change agents themselves have biased perceptions. They say that blaming difficulties on resistance to change may be a self-serving and “potentially self-fulfilling label, given by change agents attempting to make sense of change recipients’ reactions to change initiatives, rather than a literal description of an objective reality.”
Indeed, they observe that the actions of change agents may not be merely unsuccessful, but counter-productive.
“Change agents may contribute to the occurrence of the very reactions they label as resistance through their own actions and inactions, such as communications breakdowns, the breach of agreements and failure to restore trust” as well as not listening to what is being said and learning from it.
There is, of course, a lot more to this story, which you can start to get into by looking at some of the links in this post. But hopefully this post has offered enough to encourage those of us who are leading change to take a step back, look at the situation differently and thus be able to succeed.
© 2016 Norman Jacknis, All Rights Reserved
I first wrote about this proposal two years ago. But I’m reposting it, since the idea is even more relevant now, as there has been further development of virtual communications – Skype and Google translators, more varieties of videoconferencing both in the cloud and through services like FaceTime, and even video through augmented reality devices, like Microsoft HoloLens.
If you’re interested in joining and helping to build this virtual metropolis, please contact me.
People who live in big metropolises, like New York, London or Hong Kong, often say that they can always find someone within a few miles who has a special skill they need to complete some project or build a business. I’ve pointed out that the close proximity of millions of people with so many different skills is part of what has made cities successful economic engines during the industrial era.
When the population of your town is just a few thousand, there is a much smaller likelihood you’ll find the special skill you need nearby – and thus you’ll be less likely to achieve what you have in mind.
In the US alone, the Census Bureau has noted in its report “Patterns of Metropolitan and Micropolitan Population Change” that 10% of Americans live in one of the 576 small urban areas (where there is at least one urban cluster of less than 50,000, but at least 10,000 people). That’s about 32 million people.
Another 6% lived in neither major metropolitan areas nor even these small urban areas. That’s just under 20 million people.
In this century, with broadband Internet, physical proximity is no longer necessary for people to collaborate and share their skills in a common project. Yet the small towns of these more than 50 million people are mostly not connected to each other.
So here’s my wild idea for the day: why not create a virtual metropolis of millions from the people in the small towns and communities of the countryside?
Imagine if even half of those 20 million (or 52 million) people who live outside the big metropolises could work together and be combined to act as if they were physically next door – while not actually living in such crowded conditions.
Such a network or virtual aggregation of small towns would offer their residents a much higher chance of succeeding with their business ideas and making a better living. If someone, for example, had the engineering talents to design a new product, that person might more likely find the necessary marketing talent somewhere in that network of millions of people.
Clearly, anyone connected to the Internet can try to reach out to anyone else whether that person lives in a small town or a big city.
But a network of small towns alone might encourage greater collaboration because of the shared background of country life and the perceived greater friendliness (and less wariness) of non-urban residents. In most small towns, people are used to working with each other. This would just be a virtual extension of the same idea.
Initially, of course, people would feel most comfortable with those in the same region, such as within North America. Over time, as people interact more with each other on a global basis, that comfort level will expand.
Whether on a regional or global basis, this virtual metropolis could compete on a more even playing field and even establish a unique brand for the people and companies located there. It would make it possible for rural residents to keep their quality of life and also make a decent living.
© 2016 Norman Jacknis, All Rights Reserved
Dams that produce hydropower have been one of the longest established renewable energy sources in the US for a long time. The American industrial revolution started in places, like Massachusetts, with abundant free flowing rivers that were tapped for their energy to power early factories.
Hydropower is still the largest source of renewable energy, accounting for a bit under half of the total.
A few years ago, I was involved with a project that was intended to revive one of those early industrial cities, Holyoke, Massachusetts. The city still had one of the few operating dams left and it supplied local electric power at a significant discount compared to elsewhere in the state. So the idea developed of creating local jobs by building a data center in Holyoke as a remote cloud location for major universities and businesses in the Boston area. (Driving distance between the two is about 90 miles.)
Putting aside whether a data center can be a significant job creator like old-time car plants, it struck me that the state as a whole would benefit by using the water resources there, thus bringing down a relatively high cost for electricity in a digital age. Of course, river resources are present in many other states, particularly east of the Mississippi River and in the northwest.
Thus, at one meeting with representatives of the research facilities of Harvard and MIT, I asked a simple question. When was the last time that engineering or science researchers took a serious look at using better materials or designs to improve the efficiency of the turbines that the water flows through or finding replacements for turbines (like the VIVACE hydrokinetic energy converter shown here)?
Despite or maybe because of the Three Gorges Dam project in China and similar projects, hydropower from dams has diminished in popularity in the face of various environmental concerns. Yet the rivers still flow and contain an enormous amount of energy and giant dams don’t have to be the only way to capture that energy.
With that in mind, I also asked if they had looked at the possibility of designing smaller turbines so that smaller rivers could be tapped without traditional dams. Some variations of this idea are called “run of the river”. (Because of the variability of river flows, this version of hydropower doesn’t produce a consistent level of energy like a coal-burning plant. As with other renewables, it too will need more efficient and cost-effective means of storing electricity – batteries, super-capacitors, etc.)
The quizzical stares I received could most diplomatically be translated as “Why would we do that? Hydraulic engineering is centuries old and has been well established”. However, the sciences of materials and fluid dynamics is dramatically better now than it was even seventy or a hundred years ago and it calls for a much stepped up effort in new hydraulic engineering than has taken place. Periodically, the experts publicly say this as in “Hydraulic engineering in the 21st century: Where to?”
As it turned out, a year or two later in 2011/2012, there was a peak of activity in hydropower experiments in the UK, Germany, Canada, Japan, and India. Here are just some of the more interesting examples:
· Halliday Hydropower’s Hydroscrew
· The Hydro Cat, free floating
· Blue Freedom’s “world’s smallest hydropower plant” is intended primarily for small mobile devices as their slogan says “1 hour of Blue Freedom in the river. 10 hours of power for your smartphone”
· In an unusual twist on this topic, Lucid Energy harnessed the power of water flowing through urban pipes.
These were interesting prototypes, experiments and small businesses, but without the kind of academic and financial support seen in the IT industry, these don’t seem to have the necessary scale to make an impact – notwithstanding the release two months ago of a Hydropower vision paper by the US Department of Energy. I’d love to be corrected on this observation.
Perhaps this is another example of a disruptive technology, in the way that its creator, Clayton Christensen, originally defined the term. Disruptive technologies start to be used at the low end of the market where people have few or no other choices – places like India and the backcountry of advanced economies which are poorly served by the electrical grid, if at all. Only later, possibly, will these products be able to go upmarket.
Too much of the discussion about disruptive technologies has been limited to information technology. There can be disruptive technologies in other fields to solve problems that are just as important, perhaps more important, than the ones that app programmers solve – like renewable energy.
Only time will tell if the technology and markets develop sufficiently so that run of the river and similar hydropower becomes one of the successful disruptive technologies.
© 2016 Norman Jacknis, All Rights Reserved
A part of my research in graduate school included modeling a small,
but influential, network of individuals – the US Supreme Court. I used
the mathematical models tools available. I even represented the court’s
decisions in a Markov chain and computed characteristics like its
You can be excused if you’ve never heard about any of
this or even about Markov chains. Nobody at the time was much
interested either. But I suppose I should have stayed with it, with
books now being published on the impact of the Internet and network
Consider the new book, The Seventh Sense: Power, Fortune, and Survival in the Age of Networks.
It was written by Joshua Cooper Ramo, who is Vice Chairman and Co-CEO
of Kissinger Associates, and a member of the board of directors of
Starbucks and FedEx.
It emphasizes the importance of networks and
declaring that there is still a wide-open gap in the tools most of us
have for understanding these networks.
In an interview about the book, he set out his goal:
live in an age where almost everything changes because of
connectivity… The seventh sense is the idea that some people have an
instinct for how this works that’s better, sharper than the rest of us.
The book is designed to teach people how to think about connected
systems so that they can have the same kind of edge. The people who see
what’s coming in financial markets or in politics have that edge. It’s
important that the rest of us develop it, too.”
However, the book
is worth reading for what it is, not what he wants it to be. It is
unusual in probing the subtleties — both positive and negative — of our
network age, not the usual breathless or self-promoting material.
of the book describes the various ways that being connected can change
the characteristics and behavior of businesses, organizations,
governments – everything that we’ve inherited from the industrial era.
has been made in various other reviews and discussions of this book
about its the scary descriptions of security issues and other dangers in
networks. That wasn’t news to me and shouldn’t be news to most network
users who have been paying any attention.
Some people have
complained that the book is so wide ranging and repetitive it can be
frustrating to read. Parts go into related space, where he worries
that it’s not just the network, but artificial intelligence that is
surpassing us in ways we don’t understand. But this isn’t a blog of
literary criticism, so I’ll skip over that and go to the substance.
his day job at Kissinger Associates, I thought the most interesting
themes had to do with the interaction between the new global technology
network and the traditional institutions of government, business and
Two themes, in particular, stand out:
we all seem to be connected, Ramo writes that the Internet is really
divided into various gated communities. He states that “gatedness is
the corollary to connectedness” and this gatedness is a potential
At one point, he worries that you will have to be among
the rulers — presumably those with the seventh sense or at least those
controlling the gates — or the ruled. He says the network gives people
more power against the gatekeepers than in traditional institutions, but
also notes that the average person may nevertheless need to be inside
the gate to lead a satisfactory life and make a living – so there’s
really no choice after all.
Aside from the problem he mentions, why is this important?
no matter their ideology and internal practices, in the past few
centuries, all governments are fundamentally in the business of
controlling a specific bordered territory — maintaining the physical
gates. He posits that the Internet’s gatekeepers — Facebook, or Apple
iOS, etc. —are taking over that role in the cyberworld. He says that
they are the powerful ones to watch out for in future wars between
networks and the state and between networks and other networks.
others have considered the potential of a conflict between governments
and the Internet. Last summer, for example, the Wilson Quarterly had an
article responding to this concern, “The Nation-State: Not Dead Yet”.
biggest weakness in the book and others of this kind is that the lack
of nuance in the discussion of networks. The fact that there can be a
distribution of power and gates in networks doesn’t end the story.
Partly the problem with these books is that the question of what nodes
(and entry points) of a network are most influential isn’t one that
can’t be answered merely in words.
Pictures help convey a bit more, and – going back to my graduate school research – mathematics helps even more.
as you read Ramo’s book and his concerns, you get the sense that his
view of the network is similar to this picture of Indiana University’s
Big Red network:
But perhaps the world outside of such tightly
controlled campuses is more like the collaborative network of Oak Ridge
Or something different.
And although a node’s
place in a network can show its potential influence, these graphs merely
show connections, not actual influence or power. Unfortunately, the
publicly available analysis of influence over the billions of nodes and
endpoints of the Internet is still primitive. Moreover, to his point,
it is also changing.
This book is a bit like Jefferson’s view of
the Louisiana Purchase before the Lewis and Clark expedition. Jefferson
had a sense it was worth buying, but needed to send out scouts to find
out the details. While they didn’t learn everything there was to learn
about the territory, much of what they did learn was changed over time
That too will characterize our understanding of the network we explore each day.
© 2016 Norman Jacknis, All Rights Reserved
The conventional wisdom in economic development calls for growth strategies that are based on clusters of businesses in the same sector. Here are just a few examples of the many cluster-based economic plans that I’ve come across from one end of the country to the other:
The problem with this conventional wisdom is that it is increasingly unwise.
Princeton University Economics Professor Paul Krugman won the 2008 Nobel Prize for his work 20-30 years earlier in identifying the “new economic geography” (the theoretical foundation of the cluster approach). But in his acceptance speech, he noted changes:
“[Clustering] may describe forces that are waning rather than gathering strength.”
“The data accord with common perception: many of the traditional localizations of industry have declined (think of the Akron rubber industry), and those that have arisen, such as Silicon Valley, don’t seem comparable in scale.”
A European report from 2011 found:
“Business clusters could be less relevant as drivers of innovation than has been commonly assumed. The Stavanger Centre for Innovation Research analysed 1,600 companies with more than 10 employees located in the five largest Norwegian city-regions. Rather than national clusters, international cooperation or global pipelines were identified as the main drivers of innovation.”
For his University of North Carolina Ph.D. thesis research titled, “Cluster Requiem And The Rise Of Cumulative Growth Theory”, Dr. Gary Kunkle tracked the growth and survival of a cohort of more than 300,000 establishments operating in Pennsylvania from 1997-2007. His findings:
“Industry cluster theory has … an inability to explain economic dispersion and the presence of high-growing firms that thrive in non-clustered industries and locations.”
“Firm characteristics are 10-times more powerful than industry and cluster characteristics, and 50-times more powerful than location characteristics, in explaining and predicting establishment-level growth and survival”
“A sub-set of businesses systematically accumulate a disproportionate share of employment growth. Roughly 1% of establishments created 169% of all net new jobs added in the state over a ten-year period.”
This latter point is one of the reasons that the Economic Gardening movement, led by Chris Gibbons, has arisen as an insurgent force within the economic development world. It concentrates on the small proportion of enterprises that create the most new jobs.
There is nothing wrong with encouraging any existing local business to grow – again an economic gardening strategy. But it is foolish to try to build a region’s economic development strategy around a cluster where none exists.
While many regions try to be more sophisticated in their approach, too often, I’ve heard people say that they have a few web design firms and from that they’re going to invest in building a “high tech cluster”. Every town has someone who claims to design websites. Really, that’s not a cluster even in the old industrial era. And it’s not an effective strategy for economic growth in this era.
The famous economist John Maynard Keynes once said “Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist.” While some of the economists who developed cluster approaches are not quite defunct yet, the message is the still relevant.
We are in an economy where everyone in the world is connected by information and communications technologies. For residents of any city or state to flourish economically, they should not be limited to a cluster of business activity which is based on purely local, physical proximity.
© 2015 Norman Jacknis