Mary Meeker’s 2016 Internet Trends Presentation

"Blue Marble - 2002", Image by NASA Goddard Space Flight Center

“Blue Marble – 2002”, Image by NASA Goddard Space Flight Center

On June 1, 2016, at the 2016 Code Conference held this week in California, Mary Meeker, a world-renowned Internet expert and partner in the venture capital firm Kleiner Perkins, presented her fifteenth annual in-depth and highly analytical presentation on current Internet trends. It is an absolutely remarkable accomplishment that is highly respected throughout the global technology industry and economy. The video of her speech is available here on Recode.com

Her 2016 Internet Trends presentation file is divided into a series of eight main sections covering, among many other things: Internet user and financial growth rates, online advertising, generational market segments and technological preferences, new products and vendors, mobile screens for nearly everything, e-commerce, big data, privacy issues, video growth on social media platforms, messaging systems , smartphone growth,  voice interfaces, consumer spending, online security, connectivity, Facebook’s v. Google’s growth rates, and massive consumer markets in China and India. That is just the tip of the tip of the iceberg in this 213-slide file.

Ms. Meeker’s assessments and predictions here form an extraordinarily comprehensive and insightful piece of work. There is much here for anyone and everyone to learn and consider in the current and trending states nearly anything and everything online. Moreover, there are likely many potential opportunities for new and established businesses, as well as other institutions, within this file.

I very highly recommend that you set aside some time to thoroughly read through Ms. Meeker’s full presentation. You will be richly rewarded with knowledge and insight that can potentially yield a world of informative and practical dividends.

The Predictive Benefits of Analyzing Employees’ Communications Networks

Image from Pixabay

Image from Pixabay

In the wake of the destruction left by the Enron scandal and subsequent bankruptcy in the early 2000s, one of the more revelatory and instructive artifacts left behind was the massive trove of approximately 1,600,000 of the company’s corporate emails. Researchers from a variety of fields have performed all manner of extensive analyses on this “corpus” of emails as it known. Of particular interest was the structure and operations of this failed company’s communications network. That is, simply stated, extracting and examining who’s who and what’s what in this failed organization.

No other database of this type, size and depth had ever been previously available for such purposes. What the researchers have learned from this and its subsequent and significant influences in many public and private sectors was the subject of a fascinating article in MIT Technology Review posted on July 2, 2013 entitled The Immortal Life of the Enron E-mails by Jessica Lander. I highly recommend reading this.

[July 18, 2017 Update:  For a new deep and wide analysis of the Enron email database, see What the Enron E-Mails Say About Us, by Nathan Heller, in the 7/24/17 edition of The New Yorker.]

I immediately recalled this piece recently while reading a column posted on the Harvard Business Review blog on February 10, 2016 entitled What Work Email Can Reveal About Performance and Potential by Chantrelle Nielsen. This analytical processes and consulting projects it describes could be of highly practical value to all manners and sizes of organizations. I also suggest reading this in its entirety. I will summarize, annotate and pose some emoji-free questions of my own.

I believe this post will also provide a logical follow-on to the February 15, 2016 Subway Fold post entitled Establishing a Persuasive Digital Footprint for Competing in Today’s Job Market. That post covered the importance a job candidate’s digital presence before being hired while this post covers the predictive potential of an employee’s digital presence after they have become an employee and integrated themselves into an organization.

Data Generation

The author begins by focusing her attention upon the modern tools and platforms used in the workplace for people to communicate and collaborate such as Skype and Slack. More traditionally, there is email. While these modes are important, they can also be a “mixed blessing”. Careful management of these technologies can assist is determining which forms of “digital communications are productive” for both employers and their employees.

Most importantly, these systems produce huge volumes of data. As a result, some firms are developing “next generation products” containing analytical capabilities to deeply dive into these databases and the networks they support.¹,²

The author mentions that her former company, VoloMetrix, is engaged in this field and has been acquired by Microsoft. The examples and her article concern work done for the firm’s clients before it become part of MS. During this time, VoloMetrix worked for years “with executives in large enterprises” to enable them to discern patterns within employees’ digital communications.

Predicting Employee Performance

A “strong network” can be a predictive factor of an employee’s performance. For example, a software company looked at a year’s worth of anonymized employee email data across all job categories. The findings showed that:

  • The best performers were characterized by 36% larger in-house networks, when compared to average performers, where they connected “at least biweekly in small group messages”. (This criterion was used to determine “strong ties”).
  • The lower performers exhibited “6% smaller networks” when compared to average performers.

On an annual basis, the “size and strength” of employees’ networks proved to a better predictor of their performances than managers’ more traditional assessments. Thus, being “intensely engaged” in collaborating with their peers was a driver of their work performance.

This effect was likewise seen at other business-to-business sales concerns. For instance, at a software company the top 10 workers in sales were, on average, connected to 10 or more of their colleagues. Their internal networks proved to be 25% larger than the networks of low performers. When social graph data (used to visualize the structures of networks), was examined it frequently indicated that connections within a company were even more important than those outside of it.

Predicting Employee Potential

Some businesses use “engagement programs” to assist the careers of employees are seen as having high potential to become future leaders. For example, a utility company studied the networks of a few hundreds of these people. They discovered that:

  • Those people who “were often the most connected” were shown to have networks “52% larger than average”.
  • Nonetheless, there were still others within this same group having networks of “below average” dimensions.

Managers surveyed reported that the less connected workers also had “great skills or ideas”, but displayed “potentially less” extroversion³ or emotional intelligence 4 needed to become influential. Still, opportunities are available to assist these people to “gain a broader audience” with better connected “agents” who, in turn, can promote their ideas.

Furthermore, growing a large network only for its own sake is not always the optimal approach. Rather, some networks are “more effective” because of who they include. That is, if they include people who have higher degrees of influence.

Another client, a hardware company, advanced their analysis to examine the “composition and quality” of the networks assembled by their sales reps. Their findings indicated that:

  • The “involvement of certain sales roles” corresponded to a 10X increase in the size of deals with customers.
  • Some sales roles were characterized as “middlemen” and, as such, did not “clearly demonstrate” anyone’s personal leadership potential.

Synthesizing Two Approaches

As described above, two analytical approaches have emerged for examining and leveraging the insights gained from communications networks. Both can work well in conjunction with the other. First is awareness whereby business leaders:

  • Communicate the importance of building networks
  • Provide the network analytical tools
  • Maintain the “faith” that their employees will understand this message and act upon it

The second is the prediction of outcomes, most often by sales organization to determine “which deals will close”. While this currently is applied less often than the awareness approach, this situation is now changing.

The insights gained from studying communications networks which are then applied to help build better working relationships and performance, must be “used thoughtfully” while balancing human and technological factors. Moreover, for these to work properly and “make connections more meaningful and efficient”, effectively gathering sufficient data on how employees do their jobs and communicate with their peers is essential.

My Questions

  • What standards should be established to assess communication and collaboration networks? Should they be the same for all businesses and job types or varied from field to field? Should they be differentiated further from employer to employer within a field and then perhaps for every department and job title within the same firm? (For some excellent new reading on how professional networks compare in their breadth and effectiveness in different professions, I highly recommend reading another new article on The Harvard Business Review blog posted on February 19, 2016 entitled How Having an MBA vs. a Law Degree Shapes Your Network by Adina Sterling.)
  • How should “influential” members of a network be defined in a business environment? Is influencer marketing, where individuals with a significant online presence appear to have more influence upon others in their social networks and are thus given special attention by marketers, the correct model to consider?  If so, should businesses consider developing and applying the equivalent of a Klout score to their employees? (This is an online service that rates one’s relative influence across much of social media.)
  • Would it be helpful to a company’s workforce to make this data and analytics readily available to everyone on their internal network and, if so, what would be the benefits and/or drawbacks of doing so? Would access to one’s network’s shape and reach result in some unintended consequences such as pressuring workers to increase the size of their internal and external contacts?
  • Should rewards systems be piloted to see whether they can positively incentivize employees to nurture their networks? For example, for X amount of new contacts added that support a company’s goals, Y additional days off might be awarded.
  • Can network analytics be used to fairly or unfairly restrict workers with non-competition and non-disclosure clauses when they change jobs?

 


1.   Many of these 26 Subway Fold posts under the Category of Social Media also involve metrics and analytical systems for interpreting the voluminous data generated by a wide range of social media services.

2.  A thriving market exists today in enterprise search products that can index, search and unlock the valuable knowledge embedded deep within corporate email and other data platforms. Here is a list of vendors on Wikipedia.

3.  For a completely different and highly engaging analysis of the virtues of being an introvert in social and business environments, I highly recommend reading a recent bestseller entitled Quiet: The Power of Introverts in a World That Can’t Stop Talking (Broadway Books, 2013), by Susan Cain.

4.  The authoritative and highly regarded work on this subject is Emotional Intelligence: Why It Can Matter More Than IQ (Bantam Books, 2005), by Daniel Goleman.

New Startup’s Legal Research App is Driven by Watson’s AI Technology

"Supreme Court, 60 Centre Street, Lower Manhattan", Image by Jeffrey Zeldman

[New York] “Supreme Court, 60 Centre Street, Lower Manhattan”, Image by Jeffrey Zeldman

May 9, 2016: An update on this post appears below.


Casey Stengel had a very long, productive and colorful career in professional baseball as a player for five teams and later as a manager for four teams. He was also consistently quotable (although not to the extraordinary extent of his Yankee teammate Yogi Berra). Among the many things Casey said was his frequent use of the imperative “You could look it up”¹.

Transposing this gem of wisdom from baseball to law practice², looking something up has recently taken on an entirely new meaning. According to a fascinating article posted on Wired.com on August 8, 2015 entitled Your Lawyer May Soon Ask for This AI-Powered App for Legal Help by Davey Alba, a startup called ROSS Intelligence has created a unique new system for legal research. I will summarize, annotate and pose a few questions of my own.

One of the founders of ROSS, Jimoh Ovbiagele (@findingjimoh), was influenced by his childhood and adolescent experiences to pursue studying either law or computer science. He chose the latter and eventually ended up working on an artificial intelligence (AI) project at the University of Toronto. It occurred to him then that machine learning (a branch of AI), would be a helpful means to assist lawyers with their daily research requirements.

Mr. Ovbiagele joined with a group of co-founders from diverse fields including “law to computers to neuroscience” in order to launch ROSS Intelligence. The legal research app they have created is built upon the AI capabilities of IBM’s Watson as well as voice recognition. Since June, it has been tested in “small-scale pilot programs inside law firms”.

AI, machine learning, and IBM’s Watson technology have been variously taken up in these nine Subway Fold posts. Among them, the September 1, 2014 post entitled Possible Futures for Artificial Intelligence in Law Practice covered the possible legal applications of IBM’s Watson (prior to the advent of ROSS), and the technology of a startup called Viv Labs.

Essentially, the new ROSS app enables users to ask legal research questions in natural language. (See also the July 31, 2015 Subway Fold post entitled Watson, is That You? Yes, and I’ve Just Demo-ed My Analytics Skills at IBM’s New York Office.) Similar in operation to Apple’s Siri, when a question is verbally posed to ROSS, it searches through its data base of legal documents to provide an answer along with the source documents used to derive it. The reply is also assessed and assigned a “confidence rating”. The app further prompts the user to evaluate the response’s accuracy with an onscreen “thumbs up” or “thumbs down”. The latter will prompt ROSS to produce another result.

Andrew Arruda (@AndrewArruda), another co-founder of ROSS, described the development process as beginning with a “blank slate” version of Watson into which they uploaded “thousands of pages of legal documents”, and trained their system to make use of Watson’s “question-and-answer APIs³. Next, they added machine learning capabilities they called “LegalRank” (a reference to Google’s PageRank algorithm), which, among others things, designates preferential results depending upon the supporting documents’ numbers of citations and the deciding courts’ jurisdiction.

ROSS is currently concentrating on bankruptcy and insolvency issues. Mr. Ovbiagele and Mr. Arruda are sanguine about the possibilities of adding other practice areas to its capabilities. Furthermore, they believe that this would meaningfully reduce the $9.6 billion annually spent on legal research, some of which is presently being outsourced to other countries.

In another recent and unprecedented development, the global law firm Dentons has formed its own incubator for legal technology startups called NextLaw Labs. According to this August 7, 2015 news release on Denton’s website, the first company they have signed up for their portfolio is ROSS Intelligence.

Although it might be too early to exclaim “You could look it up” at this point, my own questions are as follows:

  • What pricing model(s) will ROSS use to determine the cost structure of their service?
  • Will ROSS consider making its app available to public interest attorneys and public defenders who might otherwise not have the resources to pay for access fees?
  • Will ROSS consider making their service available to the local, state and federal courts?
  • Should ROSS make their service available to law schools or might this somehow impair their traditional teaching of the fundamentals of legal research?
  • Will ROSS consider making their service available to non-lawyers in order to assist them in represent themselves on a pro se basis?
  • In addition to ROSS, what other entrepreneurial opportunities exist for other legal startups to deploy Watson technology?

Finally, for an excellent roundup of five recent articles and blog posts about the prospects of Watson for law practice, I highly recommend a click-through to read Five Solid Links to Get Smart on What Watson Means for Legal, by Frank Strong, posted on The Business of Law Blog on August 11, 2015.


May 9, 2016 Update:  The global law firm of Baker & Hostetler, headquartered in Cleveland, Ohio, has become the first US AmLaw 100 firm to announce that it has licensed the ROSS Intelligence’s AI product for its bankruptcy practice. The full details on this were covered in an article posted on May 6, 2016 entitled AI Pioneer ROSS Intelligence Lands Its First Big Law Clients by Susan Beck, on Law.com.

Some follow up questions:

  • Will other large law firms, as well as medium and smaller firms, and in-house corporate departments soon be following this lead?
  • Will they instead wait and see whether this produces tangible results for attorneys and their clients?
  • If so, what would these results look like in terms of the quality of legal services rendered, legal business development, client satisfaction, and/or the incentives for other legal startups to move into the legal AI space?

1.  This was also the title of one of his many biographies,  written by Maury Allen, published Times Books in 1979.

2.  For the best of both worlds, see the legendary law review article entitled The Common Law Origins of the Infield Fly Rule, by William S. Stevens, 123 U. Penn. L. Rev. 1474 (1975).

3For more details about APIs see the July 2, 2015 Subway Fold post entitled The Need for Specialized Application Programming Interfaces for Human Genomics R&D Initiatives

Companies Are Forming Digital Advisory Panels To Help Keep Pace With Trending Technologies

"Empty Boardroom", Image by reynermedia

“Empty Boardroom”, Image by reynermedia

As a result of the lightening-fast rates of change in social media, big data and analytics, and online commerce¹, some large corporations have recently created digital advisory panels (also called  “boards”, “councils” and “groups” in place of “panels”), to assist executives in keeping pace with implementing some of the latest technologies. These panels are being patterned as less formal and scaled-down counterparts of traditional boards of directors.

This story was covered in a fascinating and very instructive article in the June 10, 2015 edition of The Wall Street Journal entitled “Companies Set Up Advisory Boards to Improve Digital Savvy” (subscription required, however, the article is fully available here on nasdaq.com). I will sum up, annotate and add a few questions of my own.

These digital advisory panels are often composed of “six outside experts under 50 years old”. In regularly scheduled meetings, their objective is to assist corporate managers in reaching diverse demographics and using new tools such as virtual reality² for marketing purposes. The executives whom the panels serve are appreciative of their “honest feedback”, access to entrepreneurs, and perspectives on these digital matters.

George L. Davis at the executive recruiting firm Egon Zehnder reports that approximately 50 companies in the Fortune 500 have already set up digital advisory panels. These include, among others, Target Corp. (details below) and American Express. However, not all such panels have not continued to stay in operation.

Here are the experiences of three major corporations with their digital advisory panels:

1. General Electric

GE’s digital advisory panel has met every quarter since its inception in 2011. Its members are drawn from a diversity of fields such as gaming and data visualization³. The youngest member of their 2014 panel was Christina Xu. She is a co-founder of a consulting company called PL Data. She found her experience with GE to be “an interesting window” into a corporate environment.

Ms. Xu played a key role in creating something new that has already drawn eight million downloads. It’s called the GE Sound Pack, a collection of factory sounds recorded at their own industrial facilities, intended for use by musicians4.  In effect, with projects like this the company is using the web in new ways to enhance its online presence and reputation.

GE’s panel also participated in the company’s remembrance of the 45th anniversary of the first moon landing. Back then, the company made the silicon rubber for the Apollo 11 astronauts’ boots. To commemorate in 2014, the panel convinced GE to create and market a limited edition line of “Moon Boot” sneakers online. They sold out in seven minutes. (For more details but, unfortunately, no more chances to get a pair of these way cool sneakers, see an article with photos of them entitled GE Modernizes Moon Boots and Sells Them as Sneakers, by Belinda Lanks, posted on Bloomberg.com on July 16, 2014 .)

2.  Target Corporation

On Target’s digital advisory council,  Ajay Agarwal, who is the Managing Director of Bain Capital Ventures in Palo Alto, California, is one of its four members. He was told by the company that “there were ‘no sacred cows’ “. Among the council’s recommendations was to increase Target’s staff of data scientists faster than originally planned, and to deploy new forms of in-store and online product displays.

Another council member, Sam Yagin, the CEO of Match.com,  viewed a “showcase” Target store and was concerned that it looked just like other locations. He had instead expected advanced and personalized features such as “smart” shopping carts linked to shoppers’ mobile phones that would serve to make shopping more individualized. Casey Carl, the chief strategy and innovation officer at Target, agreed with his assessment.

3.  Medtronic PLC

This medical device manufacturer’s product includes insulin pumps for people with diabetes.5 They have been working with their digital advisory board, founded in 2011, to establish a “rapport” on social media with this community. One of the board’s members, Kay Madati, who was previously an executive at Facebook, recommended a more streamlined approach using a Facebook page. The goal was to build patient loyalty. Today, this FB page (clickable here), has more than 230,000 followers. Another initiative was launched to expand Medtronics’ public perception beyond being a medical device manufacturer.

This digital advisory board was suspended following the company’s acquisition and re-incorporation in Ireland. Nonetheless, an executive expects the advisory board to be revived within six months.

My questions are as follows:

  • Would it be advisable for a member of a digital advisory panel to also sit on another company’s panel, given that it would not be a competitor? Would both the individual and both corporations benefit by the possible cross-pollination of ideas from different markets?
  • What guidelines should be established for choosing members of such panels in terms of their qualifications and then vetting them for any possible business or legal conflicts?
  • What forms of ethical rules and guidelines should be imposed panel members? If so, who should draft,  approve, and then implement them?
  • What other industries, marketplaces, government agencies, schools and public movements might likewise benefit from their own digital advisory panels? Would established tech companies and/or startups likewise find benefits from them?
  • Might finding and recruiting members for a digital advisory panel be a new market segment for executive search firms?
  • What new entrepreneurial opportunities might emerge when and if digital advisory panels continue to grow in acceptance and popularity?

 


1.   All of which are covered in dozens of Subway Fold posts in their respective categories here, here and here.

2.  There are six recent Subway Fold posts in the category of Virtual and Augmented Reality.

3.  There are 21 recent Subway Fold posts in the category of Visualization.

4.   When I first read this, it made me think of Factory by Bruce Springsteen on his brilliant Darkness on the Edge of Town album.

5.   X-ref to the October 3, 2014 Subway Fold post entitled New Startups, Hacks and Conferences Focused Upon Health Data and Analytics concerning Project Night Scout involving a group of engineers working independently to provide additional mobile technology integration and support for people using insulin pumps.

Comprehensive Visualization of Future Paths of Technological Innovations

Data visualization tools and applications seem grow more intricate and original, and indeed more artistically bold and engaging, each day. Today, 4/8/14, is no exception as demonstrated in an new article posted on BusinessInsider.com entitled Science More: Health Future Science These Beautiful Charts Show The Coming Technologies That Will Change The World by Gus Lubin. He reports about a group of several private and Canadian governmental groups who have jointly produced a rather astonishing grahpics presentation predicting the development timelines on six major areas of technology. All of these are zoomable online for more detailed viewing. There is a single graphic that combines all six areas. Each of these six sectors are also individualls downloadable in PDF. They include:

  • Agricultural and Natural Manufacturing Technologies
  • Data and Communications Technologies
  • Energy Technologies
  • Health Technologies
  • Nantotechnology and Materials Science
  • Neurotechnology and Cognitive Technologies

Each of these sectors is broken down into subsections for specific developments and then each is expressed in a predictive timeline spanning the next 15 years.

While no one can accurately predict the future development paths of these sectors and the arrival dates of their presently percolating deliverables, these graphics are nonetheless a highly ambitious and original representations of what might occur. I highly recommend a click through and examination of these visualizations to appreciate the magnitude of this undertaking. Moreover, viewers might also see a challenge and find the inspiration to perhaps start or add something new that may one day appear in an update of this chart in, well, the future.

After spending some time exploring these graphics, I was reminded of the well known quote from the renowned computer scientist, Alan Kay, who once very famously said “The best way to predict the future is to invent it.”