‘Soldiers for Summits’ is a Great Way To Help Military Veterans


sfs tent

SfS Tent Banner at Everest BC, 2014.

Michael Fairman is an Afghanistan veteran (USN Hospital Corpsman, Fleet Marine Force) who served his country and many others in so doing for 19 years. His father was also a veteran and his son recently returned from his first deployment. Mike is also co-founder of Soldiers for Summits, which is focused on reducing the suicide epidemic afflicting returning veterans.

I was recently introduced to Mike through an old mutual friend Andy Politz, who I met while living and working at Mt. Rainier in 1980. My wife Betsy and I moved on a couple of years later to start a business while Andy returned to Rainier as a mountain guide alongside other climbers our age like Dave Hahn and Ed Viesturs (see Whittaker Mountaineering or International Mountain Guides).

Andy Politz on 2009 Mallory Irvine Everest Expedition

Andy and Mike have been taking vets into the mountains as part of the healing process for several years now, which I can personally confirm is a worthy effort. A life-long mountain lover, I also sought healing in the mountains during my youth when my late father (USAF Major Floyd L. Montgomery) returned from Vietnam with serious health issues that impacted our entire family. My father eventually recovered and enjoyed many good years, but a large number of veterans don’t.

  • Every 65 minutes, a military veteran commits suicide.

  • 22 military veterans commit suicide every day.

  • 31 percent of these suicides were veterans aged 49 and younger.

  • Every month nearly 1,000 veterans attempt to take their own lives.

  • Suicides among active duty personnel outpace killed in action.

  • From 2002 to December 2012, 253,330 service members were diagnosed with a Traumatic Brain Injury (TBI) of some kind.

  • 11-20% of troops suffer from PTSD who served in OIF/OEF (Operation Enduring Freedom/Operation Iraqi Freedom). 300,000-500,000 report to VA, presumably unknown number do not or have yet to report. (VA/Rand/PBS)

I reached out to Andy by email a couple of weeks ago to explore ways to help, and somewhat serendipitously Andy replied from the base of Kilimanjaro, which he and Mike had just climbed as part of Mike’s bid to climb the 7 summits to raise awareness for Post Traumatic Stress (PTS) and suicide prevention for veterans.  

Kili Summit photo

Mike and his wife Beth on Kilimanjaro (2nd summit) on 15 Sep 2014.

andy and mike

Mike and Andy Politz; Barranco Wall, Kilimanjaro.

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Summit for Soldiers

“A bunch of personally attached, self-funded combat veterans, families and mountaineers who are dedicated to continue to serve our veterans anyway we can.”

(All quotes are from Mike Fairman from email exchanges last week).

“Andy Politz has been awesome in helping me/us with our efforts, which includes my bid to climb the 7-summits of the world. So far this year I have reached the summits of Aconcagua and Kilimanjaro, and an attempt of Everest, which was cut short due to the loss of 16 Sherpas in the icefall disaster.”

(MM: Planning another attempt of Everest in 2015).

MEMORy ACT (Mental-health Exposure Military Official Record Act)

“One thing our group has done is identify an simple, safe, cost-effective fix within the DOD to track, verify and document events to eliminate future backlogs at the VA (this is currently not being done outside of those that are seriously injured) and our “grassroots” veterans created effort has led to bipartisan legislation that has been introduced as a Bill into both the HOUSE and the SENATE, we also have endorsements from every major Veterans Service Organization like the VFW and IAVA. If and when this is enacted it will better serve every veteran of the future, currently 10’s of 1000’s of veterans are turned away because of poor/lacking documentation. (You can learn more at my website: www.MemoryAct.org )”

VFW Sen Brown Me

Mike with US Sen. Brown (OH)

The goals of the MEMORy ACT reflect a similar philosophy to our work at Kyield, which is a holistic approach (Unified Network OS) for data management to close such gaps. One of the biggest challenges in caring for returning veterans is the well-known bureaucracy and archaic technology architecture which is extremely frustrating for anyone, so one can only imagine what it must be like for veterans to return home from war, discover a serious problem, and attempt to get help from the VA system only to learn that the evidence one needs to qualify for care will either take years to process, or wasn’t documented properly.

While healthcare and disability fraud is a serious problem across the U.S., accurate data on a real-time basis for the duration would allow for fraud prevention as well as proper care for those who are entitled to care. Importantly, such programs would move the DoD and VA towards much needed personalized healthcare that empowers active duty families as well as vets, which is critical for prevention, life science research, and optimizing a terribly inefficient healthcare system that is full of dedicated people, but decades behind where it should be. While I am one who agrees that the U.S. military needs the world’s most sophisticated weaponry, I’m also one who warns that we better start treating soldiers on the front lines with the same priority or it may not matter much.

“My reasons for launching on this challenge are:  One, to show my example as a veteran who struggles with mental-health injuries (including a former suicide attempt) that you CAN take back control of your life and achieve “lofty” goals. Second, is to draw attention to our mission and efforts. And finally, the main reason is to carry a flag that bears the names of some of the warriors we have known and loss to suicide… the first name on the flag was one of my marines, LCPL Bob Wiley. The Wiley family is one of many families that have got behind this effort to raise awareness and help us continue to find ways to reduce the over 8000 veteran suicides that occur each year.”

“I totally agree with what you mention about veterans healing in the mountains. We launched on this “mission” because we realized our personal therapy came from our “adventures” and our analogy was that just like dealing/struggling with PTS/Depression you work together, trust your team, and experience the good/bad together, and eventually (in spite of all the circumstances out of our control) you reach the summit. Only to go down and do it all again!”

“I am grateful to the VA and my team there, they saved my life, but that said the system has become a catch-22 for so many folks in that it almost promotes the very stigma we are trying to destroy. What I mean is this, we go to the VA, they tell us we have a problem, they intervene, treat us and compensate us for the problem. Now we are “disabled” and the tendency is to just return to the place where we can find support and because we are now technically “disabled” we simply look to that system for guidance and support. Now, I suppose I’m a bit of a hypocrite because the legislation we have developed would make sure every veteran who needs help can get it quickly without obstacles, but our intention is directed towards a DOD fix on the front end to ensure people get into the VA system that was designed to do all of the above to help get them back on their feet.”

wiley memorial

Memorial on Aconcagua. Photo of Marine LCPL Bob Wiley.

“For me the VA was the place to “reset” my physical life by sorting through my issues, diagnosis and treatments to make sure I can be safe, but the healing and repair comes after we “reset” and realize that the things we endured are in the past, and we CAN take back control of our lives… And that comes from engaging in life, reconnecting with family, finding a new purpose outside of the military and for me/us that is the mountains. A big part of the endeavor at SfS plays into my own personal therapy! In fact, many veterans that have launched on their respective causes/missions do so as part of their recovery/therapies.”

“My big vision for SfS (after we finish up this legislative opportunity we have been given) is to see it grow into state chapters that become an outdoor gathering/support group for veterans and those interested, along with a place of refuge and resource for veterans specific issues. In other words, you go out for some weekend adventures with other veterans, have a place where you can talk about what is going on, and point folks in the appropriate direction for what they need. Kind of like a new version of the VFW, but built around outdoor activities instead of just sitting around drinking in a dark room.”

CMF Afghan

C. Michael Fairman, Pre-patrol in Afghanistan, HM2 (FMF) USN (Hospital Corpsman, Fleet Marine Force) USMC Lima Company

I’d like to thank Mike for his efforts and candor. Having grown up in a military family with many friends who lost fathers in battle, I vividly recall being part of a culture that while supporting each other as family, are also trained to withhold information on a pragmatic need-to-know basis (even from family). Combined with mental health challenges and a society back home that is typically clueless to the challenges and sacrifice required of a great many so that the majority can live in relative peace, communications can be a real problem, particularly when awareness in a democracy is necessary to move the biggest mountains of all in the form of the DoD, VA, and members of the U.S. Congress.

How Business Leaders Can Help

My company is deeply involved in the issues surrounding optimized healthcare, and we’ve been working with the DoD for many years on related technology. If Kyield is even modestly successful as we commercialize our technology, we plan to sponsor Mike’s vision for a new kind of VFW focused on beneficial outings in nature. In the interim, a huge opportunity exists for private companies to sponsor the formation of a national organization dedicated to Mike’s vision and mission. It’s clear to me that the time has come to support this worthy effort, assist with funding, and help set up a sustainable organizational structure with local chapters. I think SfS could scale well and rapidly with assistance.

While such a sponsorship would seem particularly well-matched to companies like USAA, DoD contractors, and pharmaceutical firms, the scale of PST is so vast that it literally impacts every community, which also means it’s an opportunity for giants in retail, banking, tech companies, and many others.

In addition to the tragic ongoing human catastrophe that falls on a quiet minority of families that pay the ultimate price, the economic costs cannot be ignored. Estimates range from $1 trillion to $3 trillion for lifetime care of veterans labeled disabled, much of which is related to pre-existing cases of PST and traumatic brain injury, some unknown large portion of which can be mitigated. Business leaders clearly have a moral, ethical, and financial obligation to engage and assist.

How Journalists Can Help

While the greater problem of PST and VA challenges have been reported, Summit for Soldiers has received little exposure, and it’s a great story waiting to be told. In addition, the MEMORy ACT has a deadline in January so more awareness is needed a.s.a.p. The issues surrounding data management, personalized medicine, preventative care, and economics are timely, relevant, and extremely important.

How Individuals Can Help

Below are links to immediately support efforts underway, whether through contacting your representatives in the House or Senate to support the MEMORy ACT and support veterans generally, small group efforts Andy and Mike are involved with, or the 7 summit bid to raise awareness.

Links:

MEMORy ACT

Summit for Soldiers

Andy Politz’s Ascent with Honor

Support Mike’s 7 Summits Bid

After 120 Labor Day Holidays, What Have We Learned?


In reflecting on the current workforce, global economy, technology, and labor markets, I revisited the origins of the U.S. Labor Day, which is celebrated on the first Monday in September, similar to the International Worker’s Day on May 1.

While the tipping point for political winds appears to have been the Haymarket riot in Chicago in 1886 that eventually led to a national holiday, many other factors occurred during the industrial revolution that are relevant to the present day and so leaders should examine. The two eras are similar in many respects, yet very different in others.

The Haymarket Affair appears to have been triggered by several factors, including a global anarchist movement that fed off of widespread inhumane labor conditions, severe economic swings, enormous wealth gaps, political corruption, and traveling agitators exploiting conditions which led to violence. The actual bomber in the Haymarket riot for example was never found, while others paid the price, including policemen and laborers.

Fighting the Last Economic War?

Some have argued that the FRB has been fighting the last war of the Great Depression, which was after all the specialty (and thesis) of Ben Bernanke. I see more similarities in the current global economic situation today with the Long Depression of the late 1800s, which was the ‘Great Depression’ until the severity of the 1930s took the title. The underlying economic shifts driven by the information revolution, while different than industrial revolution, appear more similar to the late 1800s than the 1920s and 30s.

The most stunning similarities between the present day and the late 1800s are reflected in economic statistics. The Long Depression began with the panic of 1873, which was precipitated by the collapse of Jay Cooke & Company (considered the first investment bank in the U.S.), is the longest lasting U.S. contraction in the NBER records.

While e-commerce contributed to bubbles and crashes in our era, similar dynamics occurred in the late 1800s with industrial production and the opening of the Panama Canal. As is the case today, war was a factor in both the U.S. and Europe, with dynamics of monetary policy contributing to recoveries and triggering failures. Today we deal with the uncertainties of quantitative easing, while in the 1870s the halt to silver currency caused severe shocks and ripples worldwide with economic collapse in regions that had become dependent on silver mining.

The American Civil War ended in April 1865, which was followed by a deflationary period that lasted until 1896. The Franco-Prussian War in 1870-71 was apparently caused in part by German unification during the same period, with repatriation helping to fuel a large regional speculative economic bubble followed of course by a bust. One can see dynamic influences from the dissolution of the Holy Roman Empire and Napoleonic Wars in the early 1800s.

During the period of the Long Depression between1873–96, Europe experienced a sharp decline in prices, resulting in a depression for the majority while some industries boomed as production increased due to transportation and manufacturing efficiencies. The Long Depression finally ending in 1896 after yet another panic.

Similarities Between the Industrial and Information Revolution

  • Excess capital invested poorly caused multiple bubbles and crashes
  • Great productivity increases in each allowed companies to lower prices sharply
  • Modern day wealth gap peaks are found during these two eras
  • Severe exploitation of workers was a significant causal factor in crises within both revolutions, though in very different forms
  • Volatility led to various forms of backlash, including the rise of extreme socialists and anarchists, which then caused even further structural decay

Differences Between the Industrial and Information Revolution

Bonds fueled much of the Civil War and industrial revolution, including door-to-door sales by investment banking sales reps. The information revolution has been funded primarily by institutional VC and IPOs that boycotted small investors through SEC regulations until valuations were mature, or in some cases post mature (aka ‘pump and dump’). While both revolutions required and justified funding based on solid economic fundamentals and legitimate ROI, with very real productivity increases in each—the information revolution is really a continuance of industrial—irrational behavior, oversupply, corruption, and reactions are more similar than not.

While the industrial revolution observed massive displacement of small family farms with tractors (majority of the U.S. population), and railroads replaced wagon trains, the information revolution displaced bookstores and newspapers with search engines, and physical retailers with e-commerce. The later stages of the industrial revolution resulted in interstate highways and intercontinental flight, but we can only speculate on the late stages of the information revolution, due less to technology forecasting than potential backlashes by markets and/or regulators.

Exploitation of workers manifested in much different ways during these two eras. The industrial revolution required large numbers of workers who were experiencing increased buying power, but were not experiencing improved quality of life due to long hours, unhealthy and even deadly working conditions. The information revolution witnessed a severe bubble expansion in the late 1990s and contraction in 2000, followed by subprime mortgage bubble leading to a severe financial collapse in 2008, with enormous losses transferred directly to national debt in Europe and the U.S. Unlike the 1800s when industrial workers toiled long hours in dangerous conditions, today’s workers in the U.S. are physically safe by comparison.

However, today we have vast numbers of workers at all levels of competency supplying content and data with no compensation from the financial beneficiaries for products they supply, which has enabled some of the wealthiest individuals and companies of any era. A large portion of these product suppliers are subsidized by government or corporate compensation, and millions of others by the welfare state. Freeism and lack of protection of intellectual capital on the Internet and Web have been terribly destructive to the structural underpinnings of the global economy; particularly to wealthy nations. Some may see this as justified wealth transfer. I see it as simply historic levels of greed, exploitation, and unhealthy destruction, not to be confused with more healthy forms of creative destruction that replaces outdated industries and companies with newer more beneficial models, products, and services. While our era has all types including highly beneficial models, I’ll save that focus for another day.

The most important contrast between the two revolutions for the average American worker is that real wages increased considerably during the industrial revolution, while they are generally decreasing in the information revolution, with liabilities being transferred to national debt and FRB balance sheet. Translated to every day reality, the average American worker is experiencing a long-term decline in discretionary income while rapidly piling up a long-term increase in share of public debt. It represents a rather unholy relationship between big business and big government as governments borrow to create dependent citizens who are increasingly the product and supply chain as well as end consumer of free products during the information revolution. This trend is surely temporary as it is absolutely unsustainable in any known form of economic model, thus extremely unwise and irresponsible. The question is not whether reforms will come, but rather in what form, when, at what cost, and type. Wars have been fought over much smaller economic tensions, which is one reason the current trajectory is so concerning to many of us.

10 Recommendations For Stronger Economy

While every era of economic crises has experienced serious policy errors, sometimes driven by self-interest and/or politics, and others genuinely well intended, a few strategies are timeless. Below are 10 examples that I think are wise, translated to today’s environment:

  1. Avoid moral hazard, as it tends to create the foundation for the next crisis. Never allow too big to fail, and if it occurs break them up ASAP. Any such event should be fatal not only to the companies involved, but the regulatory bodies that failed to prevent it. Saving failed institutions is extremely toxic to the rest of the economy, and it’s entirely unnecessary.

  2. Never ever tell an entrepreneur “you didn’t build that”, especially from a leader who has never done it, in which case he/she would almost certainly never say such a thing. Anyone who isn’t aware of the benefit of public infrastructure is unlikely to have much of a chance to build anything as our job is in part to find ways to build value on top of that public investment for job and wealth creation, which is apparently much more difficult than most are aware of. Most entrepreneurs take enormous risk and make huge personal sacrifices that few politicians, government workers, or corporate executives will ever comprehend. It is therefore a good idea to limit lectures to topics one has direct experience with and thus avoid doing great harm.

  3. Tie all public funding other than the genuinely disabled to a menu of contributions that align with taxpayers who fund it, whether vocational training, education, civic work, volunteer work, or best of all: subsidized on the job training. Germany has a good public/private program that provides a basic model, which encourages retaining employees in downturns while retraining. Permanent dependency on government is a terrible thing to do to anyone as it damages confidence, reduces self-worth, and is very self-destructive from a socio-economic (and any other I can think of at the moment) perspective.

  4. Stop rewarding toxic behavior to extent possible, including government, education, finance, and/or industry. For example, bankrupting government entities with life-long golden retirement parachutes is toxic and has nothing to do with public service or protecting legitimate worker rights. Indeed, public sector pensions tend to punish other workers in a variety of ways. It should be self-evident, but insolvent governments can’t make good on political promises, whether contractual or not. For mature economies, increasingly ‘the enemy is us’.

  5. Decentralize capitalism. Our era contains very strong natural and unnatural bias towards consolidation of power and wealth. Silicon Valley, Wall Street and London are examples of financial centers that have a long history of protecting local strategic and personal interests with OPM. Eventually this leads to economic collapse and/or can lead to war, which is directly opposed to beneficial capitalism that encourages diversification, meritocracy, and peace through mutually beneficial trade. To date Wall Street and SV have failed to self-regulate, as have their investors. We may have no choice but to regulate in order to prevent even more severe crises if the current financial consolidation trajectory persists. Financially engineered profitmaking is a completely different task requiring different skills than building durable industries. We need to decentralize back to regional centers with more focus on structural entrepreneurial economics.

  6. Keep politics out of investment, including partisanship & cronyism. That any politician would think they are qualified to understand the complexities involved with investing in technology is frankly a stunning demonstration of hubris. Whether corporate, public, or institutional investor executive, anyone spending most of their time in meetings, raising money, or other activity other than total immersion for decades couldn’t possibly be in a position to appreciate the challenge. Blunt macro instruments such as QE & slinging noodles against the VC wall do great harm to structurally sound economic growth; it just isn’t as visible at the macro level.

  7. Curtail strategic mandates by institutional investors. A form of politics in investment, especially PE/VC mandates, have proven to be among the most toxic brews for the global economy in the past few decades. The needs of a sustainable economy and markets should drive and reward investment, not the internal perceived needs of portfolio management. Often has been the case where a mandate in one arm of institutional investment shared by many others—like subprime mortgage—risks an entire fund, if not entire economy. Take each investment on its individual merit, including best attempt at understanding level of toxicity. Anyone who can’t should not be at decision levels at large funds.

  8. Stop creating monopolies. There is an old saying shared by many seasoned economists and entrepreneurs that states ‘monopolies can only exist with the assistance of government’, whether directly or indirectly. Very well understood is the unhealthy relationship between big government and big business. Attempts to recreate this wheel result in broken economies. Healthy economies require diversification, allowing both failure and success by customer choice rather than government force or corrupted political system.

  9. Do not play God. Power, wealth, and popularity does not necessarily equate to competence. Rather, it almost always leads to hubris, which is of course dangerous. The most effective leaders understand their weaknesses and can identify strengths in others. They do not surround themselves with those who share the same ideology, rather seek out contrarians and devil’s advocates in the decision making process. In economics the evidence is very clear: while unification and central governance on a few issues are necessary, the collective Main Street is far more intelligent and wise than corner offices on Wall St., Sand Hill Road, Capitol buildings, or the Oval Office. We need leaders in those positions who understand their own limitations and that of their roles.

  10. Prevent anarchists while building leaders. One program from the Great Depression that worked well that we still enjoy today was the Civilian Conservation Corp (CCC). Below is a short video on a youth conservation corps program in Idaho that serves as a good example of what could have been done on a much larger scale with stimulus funds, providing much needed life experience for millions of youths rather than wasting most of the money on political favors or fermenting disenfranchisement and anarchists. For heaven’s sake, let’s allow and encourage people to engage in the positive as an alternative to the many negative options that exist in our society today.

Transforming Healthcare With Data Physics


I just completed an in-depth paper on how our work and system can help life science and healthcare companies overcome the great challenges they face, so I wanted to share some thoughts while still fresh. The paper is part of our long-term commitment to healthcare and life sciences, requiring a deep dive over the past several weeks to update myself on the latest research in behavioral psychology, machine learning, deep learning, genetics, chemicals, diagnostics, economics, and particle physics, among others. The review included several hundred papers as well as a few dozen reports.

Kyield Distributed OS - Life Science and Healthcare

The good news is that the science is improving rapidly. An important catalyst to accelerated learning over the past 20 years has been embracing the multi-disciplinary approach, which academia resisted for many years despite the obvious benefits, but is now finally mainstream with positive impact everywhere one looks.

The bad news is that the economics of U.S. healthcare has not noticeably improved. For a considerable portion of the population it has deteriorated. The economic trajectory for the country is frankly grim unless we transform the entire healthcare ecosystem.

A common obstacle to vast improvement in healthcare outcomes that transcends all disciplines with enormous economic consequences is data management and analytics, or perhaps more accurately; the lack thereof. There is no doubt that unified networks must play a lead role in the transformation of healthcare. A few clips from the paper:

“By structural we mean the physics of data, including latency, entropy, compression, and security methodology. The Kyield system is intended to define structural integrity in NNs, continually exploring and working to improve upon state-of-the-art techniques.”

“While significant progress has been made with independent standards towards a more sustainable network economy, functionality varies considerably by technology, industry, and geography, with variety of data types and models remaining among the greatest obstacles to discovery, cost efficiency, performance, security, and personalization.”

Life science and healthcare are particularly impacted by heterogeneous data, which is one reason why networked healthcare is primitive, expensive, slow, and alarmingly prone to error.

“Biodiversity presents a unique challenge for data analytics due to its ambiguity, diversity, and specialized language, which then must be integrated with healthcare and data standards as well as a variety of proprietary vendor technology in database management systems, logistics, networking, productivity, and analytics programs.”

“Due to the complexity across LS and healthcare in data types, standards, scale, and regulatory requirements, a functional unified network OS requires specific combinations of the most advanced technology and methods available.”

Among the most difficult challenges facing management in mature life science companies are cultures that have been substantially insulated from economic reality for decades, only recently feeling the brunt of unsustainable economic modeling throughout the ecosystem, typically in the form of restructures, layoffs, and in some cases closure. This uncertainty particularly impacts individuals who are accustomed to career security and relatively high levels of compensation. I observed this often during a decade of consulting. The pain caused by a dysfunctional economic system is similar to the diseases professionals spend their careers fighting; often unjustly targeting individuals in a seemingly random manner, which of course has consequences.

“Among many changes for knowledge workers associated with the digital revolution and macro economics are less security, more free agency, more frequent job changes, much higher levels of global venture funding, less loyalty to corporate brands and mature industry models, and considerably increased motivation and activism towards personal passionate causes.”

Healthcare is a topic where I have personal passion as it cuts to the core of the most important issues to me, including family, friends, colleagues, and economics, which unfortunately in U.S. healthcare represents a highly self-destructive model. My brother was diagnosed with Lou Gehrig’s disease (amyotrophic lateral sclerosis/ALS) in 1997 not long after his only child was born. I’ll never forget that phone call with him or what he and his family endured over the next three years even though his case was a fine example of dedicated people and community. My father passed a decade later after a brutal battle with type 2 diabetes; we had an old friend pass from MS recently, and multiple cancers as well as epilepsy are ongoing within our small group of family and friends. So it would be foolhardy to deny the personal impact and interest. Healthcare affects us all whether we realize it or not, and increasingly, future generations are paying for the current generation’s unwillingness to achieve a sustainable trajectory. Unacceptable doesn’t quite capture the severity of this systemic failure we all own a part of.

The challenge as I see it is to channel our energy in a positive manner to transform the healthcare system with a laser focus on improved health and economic outcomes. This of course requires a focus on prevention, reduced complexity throughout the ecosystem, accelerated science, much improved technology, and last but not least; rational economic modeling to included increased competition. The latter will obviously require entirely new distribution systems and business models more aligned with current science and economic environment. Any significant progress must include highly evolved legislation reflecting far more empowerment of patients and dramatic improvement in fiscal discipline for the ultimate payer we call America while there is still time to manage the disease. If we continue to treat only the symptoms of healthcare in America it may well destroy the quality of life for the patient, if indeed the patient as we know it survives at all. This essentially represents my diagnosis.

A few of the 80 references I cited in the paper linked below are good sources to learn more:

Beyond borders: unlocking value. Biotechnology Industry Report 2014, EY
http://www.ey.com/GL/en/Industries/Life-Sciences/EY-beyond-borders-unlocking-value

Dixon-Fyle, S., Ghandi, S., Pellathy, T., Spatharou, A., Changing patient behavior: the new frontier in healthcare value (2012). Health International, McKinsey & Company.
http://healthcare.mckinsey.com/sites/default/files/791750_Changing_Patient_Behavior_the_Next_Frontier_in_Healthcare_Value.pdf

Thessen A., Cui H., Mozzherin D. Applications of Natural Language Processing in Biodiversity Science Adv Bioinformatics.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3364545/

Top 10 Clinical Trial Failures of 2013. Genetic Engineering & Biotechnology News.
http://www.genengnews.com/insight-and-intelligence/top-10-clinical-trial-failures-of-2013/77900029/

Begley, C.G., Ellis, L.M. (2012) Drug development: raise standards for preclinical cancer research. Nature 483 http://www.nature.com/nature/journal/v483/n7391/pdf/483531a.pdf

Cambria, E., and White, B. Jumping NLP curves: A review of natural language processing research. IEEE Computational Intelligence Magazine, 9:1–28, 2014.
http://www.krchowdhary.com/ai/lects/nlp-research-com-intlg-ieee.pdf

Montgomery, M. Diabetes and the American Healthcare System. Kyield, Published online May 2010
http://www.kyield.com/images/Kyield_Diabetes_Use_Case_Scenario.pdf

All quotes above are mine from Kyield’s paper of 8-15-2014:

Unified Network Operating System
With Adaptive Data Management Tailored to Each Entity
Biotech, Pharmaceuticals, Healthcare, and Life Sciences

Complex Dynamics at the Confluence of Human and Artificial Intelligence


(This article was featured at Wired)

Fear of AI vs. the Ethic and Art of Creative Destruction

While it may be an interesting question whether the seasons are changing in artificial intelligence (AI), or to what extent the entertainment industry is herding pop culture, it may not have much to do with future reality. Given recent attention AI has received and the unique potential for misunderstanding, I thought a brief story from the trenches in the Land of Enchantment might shed some light.

The topic of AI recently came up at Santa Fe Institute (SFI) during a seminar by Hamid Benbrahim surrounding research in financial markets. Several senior scientists chimed in during Hamid’s talk representing computer science (CS), physics (2), neuroscience, biology, and philosophy, as well as several practioners with relevant experience. SFI is celebrating its 30th anniversary this year as a pioneer in complexity research where these very types of topics are explored, attracting leading thinkers worldwide.

Following the talk I continued to discuss financial reforms and technology with Daniel C. Dennett, who is an external professor at SFI. While known as an author and philosopher, Professor Dennett is also Co-Director of the Center for Cognitive Studies at Tufts University with extensive published works in CS and AI. Professor Dennett shared a personal case that provides historical and perhaps futuristic context involving a well-known computer scientist at a leading lab during the commercialization era of the World Wide Web. The scientist was apparently concerned with the potential negative impact on authors given the exponentially increasing mass of content, and I suspect also feared the network effect in certain types of consumer services that quickly result in winner-takes-all dominance.

Professor Dennett apparently attempted to reassure his colleague by pointing out that his concerns, while understandable, were likely unjustified for the mid-term as humans have a consistent history of adapting to technological change, as well as adapting technology to fill needs. In this case, Dennett envisioned the rise of specialty services that would find, filter, and presumably broker in some fashion the needs of reader and author. Traditional publishing may change even more radically than we’ve since observed, but services would rise, people and models would adapt.

One reason complexity attracts leading thinkers in science and business is the potential benefit across all areas of life and economy. The patterns and methods discovered in one field are increasingly applied to others in no small part due to collaboration, data sharing, and analytics. David Wolpert for example stated his reasoning for joining SFI part-time from LANL was a desire to work on more than one discipline simultaneously. Many others have reported similarly both for the potential impact from sharing knowledge between disciplines and the inherent challenge. I can certainly relate from my own work in applied complex adaptive systems, which at times seems as if God or Nature were teasing the ego of human intellect. Working with highly complex systems tends to be a humbling experience.

That is not to say, however, that humans are primitive or without power to alter our destiny. Our species did not come to dominate Earth due to ignorance or lack of skills, for better or worse. We are blessed with the ability to intentionally craft tools and systems not just for attention-getting nefariousness, but solving problems, and yes being compensated for doing so. Achieving improvement increasingly requires designs that reduce the undesirable impacts of complexity, which tend to accumulate as increased risk, cost, and difficulty.

Few informed observers claim that technological change is pain-free as disruptions and displacements occur, organizations do fail, and individuals do lose jobs, particularly in cultures that resist macro change rather than proactively adapt to changing conditions. That is after all the nature of creative destruction. Physics, regulations, and markets may allow us to control some aspects of technology, manage processes in others, and hopefully introduce simplicity, ease of use, and efficiency, but there is no escaping the tyranny of complexity, for even if society attempted to ban complexity, nature would not comply, nor would humans if history is any guide. The risk of catastrophic events from biological and human engineered threats would remain regardless. The challenge is to optimize the messy process to the best of our ability with elegant and effective solutions while preventing extreme volatility, catastrophic events, and as some of us intend—lead to a more sustainable, healthy planet.

2012 Kyield Enterprise UML Diagram - Human Skull

The dynamics involved with tech-led disruption are well understood to be generally beneficial to greater society, macroeconomics, and employment. Continual improvements with small disruptions are much less destructive and more beneficial than violent events that have occurred throughout history in reaction to extreme chronic imbalances. Diversification, competition, and churn are not only healthy, but essential to progress and ultimately survival. However, the messy task is made far more costly and painful than necessary, including to those most impacted, as entrenched cultures resist that which they should be embracing. Over time all manner of protectionist methods are employed to defend against change, essential disruption, or power erosion, eventually to include manipulation of the political process, which often has toxic and corrosive impacts. As I am writing this a description following a headline in The Wall Street Journal reads as follows:

 “Initiatives intended to help restrain soaring college costs are facing resistance from schools and from a bipartisan bloc of lawmakers looking to protect institutions in their districts.”

Reading this article reminded me of an interview with Ángel Cabrera, who I had the pleasure of getting to know when he was President of Thunderbird University, now in the same role at George Mason University. His view as I recall was that the reforms necessary in education were unlikely to come from within, and would require external disruptive competition. Regardless of role at the time, my experience has been similar. A majority of cultures fiercely resist change, typically agreeing only to reforms that benefit the interests of narrow groups with little concern for collective impact or macro needs. Yet society often looks to entrenched institutions for expertise, leadership, and decision power, despite obvious conflicts of interest, thus creating quite a dilemma for serious thinkers and doers. As structural barriers grow over time it becomes almost impossible to introduce new technology and systems regardless of need or merit. Any such scenario is directly opposed to proper governance policy, or what is understood to result in positive outcomes.

Consider then recent research demonstrating that resistance to change and patterns of human habit are caused in part by chemicals in the brain, and so we are left with an uncomfortable awareness that some cultures are almost certainly and increasingly knowingly exploiting fear and addiction to protect personal power and financial benefits that are often unsustainable, and eventually more harmful than tech-enabled adaptation to the very special interests they are charged with serving, not to mention the rest of society who would clearly benefit. This would seem to cross the line of motivation for change to civic duty to support those who appear to be offering the best emerging solutions to our greatest problems.

This situation of entrenched interests conflicting with the greater good provides the motivation for many involved with both basic and applied R&D, innovation, and business building. Most commonly associated with the culture of Silicon Valley, in fact the force for rational reforms and innovation has become quite global in recent years, although resistance to even the most obvious essential changes are still at times shockingly stubborn and effective.

Given these observations combined with awareness that survival of any organization or species requires adaptation to constantly changing conditions, one can perhaps see why I asked the following questions during various phases of our R&D:

Why not intentionally embrace continuous improvement and adaptation?

Why not tailor data consumption and analytics to the specific needs of each entity?

Why not prevent readily preventable crises?

Why not accelerate discoveries and attribute human capital more accurately and justly?

Why not rate, incentivize, and monetize mission-oriented knowledge?

The story I shared in conversation with Dan Dennett at SFI was timely and appropriate to this topic as philosophy not only deserves a seat at the table with AI, but also has contributed to many of the building blocks that make the technology possible, such as mathematics and data structures, among others.

The primary message I want to convey is that we all have a choice and responsibility as agents for positive change, and our actions impact the future, especially with AI systems. For example, given that AI has the capacity to significantly accelerate scientific discovery, improve health outcomes, and reduce crises, I have long believed ethics requires that we deploy the technology. However, given that we are also well aware that high unemployment levels are inhumane, contain considerable moral hazard, and risk for civil unrest, AI should be deployed surgically and with great care. I do not support wide deployment of AI for the primary purpose of replacing human workers. Rather, I have focused my R&D efforts on optimizing human capital and learning in the near-term. To the best of my awareness this is not only the most ethical path forward for AI systems, but is also good business strategy as I think the majority of decision makers in organizations are of similar mind on the issue.

In closing, from the perspective of an early advisor to very successful tech companies rather than inventor and founder of an AI system, I’d like to support the concerns of others. While we need to be cautious with spreading undue fear, it has become clear to me that some of the more informed warnings are not unjustified. Some highly competitive cultures particularly in IT engineering have demonstrated strong anti-human behavior, including companies I am close to who would I think quite probably not self-restrain actions based on ethics or macro social needs, regardless of evidence presented to them. In this regard they are no different than the protectionist cultures they would replace, and at least as dangerous. I strongly disagree with such extreme philosophies. I believe technology should be tapped to serve humans and other species, with exceptions reserved for contained areas such as defense and space research where humans are at risk, or in areas such as surgery where machine precision in some cases are superior to humans and therefore of service.

Many AI applications and systems are now sufficiently mature for adoption, the potential value and functionality are clearly unprecedented, and competitive pressures are such in most sectors that to not engage in emerging AI could well determine organizational fate in the not-too-distant future. The question then is not whether to deploy AI, or increasingly even when, but rather how, which, and with whom. About fifteen years ago during an intense learning curve I published a note in our network for global thought leaders that the philosophy of the architect is embedded in the code—it just often requires a qualified eye to see it. This is where problems in adoption of emerging technology often arise as those few who are qualified include a fair percentage of biased and conflicted individuals who don’t necessarily share a high priority for the best interest of the customer.

My advice to decision makers and chief influencers is to engage in AI, but choose your consultants, vendors, and partners very carefully.

Transparency in IT: Why we published the Kyield Enterprise investment guide and price list.


Image

After considerable thought and discussion, we decided to publish an investment guide (pictured above) for Kyield Enterprise that includes product descriptions, a price list, and a table of benefits. This was not a decision that was as easy as it may appear, so I wanted to share some thoughts on the macro challenges of price transparency and interoperability relative to the decision making process. While we’ve been debating this for some time, more experience with our still new system has helped refine our internal process, which influenced timing. Boris Evelson at Forrester Research also deserves credit for consistently bringing this issue out in the open (see my comments), as have other industry analysts. 

The challenge for customers in enterprise software and IT is establishing an accurate estimate of the total cost of ownership (TCO), which is necessary to forecast the overall return on investment (ROI); not a trivial task, requiring as much accurate information as possible. We assist by working collaboratively with customer teams to develop a deeply tailored scenario, which represents a considerable commitment and time investment.

Everyone involved with enterprise systems and networks must deal with a complex cauldron of components that are different in each organization, often including a mix of custom code, legacy software, unsupported open source software (OSS), outdated proprietary software, poorly structured data for current needs, BYOD, and of course massive amounts of unstructured data, among other issues, such as whether appropriate hardware and supported software need to be expanded for a system install. Some have reasonably argued that estimating TCO can best be achieved by privately quoted projects on a case by case basis only after an assessment of the enterprise mix, which of course should be done, but that doesn’t prevent transparency, the lack of which invites abuses across the industry.

Many companies and organizations have cited lack of functional IT systems and interoperability for bankruptcy, while others have won large law suits for being misled by consultants and vendors (usually settled subject to a gag order–not much transparency in those cases). In recent years we’ve observed multi-billion USD projects cancelled due to cost overruns that never resulted in a functional unified system, so entire massive projects were abandoned prior to delivering the first penny towards an ROI (DoD & state healthcare sites among others). While it is true that customer organizations are sometimes their worst enemies in decision making and procurement, it’s also true that the industry has had a very serious problem that hasn’t been resolved due to conflicting interests, sales quotas, growth mandates, and pressure from investors in both public and private equity.

While the lack of interoperability and related complexity have caused strong demand for IT staff, system integrators, consultants, agile developers, and data scientists, resulting in extremely large well-compensated ecosystems, the situation has also corrupted relationships and models. The result is a toxic stew that has contributed to many of the largest problems facing society and the global economy, such as poor outcomes in R&D, stagnant productivity, and failure to prevent systemic crises. This is why some of us have worked towards interoperable standards and systems since the commercialization of the Internet and Web.

In order for any interconnected system to function properly—and achieve sustainable economics, it’s critically important to have a threaded plug and play architecture. I’ve long argued that to meet the enormous current and future needs of our planet, the information revolution must adopt independent standards similar to plumbing, electricity, and transportation during the industrial revolution. This is finally occurring now, led by regulated industries, but lobbyists, entrenched incumbents, and many other conflicted parties are fully engaged at every step of the process. While the impact any single company can have on such a large systemic challenge may be minor in the near-term, unless having dominant market share of course, we can have a big impact in crafting better system design and working collectively with others to improve upon the macro situation, which is what we’ve attempted to achieve with Kyield all along.

Now I’d like to drill down a bit into some of the specific challenges in pricing from the board governance perspective in large organizations, which is our core customer. As the service and integration sector has grown along with open source, the actual cost of software licenses, subscriptions, or IP has become less of the overall problem, especially given increased support for data standards and wide deployment of APIs. It isn’t clear to me that this is sufficiently understood by many boards.

For example, while open source (OSS) and commoditization has had a very positive impact in driving down consumer prices, enterprise costs have increased dramatically overall, in part due to market power of incumbents and lock-in, but also due to the unhealthy relationship in services, which range between 1x to 10x the cost of the software alone. So while the cost of software licensing is certainly important, many are not focused on the most important issue—impact of system design on TCO, and most importantly—what ROI can be reasonably expected?

CEOs, boards, CIOs, and CFOs need to be acutely aware that OSS and low cost computing only truly becomes a powerful driver of ROI for organizations with the ability to differentiate and create a sustainable competitive advantage, which is precisely what we’ve pursued throughout the Kyield voyage. In order to achieve the best of both worlds—low cost commoditization and sustainable advantage—and realize the potential of the technology investment, it frankly requires the brains of the system running on top of the tech stack to be designed in a very specific manner, with interoperability essential, and functionality determining ROI. It’s probably not surprising that I think the optimal system looks a lot like Kyield Enterprise, which was driven by evidenced-based R&D. Kyield Enterprise can in some scenarios make the difference between success and failure. It’s possible in some sectors to provide a positive ROI for the entire IT budget for a century, upon preventing just one major crisis, accelerating the discovery of a single blockbuster drug, expediting innovation, or assisting in an important invention.

In conclusion, while I’m pleased to contribute to industry price transparency, and believe it’s probably good for our business to do so—despite the risks, I also plead with thought leaders, journalists, analysts, CIOs, and boards to keep one eye on the component details and the other eye on the broader impact of IT architecture on the needs of each entity in customer organizations relative to the global economy.

Mark Montgomery

Kyield Enterprise Description Converted to StratML


I just wanted to point to a nice conversion of our Kyield Enterprise description to Strategy Markup Language (StratML); an XML vocabulary and schema for strategic plans. The work was performed without solicitation over the weekend by Owen Ambur, Chair AIIM StratML & Co-Chair Emeritus xml.gov.

The human readable version (styled) of Kyield Enterprise in StratML can be viewed in browsers on Web here:

http://xml.fido.gov/stratml/carmel/KEwStyle.xml

New Kyield Brochure


Although Kyield represents nearly two decades of R&D followed by two years in pilot phase, dozens of papers, videos and articles, we’ve never published a brochure–until now. Actually more like a combination of a brochure, report, and mini e-book, complete with photos from our own collection to match the nature theme.

Kyield Brochure Cover 2-2014

Kyield brochure layout

The brochure is authentic — my own work, and brief at 10 pages including front and back cover.  Primarily intended for direct mail with letters from me to senior executives in well-matched companies, it’s also downloadable on our web site here:  http://www.kyield.com/brochure.html

Hope the brochure is helpful to prospective customers, broader market, and Kyield!

Book Review: “Artificial Cognitive Architectures”


“Artificial Cognitive Architectures”

James A. Crowder, John N. Carbone, Shelli A. Friess

Aficionados of artificial intelligence often fantasize, speculate, and debate the holy grail that is a fully autonomous artificial life form, yet rarely do we find a proposed architecture approaching a credible probability of success.  With “Artificial Cognitive Architectures”, Drs Crowder, Carbone and Friess have painstakingly pulled together many disparate pieces of the robot puzzle in sufficient form to convince this skeptic that a human-like robot is finally within the realm of achievement, even if still at the extreme outer bounds of applied systems.

The authors propose an architecture for a Synthetic system, which is an Evolving, Life Form (SELF):

A prerequisite for a SELF consciousness includes methodologies for perceiving its environment, take in available information, make sense out of it, filter it, add to internal consciousness, learn from it, and then act on it.

SELF mimics the human central nervous system through a highly specific set of integrated components within the proposed Artificial Cognitive Neural Framework (ACNF), which includes an Artificial Prefrontal Cortex (APC) that serves as the ‘mediator’. SELF achieves its intelligence through the use of Cognitrons, which are software programs that serve in this capacity as ‘subject matter experts’.  An artificial Occam abduction process is then tapped to help manage the ‘overall cognitive framework’ called ISAAC (Intelligent information Software Agents to facilitate Artificial Consciousness).

The system employs much of the spectrum across advanced computer science and engineering to achieve the desired results for SELF, reflecting extensive experience. Dr. Jim Crowder is Chief Engineer, Advanced Programs at Raytheon Intelligence and Information Systems. He was formerly Chief Ontologist at Raytheon which is where I first came across his work. Dr. John Carbone is also at Raytheon; a quick search will reveal many of his articles and patents in related areas. Dr. Shelli Friess is a cognitive psychologist; a discipline that until recently was rarely found associated with advanced computing architecture, even though mimicry of the human nervous system clearly calls for a deep transdisciplinary approach. For example, “Artificial Cognitive Architectures“ introduces  ‘acupressure’, ‘deep breathing’, ‘positive psychology’ and other techniques to SELF as proposed to become ‘a real-time, fully functioning, autonomous, self-actuating, self-analyzing, self-healing, fully reasoning and adapting system.’

While even the impassioned AI post-doc may experience acronym fatigue while consuming “Artificial Cognitive Architectures”, the 18 years of research behind the book with careful attention to descriptive terminology helps to minimize the confusion surrounding a topic that by necessity begins to take on the complexity of our species.

Serious students and practitioners of AI will find “Artificial Cognitive Architectures” particularly interesting for the broad systems approach, while most others with curiosity surrounding this topic will find the book technical but fascinating. Those searching for HAL 9000 will be delighted to see similar reasoning and emotions on display, while simultaneously disappointed to discover designed-in governance and security features that will hopefully prevent such Hollywood scenarios from occurring. The security design was apparently influenced by an actual entertaining case when an earlier version of intelligent agent developed for the U.S. government was inadvertently left plugged in by Dr. Crowder, resulting in a late night Instant Messaging exchange between a human colleague and a Cognitron slumber party of sorts.

Readers will find a more mature posture regarding policy and security than commonly found in popular AI culture, apparently reflecting the serious work of applying AI to missile and other systems at Raytheon.

I personally found the book refreshing as it overlaps much of my own work at the confluence of human-driven AI systems. I also share a concern for internal security as it appears inevitable that machines with even the most basic cognitive ability will immediately observe how irresponsible their organic brethren have conducted themselves as stewards of earth’s resources.

J.A. Crowder et al., Artificial Cognition Architectures
DOI 10.1007/978-1-4614-8072-3_5, © Springer Science+Business Media New York 2014

http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-1-4614-8071-6

Why It Has Always Been, and Will Always Be — The Network of Entities


Physics won this debate before anyone had a vision that a computer network might someday exist, but biology played an essential role on the team.

The reason of course is that all living things, including humans and our organizations, are unique in the universe—for our purposes anyway—until that identical parallel universe is discovered. Even perfectly cloned robots cannot occupy the same time and place, so while quite similar a machine working directly adjacent to an otherwise identical clone may be electrocuted or run over by a forklift, and will then have much different needs.

More importantly to organic creatures like myself, our DNA while similar to others is not only unique, but our health and well being are influenced by a myriad of other factors as well, including nutrition, behavior, environment, and socioeconomics among others, the totality interaction of which we only partially understand. We do know, however, that our universe, our bodies and our brains are constantly changing with a set of factors at any one time that strongly favor an adaptive response—or in many cases proactive, certainly to include managing data and information.

While networks of things and of people certainly exist, it always has been and forever will be the Internet of entities, the individual make-up of which at any moment in time, including dynamic relationships, require humans and human organizations to manage the best we are able with the most accurate information available, increasingly for the foreseeable future by this human entity to include managing organizational entities, machine entities, and yes even sensory entities. This is why I created Kyield and designed the system that powers it in precisely the manner offered.

New Report: Adaptive Unification for Life Science Ecosystems


First, I want to apologize for not being able to keep up with my blog as much as I would like, or to share as much in public as I would prefer. The reasons are twofold. We’ve been very busy at Kyield, and testing has increasingly confirmed that while competitors in our industry invest heavily in web information (CI), most customers do not; at least for enterprise-wide systems like Kyield.  So I have regrettably pulled back on detailed public writing, or rather– have replaced with more formal papers and presentations with customers.

A good example of our efforts is the new report below, which is a hybrid of an academic paper with citations supporting our claims and a detailed brochure for senior managers in pharmaceuticals, biotech, and healthcare–particularly those pursuing personalized medicine and significant improvement in operational efficiency:

Adaptive Unification  for  Life Science  Ecosystems 

Kyield report: Adaptive Unification for Life Science Ecosystems

The paper highlights the challenges facing the industry with considerable detail on how Kyield is unique in the world with respect to ability to overcome these challenges. Essentially, in order to overcome systemic challenges it requires a systemic solution, and in terms of distributed organizations it requires a very particular type of systemic solution that can address each of the challenges. Due to the high values involved, the result is that Kyield may well be the best investment option in the world today for life science executives.

For those who would prefer more frequent updates, the best methods to track either Kyield or my activity are as follows:

Connect with me on LinkedIn:      http://www.linkedin.com/in/markamontgomery/

Follow Kyield on LinkedIn:              

Follow @kyield on Twitter:             https://twitter.com/kyield

And of course visit our web site regularly at www.kyield.com

Kind regards,

Mark Montgomery

Workplace analytics paper + our new PSN


I wanted to share a couple of quick items. One is an article on workplace analytics I just completed that may be of interest (PDF). While it deals with some of the most complex technical issues, the format is a short non-technical paper intended for senior business managers and boards, most of whom do not have a technical background yet must deal with organizational issues that are increasingly driven by technology.

The second item is that we’ve launched a global professional services network (PSN) surrounding Kyield technology. We currently have a recruitment running on LinkedIn for managing partners.  The PSN is progressing very well, keeping me very busy in discussions with highly qualified consultants worldwide. Our first group of countries have now moved through the initial stage and are engaging with client organizations. -MM

The ‘Sweet Spot of Big Data’ May Contain a Sour Surprise for Some


I’ve been observing a rather distasteful trend in big data for the enterprise market over the past 18 months that has reached the point of wanting to share some thoughts despite a growing mountain of other priorities.

As the big data hype grew over the past few years, much of which was enabled by Hadoop and other FOSS stacks, internal and external teams serving large companies have perfected a (sweet spot) model that is tailored to the environment and tech stack. Many vendors have also tailored their offerings for the model backed up with arguably too much funding by VCs, dozens too many analyst reports, and a half-dozen too many CIO publications attempting to extend reach and increase the ad spend.

The ‘sweet spot’ goes something like this:

  • Small teams consisting of data scientists and business analysts.
  • Employing exclusively low cost IT commodities and free and open source software (FOSS).
  • Targeting $1 to $5 million projects within units of mid to large sized enterprises.
  • Expensed in current budget cycle (opex), with low risk and high probability of quick, demonstratable ROI.

So what could possibility be wrong with this dessert—looks perfect, right? Well, not necessarily—at least for those of us who have viewed a similar movie many times previously, with a similar foreshadowing, plot, cast of characters, and story line.

While this service model and related technology has been a good thing generally, resulting in new efficiency, improved manufacturing processes, reduced inventories, and perhaps even saved a few lives, not to mention generated a lot of demand for data centers, cloud service providers and consultants, we need to look at the bigger picture in the context of historical trends in tech adoption and how such trends evolve to see where this trail will lead. Highly paid data scientists, for example, may then find that they have been frantically jumping from one project to the next inside a large bubble with a thin lining, rising high over an ecosystem with no safety net, and then suddenly find themselves a target of flying arrows from the very CFO who has been their client, and for good fundamental reasons.

As we’ve seen many times before at the confluence of technology and services, the beginning of an over-hyped trend creates demand for high-end talent that is unsustainable even often in the mid-term. Everyone from the largest vendors to emerging companies like Kyield to leading consulting firms and many independents alike are in general agreement that while service talent in big data analytics (and closely related) are capturing up to 90% of the budget in this ‘sweet spot’ model today, the trend is expected to reverse quickly as automated systems and tools mature. The reaction to such trends is often an attempt to create silos of various sorts, but even for those in global incumbents or models protected by unions and laws like K-12 in the U.S., it’s probably wise to seek a more sustainable model and ecosystem tailored for the future. Otherwise, I fear a great many talented people working with data will find in hindsight that they have been exploited for very short-term gain in a model that no longer has demand and may well find themselves competing with a global flood of bubble chasers willing to work cheaper than is even possible given the cost of living in their location.

What everyone should realize about the big data trend

While there will likely be strong demand for the very best mathematicians, data modelers, and statisticians far beyond the horizon, the super majority of organizations today are at some point in the journey of developing mid to long-term strategic plans for optimizing advanced analytics, including investments not just for small projects, but the entire organization. This is not occurring in a vacuum, but rather in conjunction with consultants, vendors, labs and emerging companies like ours that intentionally provide a platform that automates many of the redundant processes, enable plug and play, and make advanced analytics available to the workforce in a simple to use, substantially automated manner. While it took many years of R&D for all of the pieces to come together, the day has come when physics allows such systems to be deployed and so this trend is inevitable and indeed underway.

The current and future environment is not like the past when achieving a PhD in one decade will necessarily provide job demand in the next, unless like everyone else in society one can continue to grow, evolve and find ways to add value in a hyper competitive world. The challenges we face (collectively) in the future are great and so we cannot afford apathy or wide-spread cultures that are protecting the (unsustainable) past, but rather only those attempting to optimize the future.

In our system design, we embrace the independent app, data scientist, and algorithm, and recommend to customers that they do so as well—there is no substitute for individual creativity—and we simply must have systems that reflect this reality, but it needs to occur in a rationally planned manner that attacks the biggest problems facing organizations, and more broadly across society and the global economy.

The majority seem frankly misguided on the direction we are headed: the combination of data physics, hardware, organizational dynamics and economics requires us to automate much of this process in order to prevent the most dangerous systemic crises and to optimize discovery. It’s the right thing to do. I highly recommend to everyone in related fields to plan accordingly as these types of changes are occurring in half the time as a generation ago and the pace of change is still accelerating. At the end of the day, the job of analytics is to unleash the potential of customers and clients so that they can then create a sustainable economy and ecology. 

On role and title of Chief Data Officer



I left an extensive comment on a discussion surrounding the role and title of Chief Data Officer (CDO) over at Forrester Blogs by Gene Leganza, so thought I would share it here on our own blog (below).

~~~~


Gene


CDO reminds me of CKO more than CIO — and also suffers some of the same challenges as head of BI in the blog by Boris in the job description. Most of the arguments are valid until we take the entire organization into view and that’s where I see problems.


Anytime this discussion on a new officer comes up it tends to rise from the desires, need to have more influence in the org, and aspirations of the specialist (and their ecosystem) rather than the need of the organization. Similar to a strong EA for example, what typically matters is whether the CEO (and board) is competent or not, paying attention to how the organization functions or not, and whether the culture and relationships are collaborative, combative, or even apathetic.

Unfortunately, one impact we have observed with the CIO and a few CKOs was confusion over the title officer by the entire organization, including those holding the title, when they suddenly became obsessed with their own power rather than service to others. Whether BI, EA, or CKO, in some cases we observed quite strong individuals who were driving critical value to the organization, but reporting to an infrastructure CIO who didn’t understand much at all about business or organizations, or worse in a few cases simply concerned with protecting their own turf rather than the mission of the organization and customers.

Generally speaking I think it’s wise to allow the brand of the individual rise up in the organization based on functionality, knowledge, and contributions to the organization–rather than yet another title ending with officer. Indeed, often has been the case when a person with a more humble title has had more impact, even in aggressive and highly competitive cultures, particularly when they are wicked smart and wise.

One problem rarely discussed is that corporate officer in many companies has real meaning in terms of authority, responsibility and legal accountability whereas in most cases the job description title of officer does not, creating confusion internally and externally (I am thinking now of one giant tech company in particular where titles have been a disaster to everyone but the CEO who hands them out).

I personally prefer scientist over officer and I’m not terribly fond of scientist (except when used properly to describe a true scientist) due to the disconnect in meaning and culture between science and business that is too often manifest in organizational dysfunction. I see functional roles more of a master craft person who may lead a small team, but is more interested in the value of their work than career aspirations to one day become a CEO, or even to lead large numbers of people where internal and external politics tend to rule. In fact it’s been my experience that the strongest functional people do not have any desire to hold the title of officer.

So my fear based on previous experience and observations is that in the rare highly functional organization the role and title will also function well–regardless of what we call it, but in the norm it may do more harm than good, in which case the stronger professional will likely either avoid the organization to begin with or move on at the earliest opportunity. .02- MM

New Year Review 2013: The Importance of Triple Win Ecosystems


Kyield R&D Journey- 2012

Looking Back on 2012

Among the positive trends we observed in 2012 include relatively strong continued adoption of richly structured data across all major industry clusters. A significant portion of senior managers have just recently engaged in an attempt to seriously understand how best to optimize structured data for their organizations and partners, with an exceptional minority now experiencing big aha moments. Until recently semantics was limited primarily to R&D, and analytics was restricted to a very few people in the organization with a fairly limited scope. A growing minority are finally connecting the dots and incorporating semantics into their ‘big data’ analytics strategy.

We changed a few global strategic plans with our Kyield pilot presentations in the past year as organizations began to realize that what seemed futuristic a few years ago is now executable in near real-time. However, what is still missing is a competitive ecosystem that could be called upon to serve the specific needs of customers in a triple win manner.  As is often the case with emerging technologies– individuals, small teams and companies engage due to a combination of motivating factors that includes independence, compensation, and to change the world for the better, but in order to achieve much in the enterprise market we need fully functional ecosystems.

A combination of assets must be offered in a highly efficient and credible manner, including very experienced management, superior technology, deep technical talent, appropriate financial structure and professional services, which is usually far more than even the largest companies can provide on their own. So job one for the emerging semantic enterprise community is to learn how to work together towards building a functional ecosystem, which means creating and offering mutual value while serving customer needs in win/win/win scenarios.

We held discussions with a few companies interested in partnering who underestimate the risk they face and overestimate their power, some of whom apparently don’t understand how to form mutually beneficial partnerships. In Kyield’s partner program we will only consider triple wins. And BTW, don’t expect anything but obstacles thrown in the way from the trillion dollar global integration machine, which is a mature, highly sophisticated ecosystem with unlimited funds that is threatened by independent standards and lower TCO. Customers have a special responsibility to assist the emerging semantic ecosystem as they are the primary beneficiaries of the technology and have a very important strategic interest in helping to ensure that the semantic ecosystem becomes more viable and sustainable.

Expectations for 2013

An interesting event recently occurred at a leading bank that could be telling for the near future with respect to semantics and data standards in 2013 and beyond. The bank recently announced large layoffs that included 25% within IT. The bank previously invested heavily in internal proprietary systems and are now moving towards standards where they expect to see a significant ROI with speculation that other leading banks will follow. Banks were late to semantics and obviously some proved that their proprietary risk management and governance systems were systemically dangerous, but we’re seeing a positive trend now. These layoffs may sound like bad news, but we should remember that the primary role of leading banks is to lend modestly leveraged capital to others, which creates far more jobs in a more diverse manner than when employed internally at a bank for proprietary systems and integration work. This is an important trend toward higher efficiency in a more economically sustainable manner thanks largely to adoption of independent standards. When combined with proper governance and advanced analytics throughout the financial system, this trend can become powerful indeed.

The big question in 2013 more broadly is to what degree the EU and U.S. can get their long-term fiscal house in order. The macro economic environment can easily dominate technology adoption and business creation. There is a direct relationship between balanced federal budgets, job creation, and sustainable economic progress. Clearly the U.S. culture is in a deep state of denial relative to sustainable economics reflected in a severely dysfunctional political system, and it’s having a strong negative impact even for those who offer an exceptional ROI.  In the case of Kyield, for example, the macro environment has resulted in some customer prospects in otherwise strong organizations freezing new projects until political and fiscal uncertainty is resolved, which in turn of course deters any prudent entrepreneur, investor or other decision maker from taking risk that may have seemed rational in the past in a much different macro economic environment. Since those in the health management business of elephants don’t have the luxury of being trampled more than once, Kyield plans to continue with our lean organic hybrid approach in partnership with customers and partners and leave speculative build outs to those who enjoy rolling the dice. 

I am confident that in 2013 we’ll see the competitive gap continue to widen between those who adopt more advanced, efficient, intelligent systems, and those who don’t, especially new systems that reduce lock-in and improve interoperability resulting in a sharply lower TCO. There is a strong compounding effect that occurs with adoption of rich data standards containing more integrity with advanced knowledge systems and real-time analytics, and it’s becoming increasingly more difficult to deny as organizations that master this technology pull ahead of competitors. Smart adaptive people working with smart adaptive computing is a powerful combination not to be denied.

To good health in 2013 for you, family and organization. – MM

Yield Management of Knowledge for Industry + FAQs


Industrial Yield Management of Knowledge from www.kyield.com

I decided to share this slightly edited version of a diagram that was part of a presentation we recently completed for an industry leading organization. Based on feedback this may be the most easily understandable graphic we’ve produced to date in communicating the Kyield enterprise system. As part of the same project we published a new FAQs page on our web site that may be of interest.  Most of my writing over the past several months has been in private tailored papers and presentations related to our pilot and partner programs.

I may include a version of this diagram in a public white paper soon if I can carve out some writing time. If you don’t hear from me before then I wish you and your family a happy holiday season.

Kind regards, MM

Kyield Partner Program: An Ecosystem for the Present Generation


We’ve been in various discussions for the past couple of years with potential partners, finding many interests in the industry to be in direct conflict with the mission of the customer organizations. Most of our discussions reflect a generational change in technology underway that is being met with sharp internal divisions at incumbent market leaders that result in attempting to protect the past from the present and future. The situation is not new– it is very difficult for incumbent market leaders to voluntarily cannibalize highly profitable business models, particularly when doing so would threaten jobs, so historically disruptive technology has required new ecosystems (MS and Intel in the early 1980s, Google in the late 1990s, RIM, Apple app stores in the 2000s, etc.).

So due to the platform approach to Kyield and the disruptive nature of our technology to incumbent business models, and resistance to change in industry leaders–despite pressure from even their largest customers, we determined quite some time ago that it may require building a new ecosystem based on the Kyield platform, data standards and interoperability. The driving need is not just about the enormous sum of money being charged for unproductive functionality like lock-in, maintenance fees, and unnecessary software integration–although this is an ever-increasing problem for customers, or even commoditization and lack of competitive advantage–also a very serious problem, rather as is often the case it comes down to a combination of complexity, math and physics.

Not only is it not economically viable to optimize network computing in the neural network economy based on legacy business models, but we cannot physically prevent systemic crises, dramatically improve productivity, and/or expedite discovery in a manner that doesn’t bankrupt a good portion of the economy without data standards and seamless interoperability. In addition, we do need deep intelligence on each entity as envisioned in the semantic web in order to overcome many of our greatest challenges, to execute advanced analytics, and to manage ‘big data’ in a rational manner, but we also need to protect privacy, data assets, knowledge capital and property rights while improving security. Standards may be voluntary, but overcoming these challenges isn’t.

So we’ve been working on a new partner program for Kyield in conjunction with our pilot phase in attempt to reach out to prospective partners who may not be on our radar that would make great partners and work with us to build a new ecosystem based not on protecting the past or current management at incumbent firms, but rather the future by optimizing the present capabilities and opportunities surrounding our system.  We hope to collectively create a great many more new jobs than we could possibly do on our own in the process–not just in our ecosystem, but importantly for customer ecosystems.

We’ve decided for now on five different types of partner relationships that are intended to best meet the needs of customers, partners, and Kyield:

  • Consulting
  • Technology
  • Platform
  • Strategic
  • Master

For more information on our partner program, please visit:

http://www.kyield.com/partners.html

Thank you,

Mark Montgomery
Founder, Kyield

Converting the Enterprise to an Adaptive Neural Network


Those tracking business and financial news may have observed that a little bit of knowledge in the corner office about enterprise architecture, software, and data can cause great harm, including for the occupant, often resulting in a moving van parked under the corner suite of corporate headquarters shortly after headlines on their latest preventable crisis. Exploitation of ignorance in the board room surrounding enterprise computing has become mastered by some, and is therefore among the greatest of many challenges for emerging technology that has the capacity for significant improvement.

The issues surrounding neural networks requires total immersion for extended duration. Since many organizations lack the luxury of time, let’s get to it.

Beware the Foreshadow of the Black Swan

A recent article by Reuters confirms what is perhaps the worst kept secret in the post printing press era: Many Wall Street executives say wrongdoing is necessary: survey. A whopping 25% of those surveyed believe that in order to be personally successful, they must conduct themselves in an unethical manner to include breaking important laws, some of which are intended to defend against contagion; a powerful red flag warning even if only partially true.

This reminds me of a situation almost a decade ago when I had the unpleasant task of engaging the president of a leading university about one of their finance professors who may have been addressing a few respondents to this very survey when he lectured: “if you want to survive in finance, forget ethics”. Unfortunately for everyone else, even if that curriculum served the near-term interests of the students, which is doubtful given what has transpired since, it cannot end well for civilization. Fortunately, in this case the university president responded immediately, and well beyond expectation, after I sent an email stating that I would end my relationship with the university if that philosophy was shared by the institution.

For directors, CEOs, CFOs, and CROs in any sector, this latest story should only confirm that if an individual is willing to risk a felony for his/her success, then experience warns that corporate governance rates very low on their list of priorities. Black Swan events should therefore be expected in such an environment, and so everything possible should be planned and executed to prevent them, which requires mastering neural networks.

Functional Governance: As simple as possible; as complex as necessary

Functional governance and crisis prevention in the modern complex organization requires deep understanding of the organizational dynamics embedded within data architecture found throughout the far more complex environment of enterprise networks and all interconnected networks.

Kyield Enterprise Diagram 2.7 (protected by Copyright and U.S. Patent)

Are you thinking what I think you may be thinking about now? In fact adaptive neural networks in a large enterprise is quite comparable to the complexity found in brain surgery or rocket science, and in some environments even more so. The largest enterprise neural networks today far outnumber comparable nodes, information exchanges, and memory of even the most exceptional human neurological system. Of course biological systems are self-contained with far more embedded intelligence that adapt to an amazing variety of change, which usually enables sustainability throughout a complete lifecycle—our lives, with little or no external effort required. Unfortunately, even the most advanced enterprise neural networks today are still primitive by comparison to biological systems, are not adaptive by design, and are subject to a menagerie of internal and external influences that directly conflict with the future health of the patient, aka the mission of the organization.

So the next question might be, where do we start?

The simple answer is that most organizations started decades ago with the emergence of computer networking and currently manage a very primitive, fragmented neural network that wasn’t planned at all, but rather evolved in an incremental manner where proprietary standards became commoditized and lost the ability to provide competitive differentiation, yet are still very expensive to maintain. Those needing a more competitive architecture have come to the right place at the right time as we are deeply engaged in crafting tailored action plans for several organizations at various stages of our pilot program for Kyield enterprise, which is among the best examples of a state-of-the-art, adaptive enterprise neural network architecture I am aware of. We’ve recently engaged with large to very large organizations in banking, insurance, biotech, government, manufacturing, telecommunications, engineering and pharmaceuticals in the early stages of our pilot process.

Tailored Blueprint

Think of the plan as a combination of a technical paper, a deeply tailored use case for each organization, and a detailed time-line spanning several years. In some ways it serves as sort of a redevelopment blueprint for a neighborhood that has been locked-in to ancient infrastructure with outdated electrical, plumbing, and transportation systems that are no longer compatible or competitive. Most have either suffered a crisis, or wisely intent on prevention, while seeking a significant competitive advantage.

The step-by-step process we are tailoring for each customer serves to guide collaborative teams through the conversion process from the ‘current architecture’ to an ‘adaptable neural enterprise network’, starting with the appropriate business unit and extending throughout subsidiaries over weeks, months and years in careful orchestration according to the prioritized needs of each while preventing operational disruptions. Since we embrace independent standards with no lock-in or maintenance fees and offer attractive long-term incentives, the risk for not engaging in our pilot program appears much greater than for those who do. In some cases it looks like we may be able to decrease TCO substantially despite generational improvement in functionality.

Those who are interested and believe they may be a good candidate for our pilot program are welcome to contact me anytime.

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