deal architect

2017 Flyover

Facebook generates an annual collation of “memories” for every member. I looked at mine and felt it was too shallow. Google Search summarizes the most common queries across its user base at the end of each year in video below. And I wondered mine were so different. Dramatically different.

First something about my Google searches. It has been an anguished year for many given the political situation and it shows in the Google video. I avoided too much CNN or Fox, too many political conversations or commentary. I worry that we are so distracted that our productivity and our economy suffers. Having said that, here’s a thank you to those worrying on our behalf about the political state of the world.  

On the Facebook summary, here's a longer explanation. This year, I started traveling for work and play with my iPad Pro and Pencil. It has changed how I take notes and photos and how I record interviews. I think I am more prolific than usual, and as a result files uploaded to my Google Drive grew by more than 100 gb over the course of the year. That’s a lot of experiences and memories.

Especially since it was a “book-less” year for me, for a change after 6 years. Allowed me time to write 500 blog posts (about average on annual basis) and I will end up paying the price next year with 2 books on the docket. But it also gave me time to spend time presenting on my last book, Silicon Collar. It is controversial because of its optimism about automation and impact on jobs. Also I got to do more advisory work for clients than usual. I was also honored to be invited to join the International Board of Visitors for my alma mater, the TCU Neeley Business School.

I like a wide variety in vendor events I attend, and this year some stood out even more than usual. The Workday summit, Plex’s Customer Advisory Board, America’s Cup in Bermuda, SuiteWorld for the first time in Las Vegas were particularly striking. I went back to SapphireNow after an absence of 5 years and found that very helpful.

Margaret and I celebrated our 27th wedding anniversary. Our milestones are usually low-fuss, but we both feel very blessed with this accomplishment. We are even prouder Rita and Tommy are now contributing members of society. They have had numerous part-time jobs and internships, but they are now both in very interesting careers. In a role reversal, it is so nice they are introducing us to new restaurants and experiences.

We had a fantastic family reunion over Thanksgiving. Every couple of years we have cousins and friends convene at our place. The 2017 one was especially memorable because we explored Tampa Bay with them. We have seen so much of the world and so little of our beautiful part of our world so it was nice to be tourists at home.

On a less pleasant front, we evacuated our house for the first time in 25 years to escape from Hurricane Irma. We dodged a bullet though, and mostly had yard damage

Both Margaret and I had more than our fair share of aches and pains this year. I had a food poisoning episode which led to weeks of scans and specialist visits. My knees and Margaret’s back continued to nag. My walking partner, Rudy, a neighbor’s bichon passed on to my dismay.

All this made the fact that we still got around so much more satisfying. My FitBit tells me I will have walked 2.8 million steps this year, or over 1,300 miles. That’s only slightly lower than my annual average. Margaret went with Rita to Machu PIcchu in Peru. I am awestruck they were able to get there and back in just 4 days while adjusting to the altitude of the Andes and the strenuous climbs.

Much of our personal travel this year was in 3 day weekends in rural places around the US. Margaret and I drove around parts of Colorado, Florida, New Mexico, Tennessee, Virginia and Wisconsin. These are cynically called “flyover states” but each to us was magical in the natural beauty of caverns, hills and miles of farm and waterfront we saw. This is one amazing country! And thank you to Southwest which gives Margaret a companion pass to move around the wide expanse.

So, sorry Facebook, I only shared with you a tiny piece of what we experienced in 2017.

Thank you to all my reading and consulting audiences for your continued support and feedback. Happy holidays and here’s to an even better 2018!

 

The “Star Wars” Jobs economy

Lots of people sat through the credits at the end of The Last Jedi waiting for a post-credit scene or for bloopers.

Margaret and I did to see all the job titles that went into making the movie. It is a practice we started a few years ago. It’s fascinating to recognize the people who bring these movies to life (some profiled in the video below) and how CGI, sound and other technology continues to work alongside the human element, not replace it. In Silicon Collar, I had a section which looked at the man-machine mix in the animated movie, Zootopia.

Star Wars has plenty of digital talent – SFX technicians, droid puppeteers and LIDAR techs. It also has old school carpenters, stunt artists, travel coordinators, weather consultants and costume makers.  It is a microcosm of our changing labor economy.

Before you say but this is not the real world, with every episode the science-fiction becomes science-fact. After episode 7, Infoworld wrote in 2015 about 10 technologies that are “almost here”. With this episode, US News writes about “Real-Life Tech” inspired by the movie. Wikipedia  has an bigger section on how lasers, cybernetics, prosthetics, biotech use in the movies don’t seem so distant. Think of the ripple effect on jobs in medicine, energy, defense.

Want more reality? Luke Skywalker hides in a spectacular, remote island called Ahch-To. That is actually Skellig Michael, in the SW of Ireland. Other scenes were shot in Dubrovnik, Croatia and at the salt flats in Bolivia. Should open up new tourism jobs.

Then there is the impact on jobs in the theater and concessions industry. The AMC I went to has new reclining seats, Dolby Surround Sound, IMAX screens. Lots of concession sales.

Then there are new toys like the Porgs and R2-Q5 in the movie and many others here. Lots of Christmas retail and delivery jobs.

The film has made $450 million around the world since opening overseas Wednesday. And it will not even open in China till January 5.

Long and short – plenty of jobs, digital and old school. In a galaxy pretty close to us. 

The other technical debt

The CEO of a manufacturing company expresses frustration his plant employees have to key entries into the shop floor system. Why not a voice interface? And anticipating the objection, says don’t tell me they cannot use noise canceling technology to offset the sounds of machines?

Not an unreasonable request at all. And one of many requests enterprise vendors have been ignoring.

For years now, Gartner and other analysts have been telling customers they have accumulated technical debt to vendors by not upgrading to the latest releases of software. But we have forgotten what Ward Cunningham said in 1992. He is credited with having coined the term

"Shipping first time code is like going into debt. A little debt speeds development so long as it is paid back promptly with a rewrite... The danger occurs when the debt is not repaid.”

Vendors have been accumulating gobs of technical debt by not keeping the software up with the times, even though customers keep paying them maintenance or annual subscriptions. You see it manifested in many ways

• Continued customer use of spreadsheets, often large ones, when analytical tools were supposed to have replaced them
• Vertical apps which continue to only be supported in on-prem mode when vendors have been pushing cloud and in-memory versions of horizontal apps for years
• Significant customer customizations because the functionality delivered was inadequate
• Large number of “ring-fence” tools and applications because the core functionality delivered by the vendor was inadequate or has not kept up over the years  
• UX lagging that which consumer tech has been delivering for a while
• Vendor investment in platforms and tools, when customers would prefer the money going into application functionality

Part of the issue is vendors follow a formula to keep investors happy and only spend 10 to 12% of revenues on R&D. And worse, much of that goes towards investment for new markets the vendor wants to chase.

There is an old expression “Dance with the one who brung you.” Pay off your technical debt to your incumbent customers. Or risk losing them to third party maintenance or having them ring-fence you to insignificance.

Tone down your AI expectations

We have had many previous hype cycles around AI. As I wrote in Silicon Collar : “Since the 1950s! That is when Alan Turing defined his famous test to measure a machine's ability to exhibit intelligent behavior equivalent to that of a human. In 1959, we got excited when Allen Newell and his colleagues coded the General Problem Solver. In 1968, Stanley Kubrick sent our minds into overdrive with HAL in his movie, 2001: A Space Odyssey. We applauded when IBM’s Deep Blue supercomputer beat Grandmaster Garry Kasparov at chess in 1997. We were impressed in 2011 when IBM’s Watson beat human champions at Jeopardy! and again in 2016 when Google's AlphaGo showed it had mastered Go, the ancient board game. Currently, we are so excited about Amazon's Echo digital assistant/home automation hub and its ability to recognize the human voice, that we are saying a machine has finally passed the Turing Test. Almost.”

The good news is over the seven decades, the AI community has gifted us a wide range of big words like deep learning, neural networks, cognitive computing and natural language processing.

Yale computer science professor David Gelernter thinks we have only scratched the surface. In his book The Tides of Mind, he calls it “the spectrum of consciousness,” which is “essentially a range of mental states through which all humans cycle each day. The cyclical element is crucial and underlies his metaphor of tidal motion. At the upper end of the spectrum, mental high tide, we are focused on the outer world, biased towards logical and abstract reasoning, and more likely to remember our experiences later. But as we drift down through the middle and into the lower reaches of the spectrum, we become increasingly conscious of the inner worlds of memory, prefer narrative to logic, and cross eventually into the difficult-to-remember realms of dreams.”

But we are told this time it is different. We can train machines with the gobs of Big Data we have been collecting and we have computing power in the cloud like we have never had before.

But do we really have enough of each? Listening to Ginni Rometty, CEO of IBM at Dreamforce last month (see interview below – Marc Benioff has always been a very respectful interviewer, and Ginni is in fine form), I have my doubts. Ginni makes the point that 80% of data is not searchable. I would argue that ratio for enterprise data is even higher. Most useful data is locked up in on-prem systems. Getting permissions to have broad samples of such data will be no easy feat. Then you have the issue of semantics and master data rationalization across the multiple sources of data. We are only now seeing early versions of natural user interfaces by training machines around decades of voice/accent data collected by the likes of Nuance in transcriptions ,voice mails we have been leaving each other since the early 1980s and photos we have been uploading into the cloud.

Ginni is also preparing us for a world of quantum computing because for a growing range of scenarios even today’s supercomputers (or cloud infrastructure) are not enough. Take the trajectory of weather forecasting. Decade after decade, data sets have become larger with satellites, buoy sensors and Hurricane Hunter type sorties collecting data on moisture, temperature, wind speed and other metrics. The modeling has become way more complex. So, the thirst for ever increasing compute capacity continues. Forecasts keep getting better and better – but tell that to many of my fellow Floridians who evacuated multiple times as Hurricane Irma made a mockery of most forecasts. As a renowned meteorologist said “I was very surprised not by how one model was going back and forth -- but by how all the models were going back and forth.” Exactly, now wait till Salesforce's Einstein and IBM's Watson start contradicting each other :) Customers are being told they need both.

Ginni does not overtly talk about it, but 50% of IBM revenues come from services. Go ask early Watson healthcare clients how much of the tab was in services. IBM's interest in Salesforce's AI tool, Einstein is being driven by its Bluewolf services unit. Amazon offers its engineers as consultants via its ML Solutions Lab, Google via its The Machine Learning Advanced Solutions Lab. We will need highly skilled labor to train the machines. And we will also need tactical labor to keep refining the data. Amazon has its talent networks – the Kindle author, the Flex courier, the Mechanical Turk and fulfillment networks it can mine. Apple has its iTune and iOS networks to draw from. 

Enough usable data, enough compute, enough talent? Take a hard look at each from the lens of your AI project.

Far more tactical implementations of Robotic Process Automation (RPA) are more promising. RPA is not machine learning, it uses software bots to mimic human activity – like logging in to a system, copying and pasting data across systems. The payback is much lower than what AI/ML promises, but it removes the drudgery and increases productivity of many white collar jobs. 

Mihir Shukla of RPA vendor, Automation Anywhere told me in an interview for Silicon Collar

“Think of the impact of this on real estate requirements. I can take what would need offices in six large buildings and put them on two racks. I can help consolidate global offices. A cognitive bot can process an invoice in 30 languages—I don't need centers in the Philippines and other centers in Japan to deliver diverse language skills. Think of the employee recruiting and onboarding time we can help save.”

It is a more traditional definition of savings that comes with automation, and far more realistic. But even there, many services firms are pushing RPA which is a bit of a red herring when it comes to implementation costs.

Of course, many companies are being deluded by the promises of AI (and broader automation). J.P. Gownder, a Forrester analyst says if you don’t have realistic expectations “You’ll be inclined to automate too many roles — at the expense of both customer and employee experience.  You won’t hire the right mix of new roles— or any new people at all.”  In other words besides seeing poor payback from your AI projects, you may hurt other critical parts of your business.

On the flip side, we may not need to worry as much when Elon Musk says AI is more dangerous than N. Korea. Or when Prof. Hawking says AI will end mankind. The bad guys will face the same data, compute and talent shortages that AI for good is facing.

Tone down your AI expectations. And get ready for the next generation of AI big words.

“Make Renewables so Cheap that they KILL Fossil Fuels”

Peter Diamandis, of Abundance fame, put out this rallying cry in a recent post. Renewables definitely need a kick in the behind. A recent conversation with my lawn guy, Bruce told me how far they still have to go.

I asked him if he had considered one of the new robotic, electric lawnmowers for a couple of thousand before he invested in his $ 16,000, gas-fueled 35 hp Gravely. He smiled and said “I can cut your front yard in less than 3 minutes. The robots are much slower and often run out of battery, and then you have to restart the cycle. Also lawn in Florida grows taller than what the robots can tackle ”. The conversation then turned to his set of DeWalt tools. He has a whole collection which run on lithium-ion batteries. Even there he said “I only use the battery powered blower at night to not bother the neighbors with the noise of a gas powered one”. On and on he went on why gas fueled appliances are still so much more efficient.

Bruce is smart enough but he uses simple phrases. He was saying energy density matters as much as economics. Renewables need to scale up.

The opportunity has been around for decades to kill Fossil Fuels, but renewables continue to rely too much on hope and fear

Country after country is announcing plans to ban gas or diesel fueled cars in the next couple of decades. Reason to celebrate, right? Yes, if you are blessed to live in countries like Norway and Canada where utilities get the bulk of their fuel from hydro. In most other countries, EVs are only marginally greener than cars in Brazil where 25% of fuel is cane-sourced ethanol. This chart from Our World in Data ( a project at U. of Oxford) shows how far renewables have to go just to replace coal usage in utilities. Add nuclear to that, given skittishness around that, and the opportunity for renewables is almost intimidating.

Another hope of the renewable sector is we will soon run out of fossil fuels. Tell that to bankers who plan to take Saudi Aramco public next year at a valuation between $ 1 and 2 trillion. Yes, it will be the world’s largest ever IPO. M. King Hubbert came close on his projections of decline in US oil reserves in graph below. But he did not factor the stubbornness of George Mitchell and other energy entrepreneurs and their fracking and horizontal drilling innovations. Yes, some day we will run out of oil. For now, renewables need to quit hoping that day is anytime soon.

Then there is the fear mongering. 2017 was a torrid hurricane season (it officially ended November 30) and all the boo-birds are out saying if we had moved to renewables we would not had such a ferocious time. Hello – since records were kept, 2017 was only the seventh most intense season in the Atlantic basin. And here’s another contrarian data point “Harvey ended the record-smashing 4,324-day-long “major hurricane drought” in the United States when it crashed ashore near Corpus Christi, Tex. And then it stalled, maintaining tropical storm status for 117 hours after landfall, a record for a Texas landfalling hurricane.”

It’s uncanny that for a decade after the documentary The Inconvenient Truth was released, we had that hurricane drought. Now that its sequel has been released, hopefully we will see another long respite

So, yes I hope the renewables industry steps up to Peter’s rallying cry. Start executing relentlessly and quit hoping and spreading fear.

The Future of Work–in an automated world

This time, last year I felt very lonely. In writing Silicon Collar, I was one of the few voices who is not pessimistic about automation killing masses of jobs. I kept getting asked, how can you ignore the rapid pace of technological evolution?  I kept telling people adoption of technology has not evolved as rapidly. Society has its “circuit breakers” to too-rapid automation. Read about the century of automation I have cataloged in the book and how tens of millions of jobs have changed, but survived, in most sectors. Yeah, but this time it is different, I would hear back.

Last week, I finally felt some vindication. I was at a Cognizant event which celebrated work and workers. Even the background music was mostly about the joys of work. As a slide referenced, it was as Robert Plant of Led Zeppelin often called it “a song of hope”. There was nobody clamoring for a dole or Universal Basic Income. It was about how automation is transforming work or creating new type of work. And yes, it was good to hear themes common with those in my book. Automation targets 3D tasks – dull, dirty and dangerous ones. Work has been central to mankind for millennia. Our last names handed down for generations convey that fact. The handouts had emphatic statements like “But a world without work is a fantasy that is no closer to reality in 2017 than it was 501 years ago upon the publication of Thomas More’s Utopia.”

Oh, there was a lone dissenter – Prof Vivek Wadhwa who kept saying (without much data to back him up) that jobs are lost. His pessimism only made the pragmatism of the others stand out even more. And even he was optimistic about future of healthcare and renewable energy.

The Cognizant speakers like Ben Pring – most ex Gartner and Forrester analysts and now part of its Center for the Future of Work – unveiled 21 new jobs they believe technology will help create. The graph below summarizes them.  10 of the jobs are in B2C settings, the rest in B2B settings.

Some of the job titles are awkward sounding but each is believable. Who would not like to see a member of their family benefit from a “augmented reality journey builder” before dementia or Alzheimer’s potentially afflicts them? Who does not think we will need analysts who can help run our increasingly smarter  cities? How can you argue with any of the jobs (which they say they identified from hundreds of candidates) all of which carry some element of coaching, connecting or caring? This 60 page white paper describes each of of the 21 jobs in some detail.

Another session had Danish serial entrepreneur, Dennis Mortensen, founder of x.ai, which has developed two AI driven personal assistants, Amy and Andrew which schedule your calendar. His humility was breathtaking. His highly focused bots have taken him years to build and mature. He did not expect AI to  dramatically reshape the world of more complex work anytime soon.

A guest speaker was J.P. Gownder of Forrester. He had a nice framework for how work is evolving – machine-first, machine-human teaming and humans-first. Even in machine-first scenarios like at  the Goldman Sachs cash equities desk, the number of traders has dropped from 600 in 2,000 down to 2. But now 200 software engineers support the automated trading. In contrast, in a human-first scenario, Autodesk is hiring novelists to write scripts for its chatbots.  He had plenty of other examples of man leading or following machines or teaming with them. But each still has a human element.

To me, one of the best slides from the day was about this bell curve. While the day focused on the right of the curve and new jobs, I am much more heartened by the bulk in the middle that are being transformed by technology. I have written about roofers who are using drones and tools like EagleView. I have written about digital calipers, ring scanners and AR goggles on the shop floor. Gownder had examples like Robin Technologies which is bringing Roomba like robots to lawn care. Yes, as they improve in horsepower and battery life, they will take away the drudgery of cutting grass in the summer heat, but they will also allow the care taker to focus much more on landscaping. That’s what automation has always done – allowed humans to work smarter, safer and speedier.

I expect Cognizant to keep evolving its research on the topic. Try and catch a similar session like the one I attended in a city near you. It will inspire you or at least make you feel less morbid about automation. And the music will certainly cheer you up.