Move, Adapt, or Die

Change is eternal in life, nature, business, and technology and you only have 3 options:  1) Adapt; 2) Move, or 3) Die.  I learned this truism in my 7th grade from my social studies class regarding animals response to ecological change, but the same is true for changes in our business environment.  The technology environment has forever been changed by CLOUD (IaaS, PaaS, and SaaS).  The software business and the systems integration (SI) will never be the same and is now presented with 3 simple options: 1) Adapt; 2) Move, or 3) Die.

As humans, especially business people, engineers, etc. who populate a lot of technology field, we believe we can overcome or stem the tide.  While this may work for short term or against small storms of change, it will not defeat real, substantial change any more than you can push back on walls of water from hurricanes.

IBM recognizes the power and importance of Cloud, even if it got off to slow start. Look at the emphasis. Less than 10% of IBM’s revenue is now from hardware. At the same time, everything from IBM is now on the cloud. IBM is even beating back its latest foe – Amazon Web Services (AWS). IBM Beats Amazon In 12-Month Cloud Revenue, $15.1 Billion To $14.5 Billion.

SAP has made a massive shift around SaaS and is adapting.  In 2013, Jon Reed, noted that even SAP executives would love to go on selling traditional on-premise perpetual licenses when he paraphrases the executive with ‘Hey, if we could continue to sell software to customers the way we’ve sold it to them for the last 40 years, we would. But they want new options.’  (more from Jon Reed’s Diginomica blog). Fast forward to 2016 and about 80% of SAP’s revenue is from 4 acquired SaaS products: SuccessFactors, Fieldglass, Concur, and Ariba. If SAP could figure out S/4 HANA cloud, they might even become a dominant SaaS ERP player.

Cloud and specifically SaaS to the software industry is a category 5 hurricane force of change driving a wall of water.  Remember when virtualization was only for non-proction. Now, most systems depend on virtualization.

Moving and adapting take time. So while almost everything will go cloud, it will take time. It will have to make IT and financial sense to move. The argument that some applications will not run well on the cloud will be a moot point when they are rewritten for the cloud.

The hurricane of cloud  in all forms is coming here. What are you doing to make sure your ready to move or adapt (and not die).

 

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Terrific Practical 10 step path for success with Analytics from Jerry Kurz.

Thirty years of experience talking. Worthy of 15 minutes of your time.

Folks, I am very proud and happy to have my dear friend Jerry Kurtz do a guest blog on my site. Jerry runs the Cognitive and Analytics businesses in my portfolio, and is a long time IBMer. He has been in this field for 30 years across SAP, Managed Business Process Services and Analytics and […]

via And Jerry Says : A Path to SUCCESS with Advanced Analytics — Vijay’s thoughts on all things big and small

WordPress vs. LinkedIn

Which site is best for business blogs? I prefer WordPress’s powerful editing tools. I seem to get better “following” on LinkedIn. What is your advice, comments, suggestions, or ideal solution?

WordPress is a content management tool service that is excellent tool for writing blogs and creating consistent, stylistic web pages. It has basically eliminated much of the need for IT departments to create standard variable content for their websites. For example companies like CNN, Forbes, Vogue, MTV news, The Rolling Stones, Facebook , NASA use it to create content for their websites. There are 17 blog post every second of every day from WordPress and it’s wired into everything with over 45K plugins. All of this comes from a company with 449 employees.

Alternatively, LinkedIn blogs are simple with a single style sheet, text, pictures, and video. It is more of an expanded status than a blog and definitely not a content management service. LinkedIn is popular with over 500M users with about 40M being students. That is an impressive journey from being 4,500 members in 2003. LinkedIn is big with over 10K employees in 30 cities around the globe and providing 24 languages. They’ve made a long journey from being just “business Facebook.” That doesn’t even include the impact from the Microsoft acquisition.

I liked LinkedIn because their blogs seem to get the most notice and response. Even when I link my WordPress blogs to LinkedIn, they don’t get the same notice. I think it is because WordPress blog looks no different than any other web link on LinkedIn. I like WordPress because it is a great writing and content tool. I like having my own style, colors, indexes, and other features. For me, the ideal solution would be to have WordPress as the blog engine inside of LinkedIn. Maybe it’s a plugin that I just haven’t yet found. Something else for my “to do” list.

What do you suggest?

References below:

LinkedIn: About LinkedIn

WordPress Online Support: WordPress Interesting Facts

SkillCrust: WordPress Facts

Forbes: Microsoft acquires LinkedIn

Now technology bubbles up to the Business Enterprise level from Consumers

The technology at the Consumer Electronics Show (CES) will bubble up into business and into enterprises quickly – far quicker than IBM, HPE, Cisco, or any of the enterprise strength IT companies would like. Initially technology came from business to consumers – think PCs. The sheer size of consumer market and its willingness to put up with beta releases makes the consumer world the ideal proving ground for the less fault tolerant enterprise world.

Drones are bubbling up. While they started in the military, they now are big segment of the consumer market. Drones or autonomous flying vehicles have been improving including automated stabilization, 4K cameras, enhanced flying times, etc. Many of them have dozens of computers on board and some rather impressive programming to make them simple to use.

Due to the wide-spread usage of drones in the consumer market, they are vastly improved and far less expensive. One of the leader’s in the industry, DJI’s basic drone, Phantom 3 Standard, is just under $500 flying for ~25 mins, includes GPS tracking, tracks subjects based photo recognition using a 1080 camera for photos and stills. Refurb is $329 and knock offs are even cheaper.  Just 5 years ago, this would have been a top of the line $5K drone, if even available.

Part of the attractiveness of the consumer world is scale. The other factor is that the consumer world is filled with willing beta testers. Recent releases of drones from reputable companies come with lots of complaints on the internal boards of not flying well, not following waypoints, and simply flying away. A drone that loses its signal is supposed to fly back to the point of origin and land. In the business world, this would be a breach of contract and might result in loss of property or life. In the consumer world, the drone manufacturer can just send a firmware update, a coupon, or at worst replaces the device.

While scale makes the money, it is the willing beta tester that enables advancement. Haven’t you signed up to be a beta or an alpha tester. I know I am for many of IBM’s early release programs. We have marvelous internal site called “Technology Adoption Program” where individuals submit their software inventions. Many have become key enablers of IBM’s business.

What else might bubble up? Virtual Reality has real possibilities for training. Consumer IoT devices will make it into manufacturing. Fitness IoT devices will make it into Medical IoT devices. Home IoT devices by Amazon, Google, and Apple will rapidly make both IoT device and cognitive (AI) advances as we all beta test their devices for more hardened uses. I know send in correction reports regularly and in general they do a good job following up. The list is endless as people gobble up consumer technologies.

We used to make fun of 3rd world countries using the computers out of toys to steer their weapons. Maybe they were just ahead of their time.

Grammar saves lives & numbers can hurt

Pasta should be cooked in salty water even if the numbers say otherwise. Olive Garden in order to get lifetime warranties on their pots, eliminated salt in the water  and they still don’t salt the water as of today (April 2016). As a decent cook, and others agree, you need salt in the water if you want the pasta to taste good. Only some junior analyst who thinks Olive Garden is the pinnacle of Italian food would think saving about $80 a year, the price of pot or the loss of 3 customer meals, would have no impact. Plus to cover the lack of taste in the pasta, you have to add more salt and sugar, often corn syrup in commercial products, to the sauce.

When we use numbers, we need to make sure the numbers, analytics, or metrics correspond to a meaningful output. I’ve seen consulting companies cut consultants to increase savings, not recognizing that if you have fewer consultants, you’ll have less revenue since consultants are the product. In a classic case, the US government made selling ice cream and visits to beaches illegal in an effort to stop polio.  The increased ice cream sales and visits to the beaches was due to the heat. The same heat that enables the polio virus to stay alive long enough to  spread.

At SAP TechEd a few years ago, I watched with fascination as Nate Silver kept telling the interviewer that the thing we really needed was to have highly knowledge analyst who understand the complexity of real life topics – actual experts. The interviewer kept wanting him to expound on SAP tools, but Mr. Silver held his ground. It is not the tool, the metrics, or anything that is technical. Some tools are better or easier than others, and SAP has some great tools was all he’d say, but paraphrasing the interview, he said “you have to understand the subject,  the relationships, and why a number might go up or go down”. Once you know the basics of the real system, you can use the numbers to look deeper, but not until.

If grammar can save lives (“let’s eat, grandma” vs. “let’s eat grandma”) then analytics can ruin them. Many decisions, such as layoffs or substituting equivalent products, are made on the basis of numeric analysis. As responsible analyst, we must make sure our metrics of success, failure, and our discoveries makes sense. Does the data really explain the results? Is it reasonable? What is scientific, logical reason for the outcome?

As we make more data available online and accessible, we must make sure it is clear what the data represents. Finally, we have a duty to be ardent guardians of proper use of analytics and be aggressive prosecutors when others misuse data and analytics. Numbers, and the conclusion we derive from them, directly impacts people’s quality of life. Number’s can hurt.

Consumer Technology enables SCALE and RAPID INNOVATION

Consumers enable SCALE and RAPID INNOVATION in Technology. As I walked around the Consumer Electronics Show (CES), I could see how the technology will “bubble up” into business and into enterprises quickly. Initially, technology came from business to consumers – think PCs. The sheer size of consumer market, hunger for new functionality, and its willingness to put up with beta releases makes the consumer world the ideal proving ground for the less fault tolerant enterprise world. Companies that span both world can leverage the consumer world for its SCALE and RAPID INNOVATION and bubble those innovations into the enterprise world for higher profits.

Drones are an example of bubbling up. While they started in the military, they are now a big segment of the consumer market. Drones or autonomous flying vehicles have been improving including automated stabilization, 4K cameras, enhanced flying times, etc. Many of them have dozens of computers on board and some rather impressive programming to make them simple to use. First it was movies, then multi-million dollar homes and now you see mid-market homes with drone footage. It has become a toy for teenagers, too.

Due to the wide-spread usage of drones in the consumer market, they are vastly improved and far less expensive. One of the leader’s in the industry (Drone Market Map)( https://www.droneii.com/top20-drone-company-ranking-q3-2016)), DJI’s basic drone is just under $500, flys for ~25 mins, includes GPS tracking, tracks subjects based photo recognition using a 1080 camera for photos and stills. Lots of knock offs are even cheaper.  “Toy Drones” are just $50! Five years ago, the DJI basic drone would have been a top of the line $5K drone, if even available.

Part of the attractiveness of the consumer world is scale. The other factor is that the consumer world is filled with willing beta testers and relatively low liability costs. The consumer world is an agile one where cycles occur very quickly. A typical enterprise development cycle is 18 months. In the same time in the consumer world, you’d see a major hardware, firmware, and at least 30+ releases of software.

The demand for new and the tolerance for risk is high in the consumer market. Recent releases of drones from reputable consumer companies come with lots of complaints on the internal boards of them not flying well, not following waypoints, and simply flying away. In the business world, failure to perform would be a breach of contract and might result in loss of property or life. In the consumer world, the drone manufacturer can just send a firmware update, a letter, a coupon, award you status on their web site as hero or pioneer, or at worst – replace the drone. It’s a trivial price enabling those dipping into the consumer world to advance faster than those in the business world.

While scale makes the money, it is the willing beta tester that enables advancement. Haven’t you signed up to be a beta or an alpha tester. I know I am for many of IBM’s early release programs. We have marvelous internal site called “Technology Adoption Program” where individuals submit their software inventions. Many have become key enablers of IBM’s business. They grew up fast by being adopted and depended on by IBM’s business.

What else might bubble up? Virtual Reality has real possibilities for training. Augmented Reality with heads up displays and glasses will be welcomed the field. Giving schematics, UV and Infrared vision, and more to workers. What will make it become easily affordable and useful – another Pokemon Go that plays with glasses pushing it onto millions of users’ foreheads.

3D printing is coming of age, but I can see point where 25% of households have plastics printer and your hardware store has a metal one. No inventory of 500K parts – just print it. Lots more like LED lights, Home Automation, Sports Fitness, etc. will bubble up.

Finally, Artificial Intelligence (AI) may be the biggest winner from the bubble up effect of the consumer. The key to AI is having huge knowledge base or corpus and lots of training. Where better than the consumer market with a potential of 7 billion users – the population of the world – to train your AI. Whether it is Siri, Alexa, Cortana, Watson, or Google, these companies’ AI programs will benefit from the consumer training it. You get a voice interface and they get you to train their AI.

What do you think will be the next big bubble up technology from the consumer world to the enterprise world?

 

 

Our 2 fears of Artificial Intelligence (AI)

We have two (2) overarching fears of AI. AI domination is the most irrational fear where AI becomes smarter than organic intelligence and wipes out or subjugate the organic life forms. This plays out in number of number of science fiction works like “Transformers”, “Terminator” and “I, Robot”. In “I, Robot”, the AI unit is claiming to do it in service of humanity. I’d argue AI domination is the least likely scenario of doom and maybe in dealing with our second fear, we can solve our AI domination fear, too.

The second fear is that of misuse of AI. I’d argue that is the same argument has been used against every technological advancement. The train, automobile, nuclear fission, vaccines, DNA, and more have all been cited for ending the world. I suspect someone said the same thing against the lever, wheel, fire, and bow. Each has changed the world. Each has required a new level of responsibility. We’ve banded together as humans to moderate the evil and enhance the positive in the past. Ignoring it or banning it has never worked.

Amazon, DeepMind/Google, Facebook, IBM, and Microsoft are working together in the “Partnership on AI” to deal with this second fear as described by the Harvard Business Review article “What will it take for us to trust AI” by Guru Banavar. It is a positive direction to see these forces coming together to create a baseline set of rules, values, and ethics upon which to base AI. I’m confident others will weigh in from all walks of life, but the discussion and actions needs to begin now. I don’t expect this to be the final or only voice, but a start in the right direction.

I hope the rules are as simple and immovable as Issac Asimov’s envisioning of the  3 laws of robotics on which the imagined, futuristic positronic brains power AI robots. Unfortunately, I doubt the rules will be that simple. Instead they will probably rival international tax law for complexity, but we can hope for simplicity.

The only other option is to stop AI. I don’t think it is going to work. The data is there and collecting at almost unfathomable rate. EMC reports stored data growing from 4.4ZB in 2013 to 44ZB in 2020. That is 10^21 (21 zeros) bytes of data. AI is simply necessary to process it. So unless we are going to back-out the computerized world we live in, we need to control AI rather than let it control us. We have the option to decide our fate. If we don’t then others will move forward in the shadows. Openness, transparency, and belief in all of human kind have always produced the best results.

In the process of building the foundation of AI, maybe we can leave out worst of human kind – lust for power, greed, avarice, superiority. Maybe the pitfalls in humans can simply NOT be inserted in AI. It will reflect our best and not become the worst of human kind – a xenophobic dictator.

Putting the AI genie back in the bottle will not work. So I think the Partnership on AI is a good first step.