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Tag Archives: tipping

GOOD THING TIPPING IS NOT USED IN JAPAN

November 24, 2020   Humor

Or this guy would be screwed.

He claims to not have spent money except for rent and utilities.

He gets everything via coupons.

We all love coupons and vouchers, but can you imagine living on them almost exclusively for almost four decades? A Japanese man claims to have been doing it for the last 36 years, adding that he hasn’t spent a yen of his own money during that time.

71-year-old Hiroto Kiritani is a minor celebrity in his home country of Japan. His ability to live comfortably on coupons without spending any money unless he really has to is legendary, and he has been invited on numerous television shows and events over the years. Kiritani says that he gets by without spending real money except for utilities and rent. But he’s not as frugal as you might think. He just manages to live comfortably on the coupons he receives from companies he invested in over the years.

Kiritani, who used to be a professional shogi (Japanese Chess), got into stock investment when he was 35. He was invited to teach the staff of an investment company called Tokyo Securities Kyowakai about shogi, and was fascinated by the idea of owning parts of various companies. He bought his first stock in 1984 and quickly developed a taste for it, encouraged by the stock bubble of the 1980s.

Unfortunately, in December of 1989 the Nikkei Stock Average crashed and he lost 100 million yen. It was a terrible blow, but it also helped him discover the worth of investor benefits, an alternative to dividends. Basically, as long as the profitability of a company remains above a certain threshold, shareholders qualify for certain benefits offered in the form of coupons and vouchers.

During the troubled time of the Japanese stock exchange crash of 1989, these investor benefits helped Kiritani get by, allowing him to buy food and clothing without spending any real money. The same happened in 2011, after the Great East Japan Earthquake, when the stock market crashed once again. The coupons he earned were more than enough for him to get by, and as word got out about his ability to live almost exclusively on them, he became famous in Japan.

According to Hiroto Kiritani, if a business performance deteriorates, dividends will be reduced, so this system is advantageous for large investors. Minor shareholders are much better off with the investor benefits that more than 40 percent of large Japanese companies offer, as profitability need only remain over a certain threshold.

Moreover, dividends are dependent on the number of shares a person owns in a company, whereas investor benefits are often times the same regardless of the number of shares. So even owning a single share can qualify investors for various benefits.

Kiritani claims that he gets access to everything he needs with coupons alone. One coupon allows him to go to the cinema for free 300 times a year, another offers free gym membership. He can even buy vegetables with coupons. For example one coupon he gets from the ORIX Corporation allows him to choose a variety of food products from a very generous catalog, for free.

Even though he can get all sorts of groceries with his coupons, Hiroto Kiritani says that he prefers to eat out, which, of course, he can do with coupons. He owns stock in over 1,000 Japanese companies and corporations (of which about 900 are preferential stocks), so he basically has all kinds of coupons to use for everything he needs. He has become so good at living on these pieces of paper that he has been invited on several TV shows and has given interviews for magazines about it.

“I only use cash when paying rent or cover costs that are not 100% covered by my coupons. I don’t spend much cash and live on a special treatment, so in the end, I’m saving more and more money,” Kiritani said.

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How Tipping Point Is Seeking Financial Justice with TIBCO Analytics

April 30, 2018   TIBCO Spotfire

In March 2018, the San Francisco Municipal Transportation Agency (SFMTA) announced reforms that would alleviate the burden of parking ticket fines on low-income San Franciscans. There is increasing awareness that parking citations can result in disproportionate hardship for low income drivers, from late fees, towing, and even loss of income resulting from the impounding or sale of a vehicle. Tipping Point Community, a non-profit that fights poverty in the Bay Area, has been working hard behind the scenes to promote greater awareness of this issue, sharing statistics and recommendations with the San Francisco city government. They’ve spent the last few months crunching through some pretty big datasets to quantify just how bad the problem is.

Ashley Brown, a manager and analyst on the Impact + Learning team at Tipping Point, used TIBCO’s Spotfire Data Science platform to uncover insights from parking citation data. She took advantage of the collaborative capabilities of the platform to work alongside some of TIBCO’s own data scientists. Together, they used the point-and-click analytics tools to develop an array of statistics and visualizations that highlighted the most burdensome aspects of parking citations. The team also used TIBCO Spotfire to create dashboards for communicating the findings to other members of the organization.

The project started last year when Tipping Point came to TIBCO asking for help with analyzing the large parking datasets that it had acquired from the San Francisco MTA through the SF Sunshine Ordinance and the California Public Records Act. The analysts at Tipping Point were most comfortable with tools like Excel and Stata, so they needed a solution that was equally easy to use, but that could easily handle and clan millions of rows of citations and then combine the citation data with neighborhood attributes, demographics, towing data, and more.

They also wanted to move quickly — San Francisco founded the country’s first Financial Justice Project in early 2017, a new venture in conjunction with San Francisco’s Office of the Treasurer and Tax Collector, and Tipping Point was eager to take advantage of the City’s interest in “assessing and reforming how fees and fines impact our most vulnerable residents.” TIBCO recommended deploying Spotfire Data Science within Amazon Web Services, where it can leverage scalable cloud-based platforms like EMR and Redshift. Within a few hours, the team was able to upload datasets and produce their first data workflows.

dashboard How Tipping Point Is Seeking Financial Justice with TIBCO Analytics

Initially, the data scientists from Tipping Point looked for patterns in the way citations were given in different neighborhoods. But what does it mean to compare one ZIP code to another? How should they take into account the size of the area and the density of parking meters or tow away zones? So they started looking along other dimensions — the type of ticket, the make of the vehicle. And immediately they saw that tickets were actually more expensive for certain vehicle types that were perhaps correlated with low or middle incomes. Even tickets of the same type (e.g. street sweeping) had varying costs, most likely because of late fees. The team wanted to measure just how great a burden came from more expensive tickets (e.g. lapsed registrations) and late fees and tow away fines, and if that burden might be higher for low-income people not just because they had less money, but because the tickets they got were actually — in effect — more expensive.

But there was no easy way to relate the income of a driver to the vehicle listed on the citation. The most reliable way to track a driver’s details was from the VIN number, but only a small proportion of tickets had that information. The analysts could use the make of the vehicle, but that was a very weak proxy for income. Eventually, they realized that California license plates held the key — they are issued sequentially (7ABC111, 7ABC112, etc.) and generally remain with the vehicle when it is sold. So the digits on the plate can be converted into a unitless measure of age. Meanwhile, intuition suggests that vehicle age is directly correlated with income, a hypothesis confirmed by several studies (e.g. UT Austin, U.S. Department of Transportation).

The team now had a simple way to measure the impact of ticket costs on owners of aging vehicles. And the results were quite striking: for older vehicles, citations cost 14% more in general, and certain ticket types (e.g. expired registration) cost 32% more; delinquency rates were more than twice as high as the average.

These findings confirm what we hear anecdotally, of people who cannot pay tickets, who rapidly accumulate fees that can be fully half of the original fine, and who then lose their cars and the ability to get to work. Quantifying this — which tickets are most burdensome, and by how much — is the first step to making the system more fair. So TIBCO is proud to support the analysts of Tipping Point and the City employees working to change the way citations are managed.

workspace How Tipping Point Is Seeking Financial Justice with TIBCO Analytics

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The Self-Managing Mainframe and How Tipping Points Surprise Us

October 6, 2016   Big Data

The concept of a “Tipping Point” was introduced by Malcom Gladwell in his book of the same name. Gladwell defines a tipping point as “the moment of critical mass, the threshold, the boiling point”.  The idea is that enough little things happen to add up to an irreversible change after which things happen more quickly and more visibly. Similarly, the recent announcement from Compuware about their partnership with Syncsort is a small step that is part of a bigger trend. It takes us nearer to the tipping point and the result may surprise us all. Let me explain.

For years now IT has been talking about advanced automation using goal seeking behavior. We have tried, event based automation, state based automations, policy based systems and autonomic computing; all attempts to reach towards the goal of a self-managing mainframe. IBM has often led the charge in these areas, at least in talking about them!  Their current approach is labelled “Cognitive Computing” and has been birthed out of enthusiasm for the Watson technology that has had some success and could now be applied to IT management scenarios.

The goal is always to reduce the cost and risk of manual interventions.  Given that computers can fly planes it does seem reasonable that computers should be able to operate computers.  Seems reasonable, but has so far been out of reach to us in the mainframe world! Although we do see “lights out data centers”, these are usually controlled by humans remotely more than they are by self-correcting automation.

The 44th episode of Star Trek was called the “Trouble of Tribbles” and is apparently one of the most watched shows. While they were annoying in many ways, the root cause trouble with Tribbles was the rate at which they multiplied which is the exact opposite of the trouble the IT industry has with the skills needed to manage the mainframe base into the future.

The Boomer-based demographics of the mainframe workforce has been viewed as a problem for over a decade now, but we have yet to address it effectively. The big software companies all have their graduate training initiatives and most companies using mainframes have been cross-training younger staff too. But the root cause issue is that mainframes are complex systems that are not easily understood at the level needed to manage them when things start to go wrong. The problems can multiply faster than your ability to fix them, if you lack the required experience.

On to the scene comes Splunk, the market leader in machine learning from IT log data. This now seems to be the right answer both to how we automate complex, interconnected systems and how we can pass the experience and knowledge of the Boomers onto the Millennial IT generation.

In practice Machine Learning is very different from what we usually think of as Artificial Intelligence.  AI seeks to build computer models that can emulate the functions of human brains. We expect that an AI would perceive its environment and exhibit goal seeking — purposeful behavior that is understood by humans. Ideally it would interact with humans to both receive input and augment our decision making abilities. By contrast Machine Learning is a sub-area of AI that is focused on pattern recognition that allows the system to “learn” and predict based on history, but without their being a rational explanation for that response that a human could understand.  Machine Learning relies on the consumption of masses of granular data that can be processed with statistical analysis to make predictions and uncover “hidden insights” about relationships and trends.  But these “insights” are not necessarily causalities that have an explanation that humans could understand and replicate.

Using machine learning, Splunk apps can peer into the soul of a mainframe in a way that point management tools can’t. The correlation of data from a broad range of sources both on the mainframe and from other platforms can allow the user to see the full context and interaction of events around a problem. Eventually this can lead to the self-healing, automation we have dreamed of.

Self Managing Mainframe Blog 10 5 16 The Self Managing Mainframe and How Tipping Points Surprise Us

Syncsort has been helping people Splunk their mainframes for over two years now and we have learned a lot along the way. Our Ironstream product can access machine data from almost any known source on the mainframe and there is gobs of it!  The data is transformed to be ready for ingestion by Splunk and users can filter what they consume to keep their ingestion based costs under control.

The users of Splunk solutions in general are Enterprise IT teams using data from as many platforms as possible in the quest for an end-to-end view of activity. There are several generalized uses cases from Security and compliance to IT operations and capacity planning. But the power of the Splunk Enterprise platform is such that each customer can build the solution they need very easily

With the addition of mainframe log data the Enterprise teams truly have the landscape covered and can visualize the key business services (e.g. online banking) with end to end monitoring. MF IT is beginning to see the power of this too now that their data is going into the pot.

Compuware’s first toe in the water with Splunk involves the ingestion of SMF records cut by Abend-Aid when an application, or other z/OS program abnormally terminates. The data represents critical fault management information that can be integrated into the DevOps cycle of continual improvement. With this data in Splunk users will have a historical record of faults with failure codes, causes and details about the code that has failed including the last compile date.  Special information is added when a CICS transaction abends recording the transaction ID, and caller details.

Talking with CEO Chris O’Malley about Compuware’s strategy, I expect to see more Splunk based offerings coming from them and Syncsort is certainly committed to helping them with these plans.

DH Blog 1 The Self Managing Mainframe and How Tipping Points Surprise Us

For at least 10 years the incumbent tool providers have talked about modernizing mainframe management. IBM has tried with its Tivoli strategy and CA Technologies tried with its now abandoned Chorus strategy. Numerous vendors slapped browser-based UIs on old technology.

It’s easier with hindsight to see why these tools failed. The “old guard” mainframe boomers just prefer the 3270 screens they grew up with; they can work faster with their incredible experience and years of using finger picking shortcuts.  Those new to the mainframe could rarely do their whole job on the new UIs which also didn’t simplify the task much anyway. The platform was still hard to learn and the new UIs actually ensured they worked slower than their mentors.  Bizarrely the most successful next gen mainframe workers were those that embraced 3270 copying those training them.

The promise of analytics based management tools takes a giant leap ahead and bypasses these points of failure. The new UI that modern IT workers expect is there, but the real point is that the task is transformed.

As the first industry solutions emerge we see that analytics based solutions complement the existing point management solutions more than replacing them. By gathering broad data to provide rich contextualization they will be useful to Mainframe IT, both old guard and new workers alike.  Compuware’s new free app that will collect and visualize application fault data gathered from Abend-Aid is an example of this. Bundled with the Ironstream product, Syncsort offers many other free visualizations of data sources like SYSLOG and RACF access violations.

As these next gen tools mature, progressive IT departments will tend to unify the traditional mainframe/distributed split and the MF IT teams will start to request functions that replace the old tools. They won’t replace them screen for screen and function for function, rather they will make functions obsolete because analytics based automation will increasingly make manual observation and intervention unnecessary and probably counterproductive.

I see a parallel with self-driving cars. Today they seem a bit fantastic and hard to trust. But I suspect we will adopt slowly at first until a tipping point when everyone realizes the technology has matured to the point that it is safer to keep people away from the controls.  When the tipping point is reached for this next gen mainframe automation I suspect that the analytics will be moved back to run on the Z platform somewhere. For a system as dense and powerful as a mainframe you want critical automation on platform. But for now the early tools will be where the action is and that’s on distributed Linux or cloud.

Similar in some ways to a “Tipping Point” is a “Paradigm Shift” as described by the American philosopher Thomas Kuhn, although the latter was describing major transitions in scientific frameworks. As the paradigm shift gets under way there is always resistance to change by the “old guard” until they are eventually overcome and they align themselves to the new order.

I am optimistic that MF IT teams will undergo a natural evolution of acceptance as the value is demonstrated. I suspect that the real resistance might be from the incumbent tools vendors who have not prepared for the changes and find that it impacts their business models.  Under O’Malley’s leadership, Compuware is clearly not one of these, but rather is seeking to be on the front-end, leading the way in applying analytics to a concept of DevOps that bridges mainframe to mobile.

Similarly, Syncsort seeks to play its role in the Digital Transformation by helping customers and vendors undergo the difficult transitions of the data driven economy. If you have a mainframe, let us know when you are ready for the next steps you need to take. Or experiment on your own by downloading a copy of Ironstream that is free to use with Syslog and Abend-Aid data. Good to get started soon, the self-managing mainframe will be upon us sooner than you think.

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The Customer Experience Tipping Point

May 2, 2016   CRM News and Info

By Christopher J. Bucholtz
May 2, 2016 4:05 PM PT

Sometimes, it takes something drastic to change a business’ behavior. Standard procedures can remain in place long after they’ve become detrimental to the business, but sometimes it takes a tipping point to drive home the fact that failing to change is the surest way to fail.

For example, the Ford Pinto’s easily ruptured fuel tank could have been remedied with design changes that ranged in price from US$ 11 to about $ 5 down to just $ 1. Cheap, right?

Mother Jones magazine uncovered Ford memos that showed the automaker’s in-house experts had calculated the value of a human life at $ 200,000, while a serious burn was worth about $ 67,000. Estimating that about 180 deaths and 180 injuries would come to court, the bean counters placed the cost of paying off the victims at $ 49 million, while fixing the car would have cost $ 137 million. Therefore, the Pinto remained unchanged — and that failure to change was justified by a financial number.

Justified, that is, until lawsuits from people burned in rear-end collisions began to reach the press. The judgments and settlements ran into the hundreds of millions of dollars, and Ford was charged, tried and eventually acquitted of reckless homicide.

The PR was devastating — saving money on the Pinto was pointless when no one was buying the car anymore. It was discontinued in 1980.

The Cost of Change

There’s the tipping point: The pain of doing nothing forced a recall, a redesign and improved safety standards. The cost of not changing ultimately far exceeded the cost of change and threatened to destroy what was one of America’s largest companies.

Hopefully, your business isn’t making such life-and-death calculations — but the health of your company depends on your ability to surmount the same kind of thinking that cost Ford customers their lives.

Today, most businesses state as a goal customer experience. Twenty-one percent of companies see “improving the customer experience” as the top goal, exceeding answers like “growing revenues,” according to an Accenture study.

Eighty-nine percent of businesses now believe that customer experience will be their primary basis for competition, a study by Gartner revealed.

Those numbers are impressive, but, as a customer, are you getting the sense that those companies are doing a very good job of competing on experience? The odds are not good. Six in10 companies reported a drop in customer satisfaction in 2015, evidence that the experiences they’re delivering aren’t meeting customer expectations, according to the American Customer Satisfaction Index.

Customer Exodus

That is a very bad sign for those businesses. A full 70 percent of buying experiences are based on how customers feel they are being treated, according to McKinsey.

As a result, many customers are packing up and leaving the companies they’ve long depended on. In 2015, 52 percent of customers switched providers (including retailers, banks, and cable and satellite TV providers) based simply on poor service, Accenture said. Sixty-eight percent of customers will not return to sellers they’ve switched from. Saddest of all, 80 percent of those switchers said the company they defected from could have done something to prevent them from leaving — but did not.

So what’s going on here? Why is customer experience spoken of so highly in the boardroom and then executed so poorly everywhere else?

Part of it is the idea that customer experience is someone else’s job — it belongs to marketing or customer service or some discrete part of the organization that “owns” it.

That idea flies in the face of reality: Customer service is everyone’s job. That starts at the top with the executive board, which must be fully invested in the concept, and those executives not only need to communicate the importance of customer experience to their various departments but make the resources available so employees can have an effect on the customer experience.

Read the Signs

What will that take? The arrival of a tipping point — not one that causes the death of a customer (as in Ford’s case), but one that could telegraph the potential death of your business. It is a tipping point you need to anticipate; if it comes in the form of revenues that are flatlining and customers who are defecting, the data shows that it’s probably too late.

Instead, your warning should come in the form of customer feedback, from either a designed feedback program integrated into your sales and support processes or some mechanism in your organization that allows customer-facing employees to report what customers are telling them about their experiences. Without creating these virtual listening posts, there’s no way to understand how customer expectations are evolving, how your current practices affect customers’ satisfaction with their experiences, and what you might do to make their experiences better.

Implementing changes to enhance the customer experience takes time and can cost money. It forces businesses to stop doing what they find comfortable and adopt new processes. They may have to regroup, reassess and retool their organizations — but the cost of doing so ultimately will pay off, for the company and for the customer. end enn The Customer Experience Tipping Point


CRM Buyer columnist Chris Bucholtz is director, content marketing, for CallidusCloud and a speaker, writer and consultant on topics surrounding buyer-seller relationships. He has been a technology journalist for 17 years, focusing on CRM since 2006. When he’s not wearing his business and technology geek hat, he’s wearing his airplane geek hat; he’s written three books on World War II aviation.

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Robotics tipping point: What business leaders and entrepreneurs need to know NOW (webinar)

November 8, 2015   Big Data

We’re talking real life robotics with experts from Qualcomm and Silicon Valley Robotics. Watch on demand now for free!


Silicon Valley is at the center of the perfect storm of robotics.

It’s at the center of the talent, the investment and the research, the center of the software and hardware industries — all key ecosystem components to build the robotics companies that need to rise to serve the world’s future.

But the event horizon to make that happen is something that needs to be considered in terms of decades, not the typical start-up timelines of a few months to a few years, according to Andra Keay. Keay is managing director of Silicon Valley Robotics, and one of the panelists in this upcoming webinar that will be shedding light on what businesses need to know now to take advantage of the evolution that’s reaching a tipping point.

“Robotics moves slowly but it’s been around a long time,” she says. “The industry has done a great job over the last 50 years of helping us to envision what uses we could make of robots and what that could mean to the quality of our life and our economy. Yet, few of those promises have yet been met.”

The problem, according to Keay is that our expectation of robotics has been inflated.

“We did it wrong. We’ve created this situation where we look at robots as humanoid,” Keay says. “There’s no way that robots have anything like the capability of a person. It’s just absolutely impossible in this century for a robot to replace a human in anything.”

That’s not to say that robotics technology isn’t already very much a part of our lives, or that now isn’t the right time for the industry to become more established and scale.

“Five years ago in the industry we said, OK, the time is right,” Keay says. “It’s clear that robotics is at a point where it’s time to move into new areas. Out of industry, out of research labs, into the service industry and into the home.”

Robotics technologies are well engrained in certain industries, like automotive. It’s just that, for the average person, it doesn’t feel like something that’s particularly close to home. For this reason, it’s easy for people to dismiss robotics as science fiction because it seems so far away and the tipping point moments so elusive.

Understanding what that future may actually look like comes back to understanding the technological and economic drivers that are making robotics peek right now.


Don’t miss out!  Learn more about Andra Keay’s vision for the future of robotics by tuning-in for the webinar “How robotics will change everything, including your business.”

Watch on demand now!


“In many cases it will be taking this ubiquitous connectivity that mobility computing delivers and making a gradual transition to products that are just that much more powerful and versatile,” Keay says. “It’s not going to be a disruption, but once in a while one of those devices will change in how we use it and that will lead to other changes. I think that, with time, robotics will account for the same kind of seismic shift that the internet and computers had in the 20th century.”

One popular belief is that the growth of robotic technology will inevitably equate to the loss of human jobs. But Keay says there is good reason to believe that the opposite will be true.

“Everywhere I look there are industries that have increased the number of robots that they employ. They’ve also increased the number of people that they employ,” she says. “An exciting vision of the future is that of the skilled mobile tradesperson. They’ll still drive a pickup or an SUV but instead of a leaf blower, or a power tool, they’re working with smarter tools that are used in applications to take care of robots.”

Keay sees a correlation between this future of robot builders and technicians and the opportunity to create small, regional pockets of highly-specialized, entrepreneurial manufacturers and service providers of a variety of stripes to support niche industrial and commercial requirements for robotic technology. “Robots increase the number of jobs that are needed and they also increase the productivity of a company that allow it to expand and create even more jobs,” she says. “That will create opportunities for a new class of entrepreneurs.”

Ultimately, the future of robotic technology means creating machines that augment, not replace, humans and socializing the idea that people can work with robots in an integrated fashion.

“Some of those fences are starting to come down as computing power and intelligent algorithms lead us to a better understanding of how people can work alongside robots,” Keay says. “To make a significant impact on our economy, we need to build a lot of robots because there are not that many out there today.”

“People need to build them and people need to maintain them and the only way we can do that is to create opportunities for the industry to grow in Silicon Valley and elsewhere.”

What you’ll learn:

  • The key consumer and commercial applications of robots and drones
  • The role robots will play in societies and economies
  • How smartphone technologies will pave the way to robotics’ future
  • How cognitive technologies will transform our lives and business
  • The foundation of many IoT applications in shaping the way to robotics

Speakers:

Jim McGregor, Principal Analyst, Tirias Research
Andra Keay, Managing Director of Silicon Valley Robotics
Anthony Lewis, Senior Director of Technology, Qualcomm
Maged Zaki, Director of Technical Marketing, Qualcomm Technologies, Inc.


This webinar is sponsored by Qualcomm.

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