Management 101: Sensitivity to Staff
January 24, 2016
I read “Yahoo CEO Cruelly Instills Fear in Her Workforce with Ominous Joke: No Layoffs This Week.”
I love this approach to motivation. I remember hearing Charles Colson, the pre-reformation version, gentle reader, explain to me and others in the meeting the value of fear and intimidation. By golly, I perked up. We may have been contractors to the president’s science advisor, but I got the message. Let’s see. I think that was in the early 1970s. I was useful to my employer because my father and his brother had been fund raisers for Senator Dirksen and Congressman Michel. As a result, I found myself in some darned interesting opportunity spaces when I was in Washington, DC. I saw the “hearts and mind” wall art.
If you are not familiar with the pre reformation Mr. Colson, you might find this obituary helpful. I highlighted this passage:
Charles W. Colson, the Republican political operative who boasted that he would “walk over my own grandmother” to ensure the reelection of President Richard M. Nixon and went on to found a worldwide prison fellowship ministry after his conversion to evangelical Christianity.
The write up about the fascinating Yahoo and its Xoogler leader reported:
The backlash is mounting against Yahoo CEO Marissa Mayer for a horrible joke she attempted to make recently at a companywide meeting, and now many in her presumably deflated workforce fear for their jobs. Mayer reportedly told the company that there will be “no layoffs… this week,” and although her comments were intended to be humorous, many who call the tech giant home are left wondering about their employment status within the company. “This is the reason employee morale is so low,” said one employee to the New York Post, who wished to remain anonymous out of fear of retribution.
Yep, humor works really well as a management mechanism. Nothing relaxes an individual like a reminder that the mortgage may go unpaid, one’s home life is disrupted, and one’s professional standing is decimated.
Good stuff. Mr. Colson would have approved. My recollection is that he liked to be a bit more colorful. You know. The grandmother thing was a nice rhetorical touch. Xoogler management 101, gentle reader. Think what one does in management 102.
Stephen E Arnold, January 23, 2016
Experts Team for Complex Data Infographic
January 23, 2016
I wish to point out that experts are able to make the complex easy to understand. For an outstanding infographic about the state of complex data, you will want to navigate to “The State of Complex Data in January 2016.” Because this is the 23 of January 2016 as I write this, you must click tout de suite.
The explanation of the state of complex data is the work of the experts at Ventana Research and the Aberdeen Group. Believe me, these outfits are on top of the data thing.
I noted this statement in the write up:
As for the diversity of the data – 71% of organizations analyze more than 6 data sources, and an astonishing 23% use more than 20. Doubtless, today’s data comes in many shapes and forms, posing new challenges and presenting new opportunities.
Astonishing results? Absolutely.
I am, however, not exactly certain what “complex” data mean. But help is at hand, according to the article:
This guide covers the topic of data complexity and presents the distinction between Big, Simple, Diversified and Complex data, and will enable you to understand the complexity of your own data and how to determine the best tools and techniques you’ll need to use in order to prepare, analyze and visualize this data.
Thank goodness there are keen intellects able to explain the differences among the big, simple, diversified, and complex. At the back of my mind is this reminder from one of the glossaries I prepared: Data are facts and statistics collected together for reference or analysis.
Obviously I was too stupid to realize that data can be big, simple, diversified, or complex. Now I know. My life is better.
Stephen E Arnold, January 23, 2017
Alphabet Google Justifies Its R&D Science Club Methods
January 23, 2016
In the midst of the snowmageddon craziness in rural Kentucky, I noted a couple of Alphabet Google write ups. Unlike the sale of shares, the article tackle the conceptual value of the Alphabet Google’s approach to research and development. I view most of Google’s post 2006 research as an advanced version of my high school science club projects.
Our tasks in 1960 included doing a moon measurement from central Illinois. Don’t laugh, Don and Bernard Jackson published their follow on to the science club musing in 1962. In Don’s first University of Illinois astronomy class, the paper was mentioned by the professor. The prof raised a question about the method. Don raised his hand and explained how the data were gathered. The prof was not impressed. Like many mavens, the notion that a college freshman and his brother wrote a paper, got it published, and then explained the method in front of a class of indifferent freshman was too much for the expert. I think the prof shifted to social science or economics, both less rigorous disciplines in my view.
Google’s research interests.
The point is that youth can get some things right. As folks age, the view of what’s right and what’s a little off the beam differ.
Let’s look at the first write up called “How Larry Page’s Obsessions Became Google’s Business.” Note that if the link is dead, you may have to subscribe to the newspaper or hit the library in search of a dead tree copy. The New York Times have an on again and off again approach to the Google. It’s not that the reporters don’t ask the right questions. I think that the “real” journalists get distracted with the free mouse pads and folks like Tony Bennett crooning in the cafeteria to think about what the Google was, is, and has become.
The article points out:
Mr. Page is hardly the first Silicon Valley chief with a case of intellectual wanderlust, but unlike most of his peers, he has invested far beyond his company’s core business and in many ways has made it a reflection of his personal fascinations.
I then learned:
Another question he likes to ask: “Why can’t this be bigger?”
The suggestion that bigger is better is interesting. Stakeholders assume the “bigger” means more revenue and profit. Let’s hope.
Then this insight:
When Mr. Page does talk in public, he tends to focus on optimistic pronouncements about the future and Google’s desire to help humanity.
Optimism is good.
I then worked through “Google Alphabet and Four times the Research Budget of Darpa and Larger Moonshot Ambitions than Darpa.”
The bigger, I thought, may not be revenue. The bigger may be the budget of the science club. If Don and Bernie Jackson could build on the moon data, Google can too. Right?
Evidence Pay for Traffic Works
January 22, 2016
I read “Google Paid Apple $1 Billion to Be the Default Search on iOS.” If this is indeed accurate, there are some interesting notions one can derive from the number.
The write up states:
$1 billion. That’s how much Google paid Apple in 2014 to be the default search app on the iPhone, according to court transcripts obtained by Bloomberg. As you might imagine, neither company is too happy about their business deal being made public, and as the publication notes, the court transcript “vanished without a trace” late yesterday. But whether that was because the court in the ongoing litigation between Google and Oracle eventually bowed to the whims of Cupertino and Mountain View’s requests for redaction isn’t clear.
My thought is that search engine optimization is pretty much a waste of time. If SEO worked, the dear Alphabet Google thing would just use wonky tricks and move on. If a Web or mobile site wants traffic, pay for it. Buy Adwords. Simple.
But no.
The Google is paying for exposure to Apple fans and getting traffic. The traffic leads to goodies like ad revenue and data.
Does anyone care? Nah. Search means Google, and if one can’t find it on Google, the information does not exist as I understand the matter.
Stephen E Arnold, January 21, 2016
IBM and Severance: An Arbitrary Winter Chill
January 22, 2016
I read “IIBM Alters Severance Terms.” The idea is that an IBMer gets a review and learns that s/he is no longer needed. The reason may be incompetence; the reason may be downsizing; or the reason may be part of the IBM’s desire to outsource. Who knows? Saving money makes sense after 15 consecutive quarters of revenue decline and the massive spending to make Watson a household word, pay off Bob Dylan, and visit every possible media outlet with the tidings of gladness and joy about cognitive computing.
The write up points out:
Employees who took the IBM Separation Allowance Plan used to get 6 months pay. Now it’s one month.
That sounds fair. Some money may be better than zero money. The write up quotes the IBM explanation, which I find just thrilling for the employees soon to be affected by the change:
The separation allowance payment available under the Individual Separation Allowance Plan, regardless of the circumstance under which ISAP is offered, is one month of pay. For employees covered by IBM’s Growth Driven Profit-sharing program or on any type of sales or services incentive plan or any special program which is offered in lieu of the IBM Growth Driven Profit-sharing program, the one month of pay made under ISAP is paid in a lump sum, using the employee’s base pay amount (also known as reference salary) (full or part time). Any separation allowance payment under any of IBM’s plans is in lieu of any other form of separation pay to which the employee is, may, or might have become entitled. An individual separation allowance is not an automatic entitlement and will not accrue or be paid for reasons other than those listed above. No separation allowances under any of IBM’s plans will accrue if an employee has outstanding indebtedness to IBM or debts for which IBM may be responsible. However, if an employee makes arrangements satisfactory to IBM to repay any such outstanding debts, a separation allowance may be paid. Indebtedness to IBM could include, but is not limited to, a debit commission balance, an IBM US Mobility Plan equity loan, an unpaid balance on an installment purchase of an IBM product, credit card debt, excess tax loan, an outstanding travel expense account or failure to return IBM-owned property. In the event of rehire by IBM or any of its subsidiaries as a regular employee within 30 days after separation of employment with a payment under the Plan, IBM reserves the right to require repayment of the full ISAP payment.
Did IBM Watson assist in the writing of these statements? The conditionals add a bit of spice. Just what one needs as Joshua makes its way to IBM Federal Systems in Gaithersburg, Maryland.
Stephen E Arnold, January 22, 2016
Alphabet Google Android Revenue
January 22, 2016
I read “Google’s Android Generates $31 Billion Revenue, Oracle Says.” Who knows how accurate this “number” is, but I find it interesting because the “number” allegedly spins off $22 billion in profit.
My math is not too good. But I think it means that the Alphabet Google thing has more profit than costs when it comes to Android. Numbers north of 200 percent strike me as okay.
The write up asserts:
An analysis of the search engine giant’s tightly held financial information was disclosed Jan. 14 by an Oracle attorney in the database maker’s lawsuit accusing Google of using its Java software without paying for it to develop Android. Google said in a court filing that the lawyer based her statement on information derived from its confidential internal financial documents. “Look at the extraordinary magnitude of commerciality here,” the Oracle attorney, Annette Hurst, told a federal magistrate judge as she discussed Android revenue and profit, which have never been publicly disclosed.
I wonder if Oracle perceives that the use of its Java technology has contributed to this revenue.
I think so. The write up states:
The five-year-old showdown between Google and Oracle has returned to U.S. District Judge William Alsup in San Francisco after a pit stop at the U.S. Supreme Court, where Google lost a bid to derail the case. The damages Oracle now seeks may exceed $1 billion since it expanded its claims to cover newer Android versions.
There is nothing like a flock of legal eagles circling alleged revenue to signal that spring is not far away. Yandex is grousing a bit about Android. Gee, I wonder why.
Stephen E Arnold, January 22, 2016
Microsoft Cortana Update Draws Users to Bing
January 22, 2016
The article titled Microsoft Updates Windows 10 Cortana With New Search Tools for Better Results on IB Times heralds the first good news for Bing in ages. The updates Microsoft implemented provide tremendous search power to users and focused search through a selection of filters. Previously, Cortana would search in every direction, but the filters enable a more targeted search for, say, applications instead of web results. The article explains,
“It’s a small change, but one that shows Microsoft’s dedication to making the assistant as useful as possible. Cortana is powered by Bing, so any improvements to the Windows 10 assistant will encourage more consumers to use Microsoft’s search engine. Microsoft made a big bet when it chose to deeply integrate Bing into Windows 10, and there is signs that it’s paying off. After the June 2015 Windows 10 launch, Bing attained profitability for the first time in October 2015.”
That positive note for Bing is deeply hedged on the company’s ability to improve mobile search, which has continued to grow as a major search platform while desktop search actually peaked, according to research. Microsoft launched Cortana on Android and iOS, but it is yet to be seen whether this was sufficient action to keep up the Bing momentum.
Chelsea Kerwin, January 22, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Data Discrimination Is Real
January 22, 2016
One of the best things about data and numbers is that they do not lie…usually. According to Slate’s article, “FTC Report Details How Big Data Can Discriminate Against The Poor,” big data does a huge disservice to people of lower socioeconomic status by reinforcing existing negative patterns. The Federal Trade Commission (FTC), academics, and activists have expressed for some time that big data analytics.
“At its worst, big data can reinforce—and perhaps even amplify—existing disparities, partly because predictive technologies tend to recycle existing patterns instead of creating new openings. They can be especially dangerous when they inform decisions about people’s access to healthcare, credit, housing, and more. For instance, some data suggests that those who live close to their workplaces are likely to maintain their employment for longer. If companies decided to take that into account when hiring, it could be accidentally discriminatory because of the radicalized makeup of some neighborhoods.”
The FTC stresses that big data analytics has positive benefits as well. It can yield information that can create more job opportunities, transform health care delivery, give credit through “non-traditional methods, and more.
The way big data can avoid reinforcing these problems and even improve upon them is to include biases from the beginning. Large data sets can make these problems invisible or even harder to recognize. Companies can use prejudiced data to justify the actions they take and even weaken the effectiveness of consumer choice.
Data is supposed to be an objective tool, but the sources behind the data can be questionable. It becomes important for third parties and the companies themselves to investigate the data sources, run multiple tests, and confirm that the data is truly objective. Otherwise we will be dealing with social problems and more reinforced by bad data.
Whitney Grace, January 22, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Eel Catcher Presages Future of Doctors and Lawyers
January 21, 2016
I read a poignant article called “The Last Eel Catcher: 3,000-Yo UK Tradition Comes to an End.” The write up points out:
Britain’s last traditional eel catcher announced his decision to stop the ancient practice because he “can’t live on empty pockets.”
Yep, McDo’s chicken nuggets or a vegan smoothie are raking in the dough.
I thought of the last eel catcher when I read “Davos: Doctors and Lawyers Could Be Replaced by Robots.” The business and governmental elite are thinking big thoughts about technology. I learned:
Andrew Moore, Dean of the school of computer science at Carnegie Mellon University, said machines were already performing many “boring tasks of white collar work”, with computers able to sift through millions of legal documents to help lawyers prepare for cases. “One by one you are going to see that things we thought would require our own personal ingenuity can be automated,” he told a panel at the World Economic Forum in Davos, Switzerland.
I assume that’s why Goldman Sachs is jumping on the smart software bandwagon.
What will these displaced, highly paid, quite confident individuals do for a living. Eel catching is out. KFC is a possibility. I know that a few will light their entrepreneurial fires or drive an Uber car until autonomous vehicles make it big. The future could become more interesting for the docs and the legal eagles.
Stephen E Arnold, January 21, 2016
A How to Create Jargon Tutorial
January 21, 2016
I read “Controversial Concepts: How to Tackle Defining and Naming Them.” The write up explains how to whip up jargon and get it into circulation. I thought, “Just what I need. I want to make ideas more confusing and more difficult to discuss. Hooray.”
Here’s the method:
- Name controversial concepts with proxy names such as “Greg”, “Mike” or “John” (or whatever name you prefer) to get potentially misleading names and their implicit connotations out of the way of progress.
- Draw a concept diagram showing those concepts as well as important semantic relationships among them.
- Formulate intensional definitions for each concept – still using the proxy names. Ensure that those definitions are consistent with the relationships shown on the concept diagram.
- Identify one or more communities that “baptize” those concepts by giving them better names.
Not as clear as Lotus 1-2-3 because the “intensiional definitions” threw me. After a bit of thinking, I realized that I could create really useful, clear, high impact words and phrases like:
- artificial intelligence
- Big Data
- cognitive computing
- concept search
- data lake
- metadata
- natural language
That is outstanding.
Stephen E Arnold, January 21, 2016
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