“Workforce Crisis” Published 1992

“Workforce Crisis” witten by Dychtwald, Erickson and Morrison and published in 1992 suggested

That the massive boomer generation was beginning to retire and coupled with declining birth rates leading to less younger workers, would lead to a brain drain. 

Was “Workforce Crisis” correct?  What is your experience today?  Is finding talent more difficult and perhaps more expensive than ever?  Are valuable projects and other initiatives being delayed for lack of qualified staff?  What strategies are you encouraging today in 2017 to be ready for the next wave of economic growth that may already be happening?

The Authors provided some advice in 1992 that maybe still valuable today.  Read on…

(1)    What skills will you be needing?

(2)    When will retirements hit?

(3)    Why do your employees stay or leave?

(4)    What are your sources for talent?

(5)    What academic feeder programs are you developing?


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Winds of change at MicroSoft-Azure

The winds of change are blowing at Microsoft, and rarely so clearly as in the company’s product lines for software developers.

Just about a year ago, Microsoft paid around $400 million for Xamarin, a startup that lets programmers write their code once and easily turn it into an app for PCs, Macs, Android, iPhone, and almost anything else. And Xamarin feeds right into that strategy, says de Icaza of MicroSoft. “It turns out that Xamarin developers have an affinity for [Microsoft] Azure [cloud] services,” he says. If you use Xamarin to build an app, you’re more likely to use Azure to power it on the backend, too. 

Pre-acquisition, Xamarin already had a sizable customer base. Now, even Microsoft’s big business customers are getting in on the action. Many of them already use Visual Studio to do their programming, so the addition of Xamarin greatly simplifies their process of making apps for multiple operating systems. 

“We are getting lots of requests from companies that want to build on Xamarin,” says Liuson (MicroSoft). In fact, she says, British Airways is using it to build all of their apps for multiple operating systems, letting them have one core programming team rather than one for each platform.

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By now have you heard the A.I. buzz?

By now we have all heard the buzz. Siri has plenty of company. Alexa and Google have invaded the home. Tesla’s artificial intelligence is, well, driving itself. Google’s Deep Mind is running the company’s multi-billion-dollar search business. Even they don’t know how it works — it just does. IBM’s Watson has its own office and is predicting cancer treatments for real patients. You can’t even date online without artificial intelligence (A.I.) hooking you up.

There are even A.I.-based autonomous ships, bots, games and investment and commerce platforms that are emerging. Eventually A.I. will be everywhere. Are you ready for the A.I. revolution? Of course, the answer is no one is ready, because this is only A.I. 1.0 — the beginning of time. So let’s review.

Artificial intelligence has finally emerged, and the prospects for it transforming the enterprise are excellent. Every enterprise should be looking at what blend of A.I. they want to investigate. From machine learning to neural nets, recommendation engines and decision bots — the landscape of the marketplace is full of choices. The real question I would pose is, “What should CIOs be telling their CEOs about the A.I. revolution?” The answer: “Show me the business strategy.”

I would challenge CIOs to work out the strategy question first. What is the business strategy that would benefit and even justify adding artificial intelligence? How could we generate a competitive advantage from investing in machine learning or automated decision support that A.I. could offer? There needs to be a business value or competitive advantage that investing in A.I. makes clear. If not, then you are not ready. Or don’t invest much until you can answer this strategic question.

Too many companies are so impressed with A.I. buzz that they are moving headlong into A.I. without clarifying what the business strategy case could be. Are we going to be able to generate better customer service? Help employees make better decisions? Enable our customer to use more of our products or services? How about fix that problem that those pesky humans don’t seem to be able to handle? How will we be able to monetize artificial intelligence?

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AI vs Trust…First Impressions!

AI and trust and respect – first impressions matter!
We are hardwired for judgment. Our paths up from the primordial soup have imbued in us the spirit of quick conclusions, especially when it comes to one another. As Harvard Business School psychologist Amy Cuddy puts it, we size each other up along two key questions: Can I respect this person? Can I trust this person?

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AI WORLD TRENDS-Westboro, MA-September 18, 2017

Westboro, MA – February 13, 2017 – Trends Equity, Inc. has announced that AI World Conference & Expo 2017www.aiworld.com – will be held September 18-20, 2017 at the Boston Marriott Copley in Boston, MA. Now in its’ second year, AI World has become the industry’s largest event focused on the state of the practice of enterprise AI and machine learning. AI World’s mission is to enable enterprise business and technology executives to learn how to successfully harness intelligent technologies to build competitive advantage, drive new business opportunities and accelerate innovation efforts.

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Machines Taking Over (Forbes)

The machines haven’t taken over. Not yet at least. However, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioral algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intellgience in use today.
However, the technology is still in its infancy. What many companies are calling A.I. today, aren’t necessarily so. As a software engineer, I can claim that any piece of software has A.I. due to an algorithm that responds based on pre-defined multi-faceted input or user behavior. That isn’t necessarily A.I.
A true artificially-intelligent system is one that can learn on its own. We’re talking about neural networks from the likes of Google’s DeepMind, which can make connections and reach meanings without relying on pre-defined behavioral algorithms. True A.I. can improve on past iterations, getting smarter and more aware, allowing it to enhance its capabilities and its knowledge.

H-1B _Problems

Congress set up the H-1B program to help American companies hire foreigners with exceptional skills, to fill open jobs and to help their businesses grow.
But the program has been failing many American employers who cannot get visas for foreigners with the special skills they need.
Instead, the outsourcing firms are increasingly dominating the program, federal records show. In recent years, they have obtained many thousands of the visas — which are limited to 85,000 a year — by learning to game the H-1B system without breaking the rules, researchers and lawyers said.
In some years, an American employer could snag one of these coveted visas almost anytime. But recently, with the economy picking up, the outsourcing companies have sent in tens of thousands of visa requests right after the application window opens on April 1. Employers who apply after a week are out of luck.
“The H-1B program is critical as a way for employers to fill skill gaps and for really talented people to come to the United States,” said Ronil Hira, a professor at Howard University who studies visa programs. “But the outsourcing companies are squeezing out legitimate users of the program,” he said. “The H-1Bs are actually pushing jobs offshore.”

#H-1B  #Visas  #Students

Data and Analytics-What Pros say!

FROM THE HBR.ORG INSIGHT CENTER “FROM DATA TO ACTION” | 2© 2014 Harvard Business Publishing. All rights reserved.
If you’re a manager working with the analysts in your organization to make more data-driven business decisions, asking good questions should be one of your top priorities. Many managers fear that asking questions will make them appear unintelligent about quantitative matters. However, if you ask the right kinds of questions, you can both appear knowledgeable and advance the likelihood of a good decision outcome. In my new book (co-authored with Jinho Kim) Keeping Up with the Quants, and in a related article in this month’s HBR, we list a lot of possible questions for various stages of analysis. But in this short article, I thought it might be useful to mention not only a couple of the most important questions you can ask about data, but also what some of the ensuing dialogue might involve.
1. Questions about assumptions You ask: What are the assumptions behind the model you built? You think in response to the answer: If your numbers person says there are no particular assumptions, you should worry—because every model has assumptions behind it. It may be only that you’re assuming that the sample represents a population, or that the data gathered at a previous time are still representative of the current time. Follow-up: Is there any reason to believe that those assumptions are no longer valid? You think in response: You are really looking only for a thoughtful response here. The only way to know for sure about whether assumptions still hold is to do a different analysis on newly gathered data— which could be very expensive. Perhaps a particular relationship holds only when the values of a variable are moving in a particular direction (e.g., “This mortgage risk model holds true only when housing prices are going up”—nah, that could never change!).

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First there was BIG DATA and now a LAKE!

For all IT Professionals who talk and wonder about BIG DATA…Consider what a DATA LAKE is all about! A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. While a hierarchical data warehouse stores data in files or folders, a data lake uses a flat architecture to store data. Each data element in a lake is assigned a unique identifier and tagged with a set of extended metadata tags. When a business question arises, the data lake can be queried for relevant data, and that smaller set  answer the question.

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Best Companies to work for…SAP Users

As Recruiters we are always asked about who are the best companies…And so I just found an announcement that might be helpful for those candidates looking for career opportunities in The Utilities Industry…SAP AG has just published it’s list of award winning Utilities for 2013.  The list includes First Energy, Atmos Energy, Puget Sound Energy, and Centerpoint Energy.  SAP AG says that these are the best-run Utilities because they have implemented innovative and sustainable practices based on SAP Software.