The Coming Job Glut: Expanding Work in The High-Tech Sector (page 1 of 3)

By Ivan Handler
Chicago Third Wave Study Group

Introduction

I am a highly skilled, highly paid high-tech consultant. While I have been a progressive since 1960s, I have also been a computerphreak since 1963. I have grown up with this technology and have experienced its social impact firsthand--in humanity’s ongoing crises of internecine war, increasing joblessness, and deepening alienation and despair.

I have been engaged in the debates on these topics from the beginning. While I do not want to minimize these crises or the role of information technology in any way, I have often felt that these discussions were one-sided. I believe they frequently did not take into account the internal dynamics of the information technology sector itself and how these dynamics can inform progressive or revolutionary action.

This paper reflects my experiences from the inside of a large number of corporations, including many in the Fortune 500, which I have serviced over the last several decades. It responds to many of the "end of work" scenarios that have been circulating, along with some ideas on the implications of these perspectives for political action. For the sake of clarity, I focus on employment. But I am quite aware of the many other areas that have been adversely affected by information technology including war, civil liberties, criminal justice, education and economic speculation.

What the Traditional Left is Saying

The conventional wisdom on the left on technology and jobs goes something like this:

Disastrous unemployment and underemployment is being created by two factors, both stemming from the information technology explosion that started in the 1950s:

What is to be done to prevent this dismal outlook from becoming a reality?

“Saving Jobs at Home” (usually meaning in highly developed 1st world countries) is the first key battle. Some add that demanding adherence to human rights and ecological standards by employers is also critical. Some go even further to argue that saving jobs or the environment will not work by themselves. Instead the capitalist system must be destroyed to be replaced by a favorite flavor of socialism, and that in many cases even the demand to save jobs is “misleading” workers into accepting another round of phony reforms that will not benefit the working class.

Why the Traditional Left View is Incomplete

I do not want to argue that the above views are substantially wrong, even in the short run. Given the incredible increase of misery of all kinds in the last several decades, it is hard to argue, without severe qualifications, that the information technology revolution has benefited the majority of people on this planet. Instead, the problem with the typical left perspective is that it views technology from the outside looking in; it does not take into account the internal dynamics of the information revolution and both the promise and peril waiting there.

The first inkling that there is something missing in about the left perspective is the increasing shortage of high-tech workers. The New York Times, February 27 headlined an article “Atlanta Loses Jobs but Still Needs High-Tech Workers.” Around 5000 jobs were about to be lost from Lockheed Martin, BellSouth and Coca-Cola. The article goes on to say "If Atlanta's economy has run into a rough patch, it is not because there is a shortage of jobs. To the contrary, they say, there is a lack of people to fill them, particularly in technology(1).”

In fact, programmers, analysts, web designers, content specialists and project managers are in such demand that there is no hope of fulfilling all job openings any time soon. Congress is even moving to allow the importation of more skilled workers from Asia, Russia and Eastern Europe to work in the US. This is not just because they will work for lower wages (at least until they are granted permanent residency). It is because there are not enough native-born US citizens who are qualified or who are trying to become qualified to fill these positions.

A widely quoted Feb. 9, 2000 AP article by Bart Jansen states:

Let’s look at some of the current contributing factors:

The Low Road Option. Poor people are being channeled into low-level service jobs or prison rather than college and high-tech jobs. There is no rational reason for this except for the tradition of racism and class bias that so infuses the US and most other “advanced” nations. Our political life is warped by a “cycle of idiocy”: First, politicians exploit fear of crime among minorities and the poor to get elected. Next they put more poor and minorities in jail to “fulfill their promises to the electorate.” The prison population grows wildly even as crime goes down, leading to harsher conditions and fewer educational or training programs in prison. Released ex-offenders have even less chances at decent employment, and end up going back to prison. This adds to the fear of minorities and the poor, making it even easier to get elected by fear tactics, and so on….

Older Unemployed High-Tech Workers Are Being Ignored. While this is certainly happening to many, it is not clear how many are really being left out compared to the number of positions available. The other thing to keep in mind is that the high-tech world is unforgiving. You need to constantly be learning new skills and re-inventing yourself. If you fall off the train, it can be very difficult and expensive to get back on. Very few employers want to train older workers when they hire them.

The Bill Gates Model. More and more young people want to be the next Bill. In many cases they don’t finish college (just like Bill) or even high school before starting their own businesses. Business schools are even starting to feel the heat since they are the traditional stepping-stones to CEO-hood. Thus being a hard-grinding programmer or high-tech worker has lost its allure among many young Americans, even though someone has to come in and fill those empty spots or there will be no one to make the next Bill’s bills.

The Info-Gamblers. Another aspect of the information revolution is the incredible growth of speculative markets. Anyone can now become their own broker. Those that do not want to become Bill, want to make their millions by joining the hot action on Wall Street and similar institutions world wide. In short, productive labor is out, gambling is in.

The above circumstances are not inevitable or inherent to our society. There are any number of scenarios that could come about to ameliorate or change them. Whether or not you believe political and business leaders are smart enough or humane enough to see how to do it, the solutions are not that complicated.

But I want to argue a different point. It is certainly good to promote social policies that give more people productive skills, especially if they have been locked out of the economy. But I believe the more successful we are in producing skilled high-tech workers, the greater the shortage of high-tech workers will become. Again, this does not mean we should not attempt to bring people into well paying high-tech jobs; but it does mean that we will have to radically readjust our thinking about the future of economics.

Information and Automation

cy.Rev has long argued that the fundamental commodity of this new economy is not goods and services or even money, it is information. This new economic system is based on the ever-expanding production of information. Improvements in the quality and quantity of goods and services are, in most cases, a side effect or by product of information production. That is the true meaning of automation.

In an industrial economy, there are relatively long cycles involved in producing new products for the market or even for internal use. Production involved many steps, a large portion of them involving relations with suppliers who were outside the control of the corporation needing what they supplied. One of the reasons automation has come into existence is to shorten those cycles.

The production of information, on the other hand, can follow very short cycles. In an automated process every interaction in the production cycle is usually audited at some level. This mean that even in the early design stage of a new product, information is being produced in large volumes. In many cases the raw information produced contains too many details, so it is further processed into reports, which in turn are presented to the people who manage the process. Then the results of a large number of these reports may get aggregated into other reports and so on.

In order to continue to shorten production cycles and speed up time to market, corporations are racing to make a process more efficient by integrating more and more of the components of the production cycle into a single unified information structure. This means that the people who work in these cycles have more access to information than they have had in the past.

A manufacturing engineer, for example, may gain access through an Enterprise Resource Planner (ERP to the cognoscenti). The ERP contains a diagram of a large device (say a jet engine) where every component part is linked to a database that is constantly refreshed with all of the inventory information known for that component. The engineer may then have the system automatically poll an Internet site for the best deal to be had on that part. The part can be ordered on the spot, with a purchase order immediately sent to the chosen supplier. This process also includes regular updates on when the part is to be delivered, by which carrier, with the appropriate bill of lading identifiers automatically sent back to the initiating ERP system, which then can keep the engineer and management team appraised of the status of the part order. The system can even be set to notify the engineer with an email if the expected arrival date changes for any reason.

Things can get even more complicated. The engineer may need to do research on the suppliers to make sure the one chosen will supply parts that are high quality. This can mean sifting through journals and calling contacts at other firms. Nowadays it is more likely using a search engine on the Internet or on the local document management system (if the corporation has been saving articles on suppliers in its document management system). Then issues may arise about which kinds of parts can be assembled by the robots that were just installed on the assembly line. More searches and telephone calls proceed from here. If the engineer makes any mistakes, it could seriously impact production and loose millions of dollars.

So the engineer may start to rely on special software. Or he or she may look to Internet sites focused on jet engine production that can furnish answers quickly and reliably. While it costs money for the software or to use the Internet site, it also reduces the time it takes to make a decision and does not increase the number of people in the engineer’s department. The point is that the management of information is becoming the primary factor determining how things are done or not done in this new economy. Better information management means more efficiency and (leaving aside market speculation) more profits.

Unfortunately, information management comes with its own set of special circumstances. It involves several components: collection, classification, storage and retrieval.

Collection is the process of gathering the data from its source and preparing it for entry into an electronic repository.

Classification is where other descriptive data is added to the source data to make it easier to find later on. Classification can happen before, during or after collection(3).

Storage means placing the data in electronic media for future retrieval. Storage involves worrying about how quickly the data needs to be retrieved, how much redundancy is needed to insure reliability and whether or not to store the data centrally or in a geographically dispersed system.

Retrieval is a collection of processes where a user can request information based on any number of identifiers from unique identifiers such as a product id to non-unique identifiers, such as keywords or concepts. More >>