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Business
Productivity Gains
Using management,
technology, and knowledge assets
Controversy has swirled around the extent to which computers and information technology have enhanced productivity. In the late '80s, some economists questioned whether the computer revolution had created any gains at all. Such gains could not be detected in the USA federal government's standard measures of productivity because there weren't any, the economists concluded. But a cardinal rule for economists studying government data--or any other data--is, don’t forget what you already know. We see the evidence of productivity from computers all around us. Computers have already revolutionized the way we do our banking. I'm not talking about the small percentage of us pushing the envelope by paying bills from our home PCs. I'm talking about the vast majority of us, many of whom still can't tell a modem from Monitor, who use computers every time we use an automated teller machine; because the ATM is open morning, noon, and night, we no longer have to run to the bank during lunch hour. Computers also have allowed a huge percent of professionals to skip a step in writing memos, reports, and letters: having a secretary retypes it. As a result, employers have been able to cut many secretaries from their workforces; these secretaries then go and find work elsewhere or different work at the same companies. If these productivity gains don't show up in government data, then maybe there's something wrong with the data. And there definitely is something wrong, as we'll see shortly. Another thing economists know comes from economic theory, which tells us that people don't voluntarily invest millions of dollars in capital without expecting at least the same number of dollars in benefits from that capital. Managers and investors can make mistakes and over invest in certain items, but when they do, the market teaches them not to do it again. So when companies and individuals spend hundreds of billions of dollars per year on computers and software, year in and year out, that in itself is strong evidence that the investments are worthwhile. The economic analyst's job is to probe further and determine how. Government logic Neither. The Commerce Department's august Bureau of Economic Analysis measures output of banking by the number of people employed in banking. This means that if the number of banking employees rises by 10 percent, then the government's data analysts simply assume that output rises by 10 percent. Therefore, the banking industry's productivity growth is zero, not by observation, but by definition. Of course, productivity in banking is growing. According to surveys by the Bank Administration Institute, the number of checks processed per hour, a measure of bank workers' productivity rose from 265 items in 1971 to 825 in 1986, a rate of increase of 7.6 percent annually. Presumably computers were a factor in this productivity growth. And as noted by Martin Baily, an economist at the Brookings Institution, and Robert J. Gordon, an economist at Northwestern University, the per-check processing costs for Electronic Funds Transfers (EFTs), which were made possible by the information technology revolution, are a fraction of the cost of conventional check processing. EFTs still constitute only a small percentage of transactions, but as this segment grows, productivity will increase. Even where the USA federal government's data shows an improvement in productivity, it often understates the improvement. The computer revolution has dramatically increased convenience in banking, in pumping gas, and in buying groceries. Between 1990 and 1994, the number of point-of-sale terminals at grocery stores rose from 21,500 to 187,400, and the number at gasoline stations rose from 18,700 to 85,900. The time you save at the supermarket by paying with a credit card instead of a check, or because the Universal Product Code allows the items to be read into the cash register faster, should count as an increase in productivity. But the government data counts only the employee's time saved, not the customer's. The customer comes last Even in the manufacturing industries, where output is more easily defined, the government's data underestimates the growth in output. Take the auto industry, where the data shows that hourly output grew by a healthy average of 2.4 percent a year between 1975 and 1992. To measure that industry's output, the federal government divides the dollar value of output by the price of the output. However, cars need fewer repairs, last longer, and conserve gasoline better than they used to, and much of this improvement can be traced to computer technology. But the price indexes used to compute the auto industry's output do not adequately adjust for this. Result: the increase in labour productivity in the auto industry, large as it appears, is actually larger. Other evidence for the productivity-enhancing role of computers comes from wages. Princeton University economist Alan B. Krueger found that workers who use computers on the job earn wages 10 to 15 percent higher than those of workers who don't. With various statistical tests, he found that the wage differential could not be attributed to the PC users' being better workers in any other respect. Interestingly, he noted that the most highly rewarded task for which employees used computers was email, and that, all other things being equal, those who played games on their PCs earned slightly lower wages. Mr. Krueger also presented some even blunter evidence from a survey of placement firms. For the 83 firms that responded to his 1991 survey, the average hourly rate for a secretary with computer skills was $12.77, versus $9.14 for one without such skills. If computers aren't productive, why pay someone with computer skills more? Agriculture Mr. Avery also points out that computers are revolutionizing farm management. Until very recently, he notes, farmers could not know with much accuracy how wet their land was and, therefore, how much to irrigate. Even if they could test land in one part of a field, the results would not necessarily apply to other areas. But computers have changed all that. Subsoil electronic sensors set all over the field will tell a computer on an hourly basis how much water is in the root zone of a particular crop as well as how much should be there. Concludes Mr. Avery, "We'll do irrigation better than we've ever done it before." There's more. The computer revolution has led to the coining of a new term in agriculture: precision farming. U.S. farmers can now use GPS to do intensive soil sampling yard by yard across a field, then follow up using yield monitors on the harvesting equipment that tell what each square yard produced. The goal is to determine and apply the exact amount of water, pesticides, and fertilizer the crops need and no more. With runoff and buildup of excess fertilizer and pesticides minimized, says Mr. Avery, the crops can yield their full potential with almost no environmental side effects. The revolution is happening very fast; in the last two years, virtually all newly manufactured harvesting machinery has come with a yield monitor. Case IH, the second-largest farm machinery manufacturer in the United States, is now in the precision-farming advice business, marketing software and consulting services. Precision farming has already spread to Brazil and Argentina and will spread globally, predicts Mr. Avery. Moore’s Law Today, someone who was willing to give up a job with tenure might impress us, but the idea of buying one's own computer to handle large data sets would be simply a detail. In the overall scheme, the cost of a PC with the same capabilities as a late-'70s mainframe would be a rounding error. Northwestern University economist Robert J. Gordon has estimated that the quality-adjusted price of computers dropped about 19.8 percent each year between 1951 and 1984. Since then, he estimates, prices have dropped by about 25 to 30 percent per year. True, prices of many goods drop equally quickly for the first few years after they're introduced. But a double-digit annual decline in the price of a good for a period of more than 40 years is, as far as I know, historically unprecedented. This means that, for a computer of comparable quality, the price today would be less than 1/10,000 of its price in 1951. To put that in perspective, a given amount of computer capability that cost $100,000 in 1951 would cost about $3 today. Computers' low prices mean that many people who previously worked as employees can run their own businesses, something they couldn't have done in computer-intensive industries 20 years ago. Between 1980 and 1992, according to the U.S. Statistical Abstract, the number of employees in firms with fewer than 20 employees increased by 29 percent, compared with a 24 percent increase in employees overall. Admittedly, the difference is smaller than I would have expected. But what the data leaves out is the number of self-employed people, many of whom now work out of their homes. Big Brother But a delicious irony is emerging that Orwell never conceived of: the computer revolution allows citizens to monitor, prod, and undercut the government. We can say, with only slight exaggeration, that we are using technology to control Big Brother. In February 1994, for example, when a few home-students learned of a provision in a bill before Congress that would have required parents to be certified before teaching their children, they used phones, faxes, and email to alert their allies. In just over a week, members of Congress received more than 1 million calls telling them to back off. They quickly did. "We have had enough democracy for a while," said one exhausted congressional aide. Similarly, in September 1994, when Congress added a provision to a lobbying bill that would have imposed tough restrictions on grassroots groups, a few members of such groups found out about it. Mainly via faxes, they alerted sympathizers--hosts of talk shows, trade associations, and other leaders around the country. The next week, the bill--which, in a previous version, had passed the House by a vote of 315 to 100 and the Senate by 95 to 4--was filibustered to death in the Senate. The computer revolution is allowing opponents of greater government control to learn of Big Brother's plans more quickly and to threaten Big Brother's little siblings. Wheres the money Computers have increased productivity, made it easier to start your own business, and made it harder for government to control you. They will do more of all three in the near future. Not bad for a product for which a former IBM chairman predicted worldwide demand of only five. It's
a simple matter of economics. I remember a story of a person named Lou and Dr. W. Edward Demming. This true story was used to illustrate that technology is not the only means to productivity gains. And the story is as follows: Lou, runs one of the biggest used record stores in the country once had the ear of W.E. Demming, the economist whose theories transformed business in the 1970 through to the 1990. They were sitting at a bar together, and Lou asked Demming (a very old man at this point) how he could expand his record store sales. Demming shook his head indulgently. He sighed and took a bar napkin and drew a pie chart. "You retail guys, you always think in pie charts, right?" Demming drew a little wedge in his pie chart. "Ok. Here's your percentage of sales in your market. Now you ask me - " and here Demming edged the pie-wedge's parameters a little to the left, then a little to the right, creating a slightly bigger slice of the pie - "how can I get a little more out of my market?" Then he raised his finger. "You want to know how to increase your sales?" Lou was all ears and nodded vigorously. This was the master, after all. "You make a bigger pie." Demming drew a circle around the pie on the bar napkin, and expanded the wedge outward to take in its share of the new circumference. Lou followed Deming's advice: He redefined his market. He started by renting a booth at farmer's markets, selling his records along side bushels of squash and apples. He looked into recording bands he loved. He started looking for new ways to get new customers, and he stopped thinking of his operation as merely a retail record store. A History Lesson on Total Quality Management In the late 1970's to mid-1980's U. S. companies were seeking ways to survive in an environment of back-to-back recessions; deregulation; a growing trade deficit; low productivity; downsizing; and an increase in consumer awareness and sophistication. Ford Motor Company had operating losses of 3.3 billion between 1980 and 1982. Xerox, which had pioneered the paper copier, saw its U.S. market share drop from 93% in 1971 to 40% in 1981. Attention to quality was seen as a way to combat the competition.
Many of the TQM concepts originated with the work of Dr. W. Edwards Deming, the American statistician, who guided the Japanese industry's recovery after World War II and who formed many of his ideas during World War II when he taught American industries how to use statistical methods to improve the quality of military products. While the Japanese listened to Deming American industry did not. For nearly two decades, before and after World War II, American businesses were preeminent. In this period of little foreign competition, American management methods were unchallenged and in hindsight, costly practices of traditional hierarchy took hold. Meanwhile, industrial leaders in Japan burdened with a reputation for poor quality, invited Dr. Deming to teach them his methods. Deming urged them to find out what their customers wanted, then study and improve the design and production processes until the quality of their product was unsurpassed. He urged a new style of management that shifts the focus from profits to quality. He reasoned that employees could learn how to monitor, control and continually improve their work processes and systems with the application of a scientific approach. With the collective attention of people to their work processes and their interdependency, they are better able to produce products that meet customer expectations. With total quality control (TQM), decisions are based on data gathered with scientific tools and approaches. Products and services are improved by improving how the work gets done (the methods) instead of what is done (the results). Deming pointed out what he saw as flaws in the traditional model of "management by objectives" which emphasizes a chain of command in which objectives are translated into work standards or quotas. He cautioned that with MBO the performance of employees is guided and evaluated according to numerical goals. As a result, workers, managers and supervisors get caught up in protecting themselves. Looking good overshadows a concern for the customer or the organization's long-term success. Employees, desperate to meet quotas, lose sight of the larger purpose of work. A common example is when sales people are pushed to boost business and make promises production can't keep. With the change in focus, the roles of workers and managers are reformed. A manager's role is to enable employees to do the best job possible foreseeing and eliminating barriers that get in the way. Workers learn to apply the expertise they have gained working with processes and customers on a daily basis Deming predicted the Japanese adoption of these methods would put their products in demand throughout the world in five years. He was wrong; within four years the Japanese had gained large shares of some markets. Paradigms The emerging quality movement in the United States represents significant paradigm shifts in company cultures and business operations. Typically, the culture of the United States is characterized by the paradigm of "rugged individualism". USA history reflects the contribution of many revered individuals. This model of the world sees people as both the source of and resolution of problems. In this paradigm, solutions to problems might be seen as fixing people (i.e., training employees to improve their attitudes). In this view, the survival of a company may rest in calling upon the right "star performer", like Lee Iacocca. Whereas quality control emphasizes that organization survival is contingent upon the effectiveness of the systems of the organization. In quality management there is a rule of thumb called the 85/15 Rule which suggests the root causes of 85% of organizational problems is faulty systems and that few problems are the result of the behaviors of employees. This philosophy may meet opposition in many companies where the current policies, procedures and systems are more traditional. That is holding each individual accountable instead of viewing the systems in which they work as the producer of quality. It follows that the traditional management practices of managing-by-objectives (MBO) with a hierarchy of objectives and standards that are passed down in the organization from the top, is another paradigm. The quality philosophy with a shift in focus from internal results to customer expectations is another view of the business world. Leaders will not turn quality into a competitive advantage if they behave as if TQM is a simple technique that can be bought and introduced within a traditional management framework. Vansina cautions us that installing an elabourate quality assurance system will not lead to employee commitment to quality. Such efforts are based on the assumption that processes and tasks that lead to the desired quality are already understood. A consequence may be employees feeling pushed into compliance without understanding the criteria or challenging their effectiveness. Importantly, expectations and market demands change, as do the technology, materials and/or knowledge utilized. In light of the above, the impact of the traditional paradigms on current policies, procedures, and systems in organizations is likely strong. Implementing Employee Involvement (E.I.), systems will require commitment from top management as well as from all employees. That commitment may often involve a change in attitudes. It will also involve the management of change in the organization. Guiding the change process requires an understanding of the present organizational cultures, attitudes, structures and systems. TQM PhilosophyThe TQM philosophy of management is customer-oriented. All members of a total quality management (control) organization strive to systematically manage the improvement of the organization through the ongoing participation of all employees in problem solving efforts across functional and hierarchical boundaries. TQM incorporates the concepts of product quality, process control, quality assurance, and quality improvement. Consequently, it is the control of all transformation processes of an organization to better satisfy customer needs in the most economical way. Total quality management is based on internal or self-control, which is embedded in each unit of the work system (technology and people). Pushing problem solving and decision-making down in the organization allows people who do the work to both measure and take corrective action in order to deliver a product or service that meets the needs of their customer. Managers and experts disagree about how to effectively apply TQM to their organizations. Some advise that customer satisfaction is the driving force behind quality improvement; others suggest internal productivity or cost improvement programs achieve quality management. In other applications, TQM is considered a means to introduce participative management. The Japanese, in general, concentrate on customer satisfaction with a focus on understanding customer needs and expectations. Until very recently Americans in general have emphasized the "cost of non-conference", and the importance of employees meeting the agreed upon requirements for each process. Leopold Vansina, president and founder of the International Institute of Organizational and Social Development, cautions that such efforts are based on the (faulty) assumption that processes and tasks that lead to the desired quality are already understood. However, he states, control of the production process will not likely help a business increase its market share when the product or service does not meet customer requirements. Quality Improvement vs. Quality Assurance It is important to avoid equating quality improvement with
quality assurance. Quality assurance is a system of activities designed to
ensure production that meets pre-established requirements. It gives the
customer a guarantee of quality by measuring product conformance with process
and performance specifications. Quality improvement refers to all efforts
directed to increase effectiveness and efficiency in meeting accepted
customer expectations. It is a continuous process to achieve a better
understanding of the market; to innovate products and processes; to manage
and distribute material and products; and to provide service to customers.
The success of quality improvement is based on the understanding of every
member of the organization concerning the needs of their customers (internal
and external). Maintenance of that understanding requires continuing dialogue
and negotiation with the customer and measurement of one's products and
services against the customer expectations. Productivity of Knowledge
Virtually every business in the world faces
the same fundamental problem: Maintenance of their competitive edge through
the application and formation of knowledge. The plain truth is that, in many
companies, much of the operating knowledge is undocumented; this undocumented
knowledge can easily be lost through retirement or attrition. In the
technology field, it's much worse. Knowledge workers with key competitive and
often proprietary knowledge are literally stolen away by competitors. And,
without the ability to organize, store, retrieve and manage it, much hard-won
knowledge leaves with them. Some companies are using stock options to hold
key employees. That's a good idea, but what about those who hold undocumented
knowledge but are essentially invisible to the system? In many companies,
much of the organizational "know-how" exists in the minds and
private notebooks of workers, programmers and managers. Management of
corporate knowledge assets should be as commonplace as the management of
information is today. Meanwhile, valuable knowledge assets are irretrievably
lost, running like quicksilver through the personnel office. An example of
this hidden, or tacit knowledge may prove instructive. While working at a
large expatriate automotive company recently, I was assigned a project in the
production department of their motorcycle plant. Management was preparing to
fire a fifty-something female production control supervisor named Carrie
because of constant tardiness. She was an unattractive, poorly educated, high
school drop out with bad grammar and a strong Ohio twang – no stock options
for Carrie. Although my discussions had nothing to do
with her problem, I determined, after several interviews, that she was the
only one in the facility who really understood the plant's computerized
production control system. The production control system was a rather complex
and idiosyncratic program, which had originated in Japan, and had few
knowledgeable advocates in this plant. It ran well and did the job only
because Carrie knew it backwards and forwards. In fact, she taught the
program’s functions to new production managers. Firing her would have created
a manufacturing nightmare, with bottlenecks, lost orders, and an emergency
call to Japan for several engineers. No one knew Carrie was the only
repository of this knowledge. Plant production managers assumed that she was
only one of many production control people who had this knowledge. They were
wrong. "Knowledge is the key to Human Capital" In Knowledge management there are two
goals. They are: (1)
To postulate
that the value of knowledge as a component of human performance is, in fact,
a tangible corporate asset; and (2)
To begin a
dialog with the both the financial and business communities regarding the
inclusion of the "knowledge asset" as the value-bearing part of
Human Capital. Today,
knowledge is considered a key strategic asset for many corporations. It is
our competitive edge and gives us the advantage in almost any business
situation. Yet, it is one of the least understood of all corporate attributes
Knowledge, its representation within the corporation, its value and
management. As we all know, human capital still has no
formal place on the balance sheet. Consequently, Knowledge, lacking formal
recognition by the accounting system, often receives less attention than it
deserves the path to establishing the institutional value of knowledge and
its corollary, human capital, is well worn. And, as the economist Robert
Reich said, "The burden of proof is on you." Dr. Reich, that the
time is ripe for a new sojourn into this dismal realm, in part because of
this time of unprecedented intellectual expansion when ideas, like new
application software, create capital from the mind rather than from the
system. Perhaps it is time to re-asses the rules of the game. Unlike capital
formation, knowledge formation is totally egalitarian and springs from all
sectors of our commercial society. What is corporate knowledge? How is it
applied and how is it valued? For years managers have said, “If you can't
measure it, you can't manage it.” Can we, then, measure knowledge? And, if
not, how can we possibly manage it? Some people are said to be
"knowledgeable," and others are not. Who knows? And, how do we
decide? In fact, in industry, we have no objective means to measure
knowledge. We do not identify knowledge except in highly subjective terms.
Much of what we call knowledge is really information. Usually we treat
knowledge as if it were some benevolent genie that, if we fondle, feed, and
sometimes bribe, will make us the beneficiary of its largess. The simple fact
is that the qualitative and quantitative management of knowledge is essential
if we are to survive in the global marketplace. Knowledge is our competitive
edge. Knowledge is the one factor, which delivers value to the corporation,
but is not officially recognized on the balance sheet. Currently, one cannot
formally impute worth to knowledge in financial terms, other than as some
vague and unspecified contribution to profit. However, since Knowledge is
truly the coin of Human and Intellectual Capital, it is fundamental that we
are able to both identify and quantify it. The much referenced, ill-defined
Knowledge Asset has no clear objective definition, except to imply that it
contributes in some way to the value of the company. In truth, knowledge is
the asset-bearing component of Human Capital. Knowledge and the “Knowledge
Asset” are essential to the demonstration of the value of people in our
business model. Our inability to value people is one reason for the almost
universal undervaluing of Human Resources, demonstrated, for example, by the
consistent under funding of corporate training. Any discussion of knowledge
in business should first differentiate between information and knowledge.
Although the dictionary would have us believe otherwise, knowledge and
information are not synonymous. Dr. W. Edwards Demming said knowledge is
information in action. It is our belief that Knowledge is a distinctly human
attribute. The following is an operational definition used for the special
purposes of this lecture. First, information. Information exists
external to the human mind. Information does not become knowledge until
intelligence, integration, judgment, synthesis and a host of other human
attributes are applied to it. Information is then transformed into knowledge
by the human mind. Information is useless unless we can act upon it, and that
implies that it must first be transformed into knowledge. Once integrated
into the existing knowledge framework of the individual, information becomes
actionable knowledge. In most cases, information cannot readily be transformed
on-the- fly. It cannot simply be passed like a spreadsheet, from one person
to another. An example here may prove illustrative. If the spreadsheet is
merely next months operating budget, then a few simple questions should
permit me to derive knowledge from it. However, if we have a complex product
forecast employing regression analysis and pivot tables, a bit more
explanation and indeed some training may be required before I can transform
the information in this spreadsheet into knowledge. The individual,
especially when dealing with complex processes, must transform information by
integrating it into their existing knowledge base. This transformation
process, then, is the called education and/or training. The knowledge asset
combines a number of factors, which can be objectively proven by the
observation and accomplishment of a specific set of criteria. Accomplishment
is represented by the realization of a discrete set of behaviors, called
tasks, which, when employed by an individual, or group, results in a
measurable outcome that adds value to the corporation. The Criteria for Proof of a Knowledge Asset There are four conditions are required to
verify the existence of a knowledge asset. These conditions, or criteria,
are: · Creation of a set
of graphical procedure guides which will permit a nominally trained worker to
perform the task, or tasks, independently and without further assistance. · Observation of correct job performance, which is proof of
accomplishment. · Quantification of the value of the accomplishment, as represented by
an economic measure. · Verification by an independent, certified assessor. Note: This differs from ISO-9000 in that our written procedures must be employed and observed to be valid, not just documented. Secondly, the accomplishment of the tasks must have measurable, documented economic value. These conditions must be achieved and objectively monitored by a trained, independent auditor before a knowledge asset can be declared. And, to clarify the status of the auditor, that individual must be independent of the group performing the activities to be assessed, not necessarily independent of the company in which the activities occur. In our current financial measurement and
valuation model, an asset is typically a tangible object, which, through
appreciation or depreciation, accrues value to the corporation. A Patent, or
Copyright, is an example of an intangible asset that is considered
intellectual capital. We believe that this does not go far enough in documenting
the knowledge assets of the corporation. The Patent also provides us with an
objective precedent for the use of knowledge as a tangible asset. We propose
to add the “Knowledge Asset” as another representation of value and objective
proof of Human Capital. We intend to make this argument (here and in other
venues) to Government and Business institutions that are tasked with such
assessments. The Knowledge Asset is the tangible representation of the
corporations "know-how," and is prima facie proof of corporate
competence. It represents the competence of the corporation. The sum totals
of these knowledge assets are the Human and Intellectual Capital of the
company. One of the major reasons for the failure of newly acquired
businesses is that the purchaser does not recognize that its intellectual
capital is at risk, since it resides in a limited number of employees.
Whether disaffected as a result of the buy-out, new management, a move, or
some other reason, the loss of these key knowledge assets (both the
individuals and the knowledge they represent) could render the corporation
incapable of performing. It is fundamentally true that the ability to operate
effectively is not sufficiently demonstrated by Patents or Copyrights.
Ownership of a patent is not objective proof that the company can
effectively, or efficiently, produce the product, just as owning the
copyright to a symphony does not assure that musicians can play it. In part,
the knowledge asset is to the patent what the musical score is when translated
into specific music by the musicians. To extend the metaphor, it is a
combination of the score and the competent performance of the music. Finally,
there must be economic value. It is fundamental that the proof of the
knowledge asset lies neither in the ownership of the patent or the value of
the accomplishment of production. The proof is not merely physical, but in
the combined elements of human knowledge assets, and their contribution to
the value of the product, or service, delivered to the customer. This is a
knowledge asset; this is the value of Human Capital. Unless we can include
the knowledge asset and human capital on the balance sheet to offset
investment (as we do with other corporate assets), our ability to justify
investment in building or retooling our knowledge infrastructure and Human
Capital will always be problematic. Unless formally recognized by the
Financial Accounting Standards Board (FASB), and reflected in the Generally
Accepted Accounting Principles (GAAP), the financial and accounting systems
will continue to work against such mission critical investments. The situation, is both intolerable and
incorrect, and must be rectified. It is a deficiency in how we report on,
manage, and value businesses under our form of capitalism. Example
One – Engineering (Parallel Processing)
Summary
Example two – Robotic manufacturing
· A manufacturing company was making parts for cars. · It has 23-step process to make variety of parts. In the process steps 2 to 5 employed the most people. · Step 2 cut the metal rough size. 5 People · Step 3 Drill holes into the metal. 20 People · Step 4 cut the metal into a shape. 15 People · Step 5 Remove the metal shavings. 5 People · To save the cost of people they bought a robot that would combine Step 2, 3, 4 and 5 together. · The robot manufacturer claim that it could save on material waste, save on labour costs thus producing the product at a much lower cost. The company bought the robot and they lay off 42 people. They retain 3 people to run the robot. · Result. The company started to achieve a high quality of product, but the started having delays in shipping. The result was that the machine although was producing higher quality it took longer to produce the parts. The company increases the productivity of the robot by running it from an 8-hour shift to 24-hour shift 7 days a week. By increasing the production rate the maintenance rate also increase. And the amounts of maintenance slow down the actual production. The result was that shipping was delayed. · What was the cost of that part? Since the robot was cheaper than people the actual part cost was lower; however, because it could not keep up to the demand of production schedule the cost of the part was higher due to late deliveries and lost business. · Since the company produced parts for a process call “just in time” deliveries of the part had to be calculated to the hour. The company hired the 42 people back to keep up to the production schedule. Eventually the robot was removed and the people were brought back into making parts. Summary· Was this a failure of productivity? · Improved Quality. · Improved Cost. · Poor Scheduling. · The cost of delaying the shipping of final product cost the company millions of dollars in business. · Was this a waste of Time? Example 3 - Service
An IT department had 150 employees that various task. The demand for their business was very high and as result the cost of the department was very high. The problem came when a new President of the company was brought in he determine that the company had a 100-man year backlog of work. Since competition was increasing he knew that he could not let the other department wait. He needed to make his IT department more competitive. He also knew that his clients would not wait 10 years for improvement of his product. Rather than increasing the staff to deal with the backlog he instituted a series of initiatives. The were:
Summary
Impact on business in a Technology Revolution Lumber business 1979.
Lumber business 1984.
Lumber business 1988.
Overall Summary The Technology Revolution Productivity? Quality? Costs? Schedule? How do we know? Technology? Knowledge? We must use statistical to measure. You cannot use the simple measurement of dollars to determine productivity. People are basis for the Technology Revolution. Sources. The Economist the Digital Revolution
The Deming Management Method by Mary Walton, W. Edwards Deming . Out of the Crisis by W. Edwards Deming . Fourth Generation Management: The New Business Consciousness by Brian L. Joiner, et al Demings Road to Continual Improvement by Bill Scherkenback, William W. Scherkenbach . The New Economics for Industry, Government, Education - 2nd Edition by W. Edwards Deming . The Deming Dimension by Henry R. Neave, W. Edwards Deming (Designer). Knowledge As A Corporate Asset Building the case for Human Capital Thought Leadership from The Performance Paradigm Jerome J. Peloquin Co-Principal Consultant. |
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