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Teacher performance pay that keeps paying even after student ...
Atlanta Journal Constitution
... renown educator Dr. W. Edwards Deming did not equivocate: “Performance of the individual can not be measured, except possibly on a long-term basis. ...
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A Golden Opportunity for Ford and GM
With Toyota caught in a downshift, competitors should make aggressive moves to capitalize, says HBS professor Bill George. For starters, they need to improve their auto lineups for the long term. He explains how Ford and GM can best navigate the industry landscape ahead.
Views on News: Tragedy at Toyota: How Not to Lead in Crisis
"Toyota can only regain its footing by transforming itself from top to bottom to deliver the highest quality automobiles," says professor Bill George of the beleaguered company. He offers seven recommendations for restoring consumer confidence in the safety and quality behind the storied brand.
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Katharine Horler, of Connexions, which provides advice to teenagers, said people were wrong to judge careers advice on whether they ended up doing the job their advisor suggested.
She explained: "That's not what careers advice is about.
"Careers advice is about developing decision making skills, developing resilience to help you manage the ups and downs that come with a career.
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李家同：我們的光榮，我們的憂慮
【聯合報╱李家同】
2010.02.23 04:17 am
我們國家的工業技術，最近有相當不容易的成就：比方說，我們已有一家半導體儀器供應廠商，他們最新的儀器價值五百萬美金（約合一億六千萬台幣），而且他們已經賣掉了四十幾架。我們有一家生產ＣＰＵ智慧財產的公司，已能生產性能相當不錯的ＣＰＵ，我們自製的引擎也已用在國人自己的汽車上。這類產品，當然不止以上這三種，我僅僅是舉例而已。這些成就，值得我們引以為傲，但要能將這類產品推銷到全世界去，並不簡單。
這類產品的共同特色乃是在於他們的功能是非常重要而有關鍵性的，生產線上的儀器，手機裡的ＣＰＵ和汽車裡的引擎，都扮演著極為關鍵性的角色。這類產品有別於烤麵包機，家裡的烤麵包機壞了，不會引起恐慌，生產線上的儀器有瑕疵，公司的損失就大了。使用者在購買這些產品的時候，免不了會有些猶豫，畢竟我們的產品是新的，和世界著名廠商來比，買著名廠商的產品，風險的確小得多。
這類產品的另一特色是他們常需要和客戶密切合作，以生產線上儀器為例，儀器廠商不一定充分瞭解使用者廠商生產線上的需求，如果有廠商用他的產品，不僅可以去掉他們產品的缺點，也可以使他們的產品越來越精良。反過來說，如果沒有這類合作，這家儀器廠商會越來越失去競爭力的。ＣＰＵ更是如此，如果要使手機廠商使用，必須有通訊廠商肯開始將這顆ＣＰＵ和通訊系統連接起來，也要在ＣＰＵ上面寫很多軟體，這種工作是十分繁重的，目前的著名ＣＰＵ廠商，因為問世得早，已有很多通訊公司利用了這些老牌ＣＰＵ，任何一家手機廠商，如果用那些老牌ＣＰＵ，比較會得心應手，所以我們的ＣＰＵ廠商，雖然產品性能已相當優越，在推廣上比較會處於劣勢的地位。
我們有時會驚訝韓國為什麼會在短時間內，產生了一個極有競爭力的廠商，考其原因，是因為這家廠商往往有另一家廠商是他的合作夥伴。假設有一家Ａ公司想生產一架機器，他極有可能找到一家Ｂ公司幫他的忙。Ｂ公司使用這類機器已有多年歷史，深知目前世面上這類機器的缺點，也對這類機器的原理弄得很清楚，Ａ公司從Ｂ公司那裡得到不少非常有用的資訊，雛型機器發展出來，立刻有人替他作徹底的測試，它的機器當然會具有相當好的競爭力。
這種產品廠商和使用者廠商密切合作的文化極為重要，初期，產品廠商需要使用者廠商的支援協助，才得以生存茁壯，我們的機器和零組件，如果要扮演極重要的角色，使用者一定會有點猶豫，政府一定要想出一種機制，替生產這類產品的廠商找到協助的廠商。政府本身也應該起帶頭作用。比方說，政府可以訂做幾架非常高級的機器或某種軟體，以供政府單位測試及使用。如果我們的產品越來越高級，性能也越來越有關鍵性，但個個都是單打獨鬥，他們會不容易壯大的。我們為我們的高性能產品感到光榮，也為他們的處境備感憂慮，希望政府能注意這個問題。
（作者為暨南、清華、靜宜大學榮譽教授）
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什么是企业的意义？ FT专栏作家斯卡平克：经历了过去几年的风风雨雨，人们终于认识到，企业的目标应该是：通过从事我们为之自豪的工作，赚取利润，并服务客
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豐田章男在證詞中稱﹐公司的發展步伐過快令他感到不安﹐他對由此導致的在此次召回事件中暴露出來的安全問題表示遺憾﹐對豐田汽車駕駛人所遭遇的事故深感抱歉。53歲的豐田章男是該日本汽車生產商創始人的孫子。
他在發言中稱﹐他的名字銘刻在公司的每一輛車上﹐豐田將致力於重新贏得人們對其產品的信任。
豐田章男表示他有絕對的信心認為﹐公司電子油門系統的設計沒有問題。
他在回應美國國會議員的質詢時說自己完全確信豐田汽車的電子油門控制系統不存在設計缺陷。
此前有消費者投訴稱豐田汽車會突然自動加速﹐一些議員懷疑這一問題可能是由電子系統的故障導致的﹐週三的聽證會就是圍繞這些投訴展開的。
豐田章男表示將承擔此次問題的責任﹐並承諾將重塑客戶對豐田汽車的信心。
當天出席美國國會聽證會的美國運輸部部長Ray LaHood則表示﹐豐田召回的車輛存在安全問題。他呼籲這些車的車主將車輛送至經銷商處檢修。
大規模召回 暴衝有解？
豐田社長豐田章男在周三出席美國國會聽證會，他為豐田的安全問題道歉。然而對美國人來說，更重要的是豐田大規模召回汽車能否根絕問題，但豐田高層周二說可能無法靠召回維修的方式完全解決暴衝問題。
華爾街日報周三報導，根據豐田章男向眾議院監督暨政府改革委員會提交的書面證詞，他為豐田涉及的各起交通意外道歉，對因為安全問題而召回 逾850萬部汽車表達悔意。他承認豐田擴張速度，超過公司人力與組織的增長，把汽車品質問題歸咎於公司成長太快而無法完全掌控。
眾議院能源委員會周二已率先召開第1場聽證會，主席維克曼（Henry Waxman）痛批豐田高層過去10年漠視汽車暴衝問題，並指責包括國家高速公路交通安全管理局（NHTSA）等汽車安全監管機關沒有足夠設備去評估汽車的電子故障問題。
維克曼指汽車業已經進入電子化世代，但NHTSA卻仍停留在過去機械操控結構的舊思維，認為NHTSA必須有新工具和資源，去確保汽車電子操控系統和車用電腦的安全性；指豐田事件所引發的危機，將必須由立法來監管和解決。
對於有人指美國政府因為擁有通用汽車60％股權，而讓NHTSA修理豐田以提升通用的競爭力，運輸部長拉胡德（Roy LaHood）對此直斥胡說八道。
美國許多國會議員深信豐田的電子故障，是導致多起交通意外的肇因，豐田美國區總裁兼營運長藍茲（Jim Lentz）周二在聽證會上強調其電子油門控制系統沒有問題，強調暴衝是油門踏板等零件問題造成。
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Toyota says other acceleration issues being probed
Reticent Toyota president typical for Japan Inc., where harmony reigns not ...
Los Angeles Times
In harmony-loving Japan, company heads are rarely management professionals, and are picked more to be cheerleaders for the rank-and-file. ...
美国大陪审团和证交会介入调查丰田召回 英 丰田可能面临刑事起诉和巨额罚款
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Tech.view
Bring back the metal-bashers
Building quality into cars was easier before they went digital
Feb 22nd 2010 From The Economist online
LATE one night in a Ginza bar, a veteran executive at Nissan recounted to your correspondent the early days of exporting to America, when his firm’s cars were known abroad as Datsuns. Before being shipped, all export models went through additional inspections because the cost of fixing warranty claims so far from the factory and its supply chain would wipe out any profit made on them. On the rare occasions they did break, the parts had to be shipped in from Japan.
One day, the story goes, a plane carrying a crate of such parts lost an engine over the Midwest and had to jettison its cargo to save weight. On the ground below, a farmer noticed the debris falling from the sky. “Ah,” he mumbled to himself, “it’s raining Datsun cogs.”
The point the Nissan man was making with this shaggy-dog story was that the quality of Japanese cars sold abroad was well above average while they were being shipped from factories in Japan and extra precautions taken to save on warranty claims. At the time, this strategy made perfect sense. Japanese carmakers saved a ton of money from not having to finance expensive inventories around the world. Meanwhile, Honda, Toyota and Nissan (the Datsun name was dropped in 1982) gained reputations, deservedly so, for quality and reliability. Until Toyota’s recent fiasco, those brand values remained largely intact, despite Japanese carmakers relocating much of their capacity to factories overseas.
The modern view is that carmakers everywhere have learned the secrets of Japanese manufacturing and now build products of comparable quality. That is debatable. Price for price, Japanese manufacturers still manage to make their products more reliable than average. At least, they did until recently. But, in what might now be viewed as a straw in the wind, Toyota (or, rather, its luxury Lexus brand) was dethroned from the top spot in last year’s J.D. Power report on vehicle dependability.
J.D. Power and Associates, a market-research firm based in Westlake Village, California, issues this report on the American car market every year. Lexus had topped it for the previous 14. In 2009, though, Buick and Jaguar came joint top. Toyota still did well overall. Its vehicles earned nine awards for reliability in specific market segments. No other marque, save Ford’s Lincoln division, which took two, won more than one such award. But the balloon of invincibility had been punctured.
The person who began the process of inflating that balloon was, ironically, an American. From 1950 onwards W. Edwards Deming, an expert on quality control, taught a generation of Japanese managers how to improve their products. The lesson they took back to their factories was the overriding importance of statistical quality control (SQC). In industrial countries elsewhere, even in Deming’s own America, manufacturers were still relying on inspection and rejection of faulty parts—a horrendously wasteful process.
One of the main tools for SQC that Deming introduced to his Japanese disciples was the control chart, invented by Walter Shewhart at Bell Labs, the research arm of America’s former telephone monopoly, Bell System, in the 1920s. Shewhart was among the first to recognise that data collected from observations of manufacturing processes rarely follow a simple Gaussian distribution (bell curve) in the way that natural phenomena like human height do. Instead, each manufacturing process exhibits its own pattern of variation. Some display a controlled variation inherent to the process itself. Others display uncontrolled variation caused by something external to the process.
The distinction between the two patterns goes to the philosophical heart of probability theory. Deming and his colleagues at Western Electric, the manufacturing arm of Bell System, coined the terms “common cause” for the former and “special cause” for the latter.
For quality purposes, any common cause of variations in manufacturing (tool wear, say, or poor set-up) can be predicted statistically from previous observations, and the process controlled accordingly. Any special cause in variation is something that comes out of the blue from outside the process (a power surge, perhaps, or an operator falling asleep) and is beyond the scope of statistical forecasting.
The purpose of a control chart is to identify instances when variations in manufacturing are causing the specifications of a product to move above or below a mean value by more than a critical amount—say, three standard deviations. The standard deviation is a measure of the spread of a statistical curve such as a bell curve around its mean. The idea, then, is to define acceptable tolerances above and below this mean value, and design the manufacturing process to draw in the tails of the curve so that those tolerances are met a given fraction of the time. If the tolerance limits are three standard deviations from the mean, and the curve is a true Gaussian distribution, then 99.7% of production will within the zone of tolerance. If that falls, it suggests something had gone wrong. This way, any unpredictable special-cause effects can be spotted and corrected before doing too much harm.
Many refinements have been made to statistical control and the theory of quality assurance since Deming’s days—with acronyms like TQM, CMMI, MSA, QFD, FMEA and APQP, each with its own loyal band of adherents and eras of fashion. One of the more successful has been the Six Sigma strategy for identifying and removing the causes of defects, pioneered by Motorola in the 1980s. (Sigma is the Greek letter that mathematicians use to represent the standard deviation in equations.) Today, Six Sigma is used by two-thirds of the firms in Fortune’s “500” list.
Processes that operate with Six Sigma quality (in principle, within six standard deviations of a mean value) over a short sampling period produce defect levels over the long term of less than 3.4 per million—providing, of course, a lot of other management practices are also in place. When achieved, this translates into a production yield of 99.99966%. Six Sigma is said to have saved Motorola more than $17 billion over the years.
So, how did Toyota—a manufacturer that has made some of the most significant contributions to the science of quality assurance—manage to screw up so badly? It is not just the move offshore. Though the firm has 52 overseas plants in 27 countries, the quality practices honed at its headquarters in Aichi prefecture can be packaged and transplanted to Mexico or Kentucky just as readily as to a Komatsu press shop.
Nor was it Toyota’s obsession with overtaking General Motors at any cost to become the world’s largest carmaker. There is no evidence to suggest that increasing volume on modern production lines will lead inevitably to some loss of quality.
Instead, two recent trends, both software related, hint at the reason behind Toyota’s unexpected decline. One is the shortening of product-development cycles generally in the car industry. These are down from a typical four or five years to little more than 15 months, thanks to computer-aided design and manufacturing, and the virtual simulation of the resulting products. To save money and time, Toyota has even dispensed on occasion with building test “mules” and other engineering prototypes.
The other trend is the wholesale replacement of mechanical components with electronic controls. It started with ignition systems, then spread to air-conditioning, cruise-control, engine-management, throttle linkages, transmissions, and now the steering and braking systems. Drive-by-wire is not cheap, but it reduces the number of components needed to do the job. It also allows them to do extra things as well as to compensate for wear and changes in driving style and road conditions.
But software is not hardware, and software “engineers”, despite their appropriation of the name, are a different breed from the sort that bash metal. Programming digital controllers is not one of Toyota’s core competences. Even with the most diligent of testing, bugs will always find their way into software. Right now, it seems Toyota is learning that lesson the hard way.
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這個"研發"是更前段的研發
3還不用考慮到"鞋子"這個概念的研發
都是物理化學的階段
Working paper: The Evolution of Science-Based Business: Innovating How We Innovate
Download the PDF. Science has long been connected to innovation and thus to the business enterprise. However, the nature of the connection between science and business in recent decades has begun to change in important ways. On the one hand, we have witnessed the decline of corporate industrial laboratories. At the same time, we have seen the emergence of a new class of entrepreneurial firms that are deeply immersed in science in sectors like biotech, nanotech, and more recently energy. HBS professor Gary P. Pisano examines the changing nature of the science-business intersection and describes the emergence of a science-based business as a novel organizational form. He also describes the institutional and organizational challenges created by this convergence.
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