【獨家原文翻譯56頁版】麥肯錫大數(shù)據(jù)：創(chuàng)新、競爭和生產(chǎn)力的下一個前沿(原文翻譯)

1、大數(shù)據(jù)：創(chuàng)新、競爭和生產(chǎn)力的下一個前沿（原文翻譯）麥肯錫在2011年5月發(fā)布了一個關(guān)于大數(shù)據(jù)方面的報告：Big data: The next frontier for innovation, competition, and productivity，雖然是6年前的報告，但是今天讀來，還是非常用指導(dǎo)意義。報告分為兩個版本，一個是概要版20頁，一個是完整版156頁。正好最近看了一遍概要版，覺得收益甚大。所以試著翻譯一下，僅供參考。標(biāo)題：Big data: The next frontier for innovation, competition, and productivity譯文：大數(shù)據(jù)：創(chuàng)

2、新、競爭和生產(chǎn)力的下一個前沿第二頁是關(guān)于MGI（麥肯錫全球研究院）的介紹，就不翻譯了。略。Data have become a torrent flowing into every area of the global economy. 1 Companies churn out a burgeoning volume of transactional data, capturing trillions of bytes of information about their customers, suppliers, and operations. millions of networked

3、sensors are being embedded in the physical world in devices such as mobile phones, smart energy meters, automobiles, and industrial machines that sense, create, and communicate data in the age of the Internet of Things. 2 Indeed, as companies and organizations go about their business and interact wi

4、th individuals, they are generating a tremendous amount of digital “exhaust data,” i.e., data that are created as a by-product of other activities. Social media sites, smartphones, and other consumer devices including PCs and laptops have allowed billions of individuals around the world to contribut

5、e to the amount of big data available. And the growing volume of multimedia content has played a major role in the exponential growth in the amount of big data (see Box 1, “What do we mean by big data?”). Each second of high-definition video, for example, generates more than 2,000 times as many byte

6、s as required to store a single page of text. In a digitized world, consumers going about their daycommunicating, browsing, buying, sharing, searching create their own enormous trails of data.譯文：數(shù)據(jù)已成為流入全球經(jīng)濟(jì)各個領(lǐng)域的激流。公司制造了數(shù)量龐大的交易數(shù)據(jù)，捕獲了數(shù)萬億字節(jié)的有關(guān)其客戶、供應(yīng)商和公司運營的信息。數(shù)百萬的網(wǎng)絡(luò)傳感器被嵌入在諸如移動電話、智能電表、汽車和工業(yè)機(jī)器等實體設(shè)備中，它們在物聯(lián)

7、網(wǎng)時代感知、創(chuàng)建和傳送著數(shù)據(jù)。事實上，隨著公司和組織開展他們的業(yè)務(wù)并與個人進(jìn)行互動，他們正在產(chǎn)生大量的“排放數(shù)據(jù)”，即作為其他活動的副產(chǎn)品而產(chǎn)生的數(shù)據(jù)。社交媒體、智能手機(jī)和其他消費設(shè)備，包括PC和筆記本電腦，使世界上數(shù)十億的個人能夠貢獻(xiàn)大量數(shù)據(jù)。而且越來越多的多媒體內(nèi)容在大數(shù)據(jù)的指數(shù)增長中發(fā)揮了重要作用（見插文1，“大數(shù)據(jù)”是什么？）。例如，每秒的高清視頻生成的字節(jié)數(shù)量是存儲單頁文本所需的2000倍。在數(shù)字世界中，消費者每天都在進(jìn)行通信、瀏覽、購買、共享和搜索創(chuàng)建自己巨大的數(shù)據(jù)流。Box 1. What do we mean by big data?“Big data” refers to d

8、atasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big datai.e., we dont define big data in ter

9、ms of being larger than a certain number of terabytes (thousands of gigabytes). We assume that, as technology advances over time, the size of datasets that qualify as big data will also increase. Also note that the definition can vary by sector, depending on what kinds of software tools are commonly

10、 available and what sizes of datasets are common in a particular industry. With those caveats, big data in many sectors today will range from a few dozen terabytes to multiple petabytes (thousands of terabytes).譯文：插文1.“大數(shù)據(jù)”是什么？“大數(shù)據(jù)”是指數(shù)據(jù)量級超過傳統(tǒng)數(shù)據(jù)庫軟件工具捕獲、存儲、管理和分析能力的數(shù)據(jù)集。 這個定義是主觀的，并且包含了一個數(shù)據(jù)集量級的動態(tài)定義（超過這個大

11、小才會被認(rèn)為是大數(shù)據(jù)）也就是說，我們沒有定義一個確定的值（比如多少TB）。我們認(rèn)為隨著技術(shù)的進(jìn)步，被認(rèn)定為“大數(shù)據(jù)”的數(shù)據(jù)集的大小數(shù)量級也將增加。還要注意，這個數(shù)據(jù)集大小的定義會因行業(yè)而異，它取決于這些行業(yè)中普遍使用的軟件工具不同以及通常的數(shù)據(jù)集的大小?；谶@些認(rèn)知，今天許多行業(yè)的大數(shù)據(jù)的數(shù)據(jù)集大小范圍將從幾十TB到幾PB（幾千TB）。In itself, the sheer volume of data is a global phenomenonbut what does it mean? Many citizens around the world regard this collect

12、ion of information with deep suspicion, seeing the data flood as nothing more than an intrusion of their privacy. But there is strong evidence that big data can play a significant economic role to the benefit not only of private commerce but also of national economies and their citizens. Our researc

13、h finds that data can create significant value for the world economy, enhancing the productivity and competitiveness of companies and the public sector and creating substantial economic surplus for consumers. For instance, if US health care could use big data creatively and effectively to drive effi

14、ciency and quality, we estimate that the potential value from data in the sector could be more than $300 billion in value every year, two-thirds of which would be in the form of reducing national health care expenditures by about 8 percent. In the private sector, we estimate, for example, that a ret

15、ailer using big data to the full has the potential to increase its operating margin by more than 60 percent. In the developed economies of Europe, we estimate that government administration could save more than 100 billion ($149 billion) in operational efficiency improvements alone by using big data

16、. This estimate does not include big data levers that could reduce fraud, errors, and tax gaps (i.e., the gap between potential and actual tax revenue).譯文：數(shù)據(jù)量激增本身是一個全球現(xiàn)象，但它是意味著什么呢？全球范圍內(nèi)有許多人對這種信息收集持深深的懷疑態(tài)度，認(rèn)為數(shù)據(jù)泛濫只不過是對他們隱私的侵犯。但有證據(jù)表明，大數(shù)據(jù)不僅惠及商業(yè)，而且在國民經(jīng)濟(jì)及民生方面，都會發(fā)揮重要的經(jīng)濟(jì)價值。我們的研究發(fā)現(xiàn)，數(shù)據(jù)可以為世界經(jīng)濟(jì)創(chuàng)造巨大的價值、提高公司和公共部門

17、的生產(chǎn)力和競爭力，并為消費者創(chuàng)造顯著的經(jīng)濟(jì)附加值。例如，如果美國醫(yī)療保健行業(yè)能夠創(chuàng)造性地、有效地使用大數(shù)據(jù)來提高效率和質(zhì)量，我們估計，該行業(yè)從數(shù)據(jù)獲取的潛在價值可能超過每年3000億美元，其中三分之二將體現(xiàn)在減少了國民醫(yī)療保健約8的支出。在商業(yè)世界里，我們估計，例如，充分使用大數(shù)據(jù)的零售商有可以將其營業(yè)利潤率增加60以上。在歐洲發(fā)達(dá)經(jīng)濟(jì)體，我們預(yù)計政府行政部門可以通過使用大數(shù)據(jù)，在運營效率提升上節(jié)省1000億歐元以上（1 940億美元）。這個估計不包括大數(shù)據(jù)杠桿帶來的收益，比如減少欺詐、錯誤和稅收差距（即潛在稅收和實際稅收收入之間的差距）。Digital data is now everywh

18、erein every sector, in every economy, in every organization and user of digital technology. While this topic might once have concerned only a few data geeks, big data is now relevant for leaders across every sector, and consumers of products and services stand to benefit from its application. The ab

19、ility to store, aggregate, and combine data and then use the results to perform deep analyses has become ever more accessible as trends such as Moores Law in computing, its equivalent in digital storage, and cloud computing continue to lower costs and other technology barriers. 3 For less than $600,

20、 an individual can purchase a disk drive with the capacity to store all of the worlds music. 4 The means to extract insight from data are also markedly improving as software available to apply increasingly sophisticated techniques combines with growing computing horsepower. Further, the ability to g

21、enerate, communicate, share, and access data has been revolutionized by the increasing number of people, devices, and sensors that are now connected by digital networks. In 2010, more than 4 billion people, or 60 percent of the worlds population, were using mobile phones, and about 12 percent of tho

22、se people had smartphones, whose penetration is growing at more than 20 percent a year. More than 30 million networked sensor nodes are now present in the transportation, automotive, industrial, utilities, and retail sectors. The number of these sensors is increasing at a rate of more than 30 percen

23、t a year.譯文：現(xiàn)在數(shù)字化數(shù)據(jù)無處不在存在于每個行業(yè)、每個經(jīng)濟(jì)體以及每個使用數(shù)字技術(shù)的組織和用戶中。雖然大數(shù)據(jù)這個話題可能只有一些數(shù)據(jù)極客在提及，但大數(shù)據(jù)現(xiàn)在與每個領(lǐng)域的領(lǐng)導(dǎo)者都相關(guān)，而且消費者已經(jīng)從其被應(yīng)用的產(chǎn)品和服務(wù)中受益。存儲、聚合和組合數(shù)據(jù)，并將其結(jié)果進(jìn)行深入分析的能力，經(jīng)歷著像摩爾定律在計算領(lǐng)域的趨勢一樣：數(shù)字存儲介質(zhì)、云計算持續(xù)地在降低成本和技術(shù)障礙。不到600美元，你就可以購買一個磁盤用來存儲世界上所有的音樂。從數(shù)據(jù)中獲取洞察的方法也得到顯著提升，這得益于應(yīng)用了復(fù)雜技術(shù)的軟件和強(qiáng)大的計算能力在一起進(jìn)步。此外，由于現(xiàn)在通過網(wǎng)絡(luò)連接的人、設(shè)備和傳感器的數(shù)量的增加，生成、傳播、

24、共享和訪問數(shù)據(jù)的能力得到了革命性的提升。2010年，超過40億人（占世界人口的60）使用手機(jī)，其中約12的人使用智能手機(jī)，其滲透率還在以每年超過20的速度增長。目前在交通、汽車、工業(yè)、公用事業(yè)和零售行業(yè)有超過3000萬個網(wǎng)絡(luò)傳感器節(jié)點。這些傳感器的數(shù)量以每年超過30的速度增長。There are many ways that big data can be used to create value across sectors of the global economy. Indeed, our research suggests that we are on the cusp of a tr

25、emendous wave of innovation, productivity, and growth, as well as new modes of competition and value captureall driven by big data as consumers, companies, and economic sectors exploit its potential. But why should this be the case now? Havent data always been part of the impact of information and c

26、ommunication technology? Yes, but our research suggests that the scale and scope of changes that big data are bringing about are at an inflection point, set to expand greatly, as a series of technology trends accelerate and converge. We are already seeing visible changes in the economic landscape as

27、 a result of this convergence.譯文：有很多方法可以使大數(shù)據(jù)在全球經(jīng)濟(jì)的各行業(yè)中創(chuàng)造價值。事實上，我們的研究表明，我們正處在創(chuàng)新、生產(chǎn)效率和經(jīng)濟(jì)增長的巨大浪潮中，伴隨著新的競爭和價值獲取模式完全由大數(shù)據(jù)驅(qū)動，這些大數(shù)據(jù)需要消費者、企業(yè)和各行業(yè)充分開發(fā)其潛力。但為什么是現(xiàn)在這樣呢？ 難道數(shù)據(jù)不是信息、通信技術(shù)影響的一部分？ 是的，但我們的研究表明，大數(shù)據(jù)所帶來的變化的規(guī)模和范圍處于一個拐點，隨著一系列技術(shù)趨勢的加速和趨同，它將大大擴(kuò)展。由于這種趨同，我們已經(jīng)看到經(jīng)濟(jì)格局在明顯變化。Many pioneering companies are already using

28、big data to create value, and others need to explore how they can do the same if they are to compete. Governments, too, have a significant opportunity to boost their efficiency and the value for money they offer citizens at a time when public finances are constrainedand are likely to remain so due t

29、o aging populations in many countries around the world. Our research suggests that the public sector can boost its productivity significantly through the effective use of big data.譯文：許多先驅(qū)公司已經(jīng)在使用大數(shù)據(jù)來創(chuàng)造價值，其它的需要探索他們需要如何做才能去競爭。政府也面臨一個重要的機(jī)會，在公共財政預(yù)算有限的情況下，提高他們的效率并給公民帶來的價值，而且很可能由于世界許多國家的人口老齡化，財政預(yù)算一直持續(xù)吃緊。我們

30、的研究表明，公共事業(yè)領(lǐng)域可以通過有效利用大數(shù)據(jù)來顯著提高其生產(chǎn)力。However, companies and other organizations and policy makers need to address considerable challenges if they are to capture the full potential of big data. A shortage of the analytical and managerial talent necessary to make the most of big data is a significant and

31、pressing challenge and one that companies and policy makers can begin to address in the near term. The United States alone faces a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts to analyze big data and make decisions based on their find

32、ings. The shortage of talent is just the beginning. Other challenges we explore in this report include the need to ensure that the right infrastructure is in place and that incentives and competition are in place to encourage continued innovation; that the economic benefits to users, organizations,

33、and the economy are properly understood; and that safeguards are in place to address public concerns about big data.譯文：然而，如果公司和其他組織和政策制定者要獲取大數(shù)據(jù)的全部潛力，需要面對相當(dāng)大的挑戰(zhàn)。能夠充分利用大數(shù)據(jù)的分析和管理人才的短缺是一個重大而緊迫的挑戰(zhàn)，公司和政策制定者可能很快就會遇到。僅美國就面臨14萬至19萬具備深厚的分析能力的人才缺口，更不用說還需要150萬名管理人員和分析人員要分析數(shù)據(jù)并根據(jù)上述人的發(fā)現(xiàn)做出決策。人才短缺只是開始。我們在本報告中探討的其他挑戰(zhàn)

34、包括：建立相應(yīng)的基礎(chǔ)設(shè)施；鼓勵持續(xù)創(chuàng)新的激勵和競爭機(jī)制；用戶、組織和經(jīng)濟(jì)體對于經(jīng)濟(jì)效益的正確理解；保障措施到位以應(yīng)對公眾對大數(shù)據(jù)的顧慮。This report seeks to understand the state of digital data, how different domains can use large datasets to create value, the potential value across stakeholders, and the implications for the leaders of private sector companies and p

35、ublic sector organizations, as well as for policy makers. We have supplemented our analysis of big data as a whole with a detailed examination of five domains (health care in the United States, the public sector in Europe, retail in the United States, and manufacturing and personal location data glo

36、bally). This research by no means represents the final word on big data; instead, we see it as a beginning. We fully anticipate that this is a story that will continue to evolve as technologies and techniques using big data develop and data, their uses, and their economic benefits grow (alongside as

37、sociated challenges and risks). For now, however, our research yields seven key insights:譯文：本報告旨在了解大數(shù)據(jù)的現(xiàn)狀，不同領(lǐng)域如何使用大數(shù)據(jù)來創(chuàng)造價值，對利益相關(guān)者的潛在價值，以及對私營公司和公共事業(yè)領(lǐng)域的領(lǐng)導(dǎo)人，也就是決策者的影響。 我們對大數(shù)據(jù)作為一個整體進(jìn)行了分析，詳細(xì)分析了五個領(lǐng)域（美國的衛(wèi)生保健，歐洲的公共事業(yè)領(lǐng)域，美國的零售業(yè)，全球的制造和個人位置數(shù)據(jù)）。這項研究絕不是大數(shù)據(jù)的蓋棺定論，相反它僅僅是一個開始。我們確信，隨著使用大數(shù)據(jù)的技術(shù)和方法的發(fā)展，以及數(shù)據(jù)、數(shù)據(jù)應(yīng)用、數(shù)據(jù)應(yīng)用所帶來的經(jīng)

38、濟(jì)效益的增長（伴隨著挑戰(zhàn)和風(fēng)險），這將是一個持續(xù)發(fā)展的故事。就目前來說，我們的研究涵蓋了以下七個核心觀點：1. DATA HAVE SWEPT INTO EVERY INDUSTRY AND BUSINESS FUNCTION AND ARE NOW AN IMPORTANT FACTOR OF PRODUCTIONSeveral research teams have studied the total amount of data generated, stored, and consumed in the world. Although the scope of their estima

39、tes and therefore their results vary, all point to exponential growth in the years ahead. MGI estimates that enterprises globally stored more than 7 exabytes of new data on disk drives in 2010, while consumers stored more than 6 exabytes of new data on devices such as PCs and notebooks. One exabyte

40、of data is the equivalent of more than 4,000 times the information stored in the US Library of Congress. Indeed, we are generating so much data today that it is physically impossible to store it all. Health care providers, for instance, discard 90 percent of the data that they generate (e.g., almost

41、 all real-time video feeds created during surgery).譯文：1. 數(shù)據(jù)已經(jīng)滲透到每個行業(yè)和商業(yè)功能之中，是生產(chǎn)的重要因素。已經(jīng)有幾個研究團(tuán)隊對世界范圍內(nèi)生成、存儲和消費的數(shù)據(jù)總量進(jìn)行研究。盡管由于研究范圍不同，所帶來的結(jié)果各不相同，但都表明未來會呈指數(shù)級增長。MGI估計，2010年，全球企業(yè)在磁盤驅(qū)動器中存儲超過7 EB的新數(shù)據(jù)，與此同時，消費者在PC和筆記本電腦等設(shè)備上存儲超過6 EB的新數(shù)據(jù)。1 EB的數(shù)據(jù)相當(dāng)于4000多倍于美國國會圖書館的存儲信息。事實上，我們今天所收集的海量數(shù)據(jù)，物理存儲無法實現(xiàn)。例如，醫(yī)療保健提供者會丟棄其90%的生成

42、數(shù)據(jù)（例如，幾乎所有在手術(shù)期間所創(chuàng)建的實時視頻）。Big data has now reached every sector in the global economy. Like other essential factors of production such as hard assets and human capital, much of modern economic activity simply couldnt take place without it. We estimate that by 2009, nearly all sectors in the US econom

43、y had at least an average of 200 terabytes of stored data (twice the size of US retailer Wal-Marts data warehouse in 1999) per company with more than 1,000 employees. Many sectors had more than 1 petabyte in mean stored data per company. In total, European organizations have about 70 percent of the

44、storage capacity of the entire United States at almost 11 exabytes compared with more than 16 exabytes in 2010. Given that European economies are similar to each other in terms of their stage of development and thus their distribution of firms, we believe that the average company in most industries

45、in Europe has enough capacity to store and manipulate big data. In contrast, the per capita data intensity in other regions is much lower. This suggests that, in the near term at least, the most potential to create value through the use of big data will be in the most developed economies. Looking ah

46、ead, however, there is huge potential to leverage big data in developing economies as long as the right conditions are in place. Consider, for instance, the fact that Asia is already the leading region for the generation of personal location data simply because so many mobile phones are in use there

47、. More mobile phonesan estimated 800 million devices in 2010are in use in China than in any other country. Further, some individual companies in developing regions could be far more advanced in their use of big data than averages might suggest. And some organizations will take advantage of the abili

48、ty to store and process data remotely.譯文：大數(shù)據(jù)現(xiàn)已覆蓋全球經(jīng)濟(jì)中的各個部門，一如有形資產(chǎn)和人力資本這樣的重要生產(chǎn)要素，現(xiàn)代經(jīng)濟(jì)活動根本離不開大數(shù)據(jù)。我們估計，到2009年，美國經(jīng)濟(jì)中幾乎所有領(lǐng)域擁有1000名以上員工規(guī)模的企業(yè)，平均至少有200 TB的存儲數(shù)據(jù)（這是1999年美國零售商沃爾瑪數(shù)據(jù)倉庫規(guī)模的兩倍）。在許多行業(yè)，每個公司的平均存儲數(shù)據(jù)都超過1 PB?？偟膩碚f，歐洲組織大約是整個美國存儲容量的70，接近11 EB，而美國在2010年超過16 EB。鑒于歐洲各經(jīng)濟(jì)體發(fā)展階段彼此類似，因此，我們認(rèn)為，歐洲大多數(shù)行業(yè)的公司都有足夠的能力來存儲和操縱

49、大數(shù)據(jù)。其他地區(qū)的人均數(shù)據(jù)容量相較更低。這表明，至少在短期內(nèi)，通過大數(shù)據(jù)創(chuàng)造價值的最大潛在地區(qū)是在最發(fā)達(dá)經(jīng)濟(jì)體。然而長遠(yuǎn)來看，只要條件成熟，發(fā)展中經(jīng)濟(jì)體也同樣潛力巨大。例如，目前亞洲已經(jīng)是個人位置數(shù)據(jù)的領(lǐng)先地區(qū)，因為人口眾多，移動電話普及。 2010年，手機(jī)使用率還會更高僅僅在中國就預(yù)計有8億臺設(shè)備。此外，發(fā)展中國家的個別公司，在使用大數(shù)據(jù)方面表現(xiàn)強(qiáng)勁。還有的組織將充分利用遠(yuǎn)程存儲和數(shù)據(jù)處理能力。The possibilities of big data continue to evolve rapidly, driven by innovation in the underlying tec

50、hnologies, platforms, and analytic capabilities for handling data, as well as the evolution of behavior among its users as more and more individuals live digital lives.譯文： 由于基礎(chǔ)技術(shù)、平臺和數(shù)據(jù)分析能力的創(chuàng)新，并且越來越多的用戶行為在虛擬的數(shù)字世界展現(xiàn)出來，大數(shù)據(jù)的可能性將持續(xù)迅猛發(fā)展。2. BIG DATA CREATES VALUE IN SEVERAL WAYSWe have identified five broa

51、dly applicable ways to leverage big data that offer transformational potential to create value and have implications for how organizations will have to be designed, organized, and managed. For example, in a world in which large-scale experimentation is possible, how will corporate marketing function

52、s and activities have to evolve? How will business processes change, and how will companies value and leverage their assets (particularly data assets)? Could a companys access to, and ability to analyze, data potentially confer more value than a brand? What existing business models are likely to be

53、disrupted? For example, what happens to industries predicated on information asymmetrye.g., various types of brokersin a world of radical data transparency? How will incumbents tied to legacy business models and infrastructures compete with agile new attackers that are able to quickly process and ta

54、ke advantage of detailed consumer data that is rapidly becoming available, e.g., what they say in social media or what sensors report they are doing in the world? And what happens when surplus starts shifting from suppliers to customers, as they become empowered by their own access to data, e.g., co

55、mparisons of prices and quality across competitors?譯文：2. 大數(shù)據(jù)在眾多領(lǐng)域創(chuàng)造價值我們發(fā)現(xiàn)了五種廣泛適用的途徑，通過利用大數(shù)據(jù)發(fā)現(xiàn)潛在的轉(zhuǎn)型可能來創(chuàng)造價值，并對組織如何設(shè)計、運營和管理產(chǎn)生重要影響。例如，在可以開展大規(guī)模試驗的環(huán)境中，企業(yè)如何開展?fàn)I銷活動？企業(yè)流程如何調(diào)整，企業(yè)如何評估和利用他們的資產(chǎn)（特別是數(shù)據(jù)資產(chǎn)）？公司對數(shù)據(jù)的訪問和分析能力能否具有高于品牌的價值？現(xiàn)有的商業(yè)模式會被什么取代？例如，基于信息不對稱的行業(yè)例如，各種類型的經(jīng)紀(jì)人在數(shù)據(jù)充分透明度的世界，將會有何改變？在原有商業(yè)模式和基礎(chǔ)架構(gòu)之上的現(xiàn)任人員，如何與新晉攻擊者競

56、爭，這些攻擊者能夠快速處理并利用詳實的消費者數(shù)據(jù)，例如，他們在社交媒體中說了些什么，他們在使用哪種設(shè)備？當(dāng)大量數(shù)據(jù)開始從供應(yīng)商轉(zhuǎn)移到消費者端，消費者可以自主的訪問數(shù)據(jù)，比如對比各競爭對手間的價格和質(zhì)量，那又會發(fā)生什么呢？Creating transparency Simply making big data more easily accessible to relevant stakeholders in a timely manner can create tremendous value. In the public sector, for example, making relevan

57、t data more readily accessible across otherwise separated departments can sharply reduce search and processing time. In manufacturing, integrating data from R&D, engineering, and manufacturing units to enable concurrent engineering can significantly cut time to market and improve quality.譯文：創(chuàng)建透明度使利益

58、相關(guān)者的及時訪問更加便捷，僅憑這一點就可以創(chuàng)造巨大的價值。例如，在公共部門，使那些獨立部門獲取數(shù)據(jù)更為容易，可以大大減少搜索和處理時間。在制造過程中，整合來自研發(fā)、工程和制造單元的數(shù)據(jù)，以實現(xiàn)并行處理，可顯著縮短產(chǎn)品推向市場的時間并提高其質(zhì)量。Enabling experimentation to discover needs, expose variability, and improve performance As they create and store more transactional data in digital form, organizations can collec

59、t more accurate and detailed performance data (in real or near real time) on everything from product inventories to personnel sick days. IT enables organizations to instrument processes and then set up controlled experiments. Using data to analyze variability in performancethat which either occurs naturally or is generated by controlled experimentsand to understand its root causes can enable lea