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The age of analytics: Competing in a data-driven world | McKinsey

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mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-8 mdc-u-ts-9"><span> </span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j">Nicolaus Henke<!-- --> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j">Jacques Bughin<!-- --> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/michael-chui" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Michael Chui</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/james-manyika" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">James Manyika</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/tamim-saleh" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Tamim Saleh</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/bill-wiseman" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Bill Wiseman</span></a><span>  </span></span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j">Guru Sethupathy</span></span></div><div class="mdc-u-grid-col-md-start-8 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-8 mdc-u-grid-col-lg-end-11 ArticleContent_mck-c-article-content__share-tools__kWRRw"></div></section><section class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-animation-blur-in-400"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-5"><div class="mck-u-links-inline">Big data&rsquo;s potential just keeps growing. Taking full advantage means companies must incorporate analytics into their strategic vision and use it to make better, faster decisions.</div></div></div></section><main data-layer-region="article-body" class="mdc-u-grid mdc-u-grid-gutter-xxl"><div class="mdc-u-grid mdc-u-grid-col-1 mdc-u-grid-col-md-12"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><div class="mdc-o-content-body mck-u-dropcap"><div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="DownloadsSidebar_mck-c-downloads-sidebar__iFmyt mck-o-xs-right-span"><div data-layer-region="downloads-right-rail"><h3 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-c-heading--border___K8dj3_2734c4f"></h3><div><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f"><a data-component="mdc-c-link" href="/~/media/mckinsey/industries/public and social sector/our insights/the age of analytics competing in a data driven world/the-age-of-analytics-in-brief.pdf" class="DownloadsSidebar_mck-c-downloads-sidebar__download-link__fPqFQ mdc-c-link___lBbY1_2734c4f" target="_blank" data-layer-event-prefix="Download Link" data-layer-action="click" data-layer-report-type="" data-layer-file-name="the-age-of-analytics-in-brief" data-layer-report-name="the-age-of-analytics-in-brief&gt;"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mdc-c-icon--size-md___yi5fA_2734c4f mck-download-icon"></span><span class="mdc-c-link__label___Pfqtd_2734c4f"> (PDF-533 KB)</span></a><a data-component="mdc-c-link" href="/~/media/mckinsey/industries/public and social sector/our insights/the age of analytics competing in a data driven world/mgi-the-age-of-analytics-executive-summary.pdf" class="DownloadsSidebar_mck-c-downloads-sidebar__download-link__fPqFQ mdc-c-link___lBbY1_2734c4f" target="_blank" data-layer-event-prefix="Download Link" data-layer-action="click" data-layer-report-type="" data-layer-file-name="mgi-the-age-of-analytics-executive-summary" data-layer-report-name="mgi-the-age-of-analytics-executive-summary&gt;"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mdc-c-icon--size-md___yi5fA_2734c4f mck-download-icon"></span><span class="mdc-c-link__label___Pfqtd_2734c4f"> (PDF-1 MB)</span></a><a data-component="mdc-c-link" href="/~/media/mckinsey/industries/public and social sector/our insights/the age of analytics competing in a data driven world/mgi-the-age-of-analytics-full-report.pdf" class="DownloadsSidebar_mck-c-downloads-sidebar__download-link__fPqFQ mdc-c-link___lBbY1_2734c4f" target="_blank" data-layer-event-prefix="Download Link" data-layer-action="click" data-layer-report-type="" data-layer-file-name="mgi-the-age-of-analytics-full-report" data-layer-report-name="mgi-the-age-of-analytics-full-report&gt;"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mdc-c-icon--size-md___yi5fA_2734c4f mck-download-icon"></span><span class="mdc-c-link__label___Pfqtd_2734c4f"> (PDF-3 MB)</span></a></div></div></div></div> <p><strong>Is big data all hype?</strong> To the contrary: earlier research may have given only a partial view of the ultimate impact. A new report from the McKinsey Global Institute (MGI), <em>The age of analytics: Competing in a data-driven world</em>, suggests that the range of applications and opportunities has grown and will continue to expand. Given rapid technological advances, the question for companies now is how to integrate new capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries.</p> <!-- --> <p>A 2011 MGI report highlighted <a href="/capabilities/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation">the transformational potential of big data</a>. Five years later, we remain convinced that this potential has not been oversold. In fact, the convergence of several technology trends is accelerating progress. The volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, virtual-reality applications, and billions of mobile phones. Data-storage capacity has increased, while its cost has plummeted. Data scientists now have unprecedented computing power at their disposal, and they are devising algorithms that are ever more sophisticated.</p> <p>Earlier, we estimated the potential for big data and analytics to create value in five specific domains. Revisiting them today shows uneven progress and a great deal of that value still on the table (exhibit). The greatest advances have occurred in location-based services and in US retail, both areas with competitors that are digital natives. In contrast, manufacturing, the EU public sector, and healthcare have captured less than 30 percent of the potential value we highlighted five years ago. And new opportunities have arisen since 2011, further widening the gap between the leaders and laggards.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/industries/public%20and%20social%20sector/our%20insights/the%20age%20of%20analytics%20competing%20in%20a%20data%20driven%20world/svgz-big-data-analytics-ex1.svgz?cq=50&amp;cpy=Center"/><img alt="Progress in capturing value from data and analytics has been uneven." src="/~/media/mckinsey/industries/public%20and%20social%20sector/our%20insights/the%20age%20of%20analytics%20competing%20in%20a%20data%20driven%20world/svgz-big-data-analytics-ex1.svgz?cq=50&amp;cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-disruptor1up mck-o-md-center mck-u-inline-module-border-top mck-u-inline-module-border-bottom mck-u-screen-only" data-layer-region="disruptor-1up"><div class="mdc-u-grid mdc-u-grid-gutter-md mdc-u-grid-col-lg-12 mdc-u-grid-col-md-12 "><div class="mdc-u-grid-col-md-span-12"><header data-component="mdc-c-header" class="mdc-c-header"><div class="mdc-c-header__block___i1Lg-_2734c4f"><h3 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f"><div>Would you like to learn more about the <a href="/mgi/overview">McKinsey Global Institute</a>?</div></h3></div></header><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f mdc-c-link-container--display-column___X0HDD_2734c4f mck-c-disruptor1up__content Disruptor1Up_mck-c-disruptor1up__content--links__VV4lE mdc-u-grid-gutter-md"><a data-component="mdc-c-link" href="/mgi/our-research/technology-and-markets-of-the-future" class="mdc-c-link-cta___NBQVi_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Visit our Technology & Innovation page</span><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mck-link-arrow-right-icon"></span></a></div></div></div></div> <p>Leading companies are using their capabilities not only to improve their core operations but also to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most situation in some markets. The leading firms have remarkably deep analytical talent taking on various problems—and they are actively looking for ways to enter other industries. These companies can take advantage of their scale and data insights to add new business lines, and those expansions are increasingly <a href="/capabilities/strategy-and-corporate-finance/our-insights/the-new-global-competition-for-corporate-profits">blurring traditional sector boundaries</a>.</p> <p>Where digital natives were built for analytics, legacy companies have to do the hard work of overhauling or changing existing systems. Adapting to an era of data-driven decision making is not always a simple proposition. Some companies have invested heavily in technology but have not yet changed their organizations so they can make the most of these investments. Many are struggling to develop the talent, business processes, and organizational muscle to capture real value from analytics.</p> <p>The first challenge is incorporating data and analytics into a <a href="/capabilities/mckinsey-digital/our-insights/making-data-analytics-work-for-you-instead-of-the-other-way-around">core strategic vision</a>. The next step is developing the right business processes and building capabilities, including both data infrastructure and talent. It is not enough simply to layer powerful technology systems on top of existing business operations. All these aspects of transformation need to come together to realize the full potential of data and analytics. The challenges incumbents face in pulling this off are precisely why much of the value we highlighted in 2011 is still unclaimed.</p> <p>The urgency for incumbents is growing, since leaders are staking out large advantages, and hesitating increases the risk of being disrupted. Disruption is already happening, and it takes multiple forms. Introducing new types of data sets (“orthogonal data”) can confer a competitive advantage, for instance, while massive integration capabilities can break through organizational silos, enabling new insights and models. <a href="/industries/technology-media-and-telecommunications/our-insights/competition-at-the-digital-edge-hyperscale-businesses">Hyperscale digital platforms</a> can match buyers and sellers in real time, transforming inefficient markets. Granular data can be used to personalize products and services—including, most intriguingly, healthcare. New analytical techniques can fuel discovery and innovation. Above all, businesses no longer have to go on gut instinct; they can use data and analytics to make faster decisions and more accurate forecasts supported by a mountain of evidence.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-disruptor1up mck-o-md-center mck-u-inline-module-border-top mck-u-inline-module-border-bottom mck-u-screen-only" data-layer-region="disruptor-1up"><div class="mdc-u-grid mdc-u-grid-gutter-md mdc-u-grid-col-lg-12 mdc-u-grid-col-md-12 "><div class="mdc-u-grid-col-lg-span-4 mdc-u-grid-col-md-span-5 Disruptor1Up_mck-c-disruptor1up__image___2Gc4"><picture data-component="mdc-c-picture"><img alt="bdne11_frth" src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/big%20data%20the%20next%20frontier%20for%20innovation/bdne11_frth.jpg?cq=50&amp;mh=145&amp;car=16:9&amp;cpy=Center" loading="lazy"/></picture></div><div class="mdc-u-grid-col-lg-span-8 mdc-u-grid-col-md-span-7"><header data-component="mdc-c-header" class="mdc-c-header"><div class="mdc-c-header__block___i1Lg-_2734c4f"><h3 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f"><div>Big data: The next frontier for innovation, competition, and productivity</div></h3></div></header><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f mdc-c-link-container--display-column___X0HDD_2734c4f mck-c-disruptor1up__content Disruptor1Up_mck-c-disruptor1up__content--links__VV4lE mdc-u-grid-gutter-md"><a data-component="mdc-c-link" href="/capabilities/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation" class="mdc-c-link-cta___NBQVi_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Read the article</span><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mck-link-arrow-right-icon"></span></a></div></div></div></div> <p>The next generation of tools could unleash even bigger changes. New machine-learning and deep-learning capabilities have an enormous variety of applications that stretch into many sectors of the economy. Systems enabled by machine learning can provide customer service, manage logistics, analyze medical records, or even write news stories.</p> <p>These technologies could generate productivity gains and an improved quality of life, but they carry the risk of causing job losses and dislocations. Previous MGI research found that <a href="/capabilities/mckinsey-digital/our-insights/four-fundamentals-of-workplace-automation">45 percent of work activities could be automated</a> using current technologies; some 80 percent of that is attributable to existing machine-learning capabilities. Breakthroughs in natural-language processing could expand that impact.</p> <p>Data and analytics are already shaking up multiple industries, and the effects will only become more pronounced as adoption reaches critical mass—and as machines gain unprecedented capabilities to solve problems and understand language. Organizations that can harness these capabilities effectively will be able to create significant value and differentiate themselves, while others will find themselves increasingly at a disadvantage.</p></div><div class="container-placeholder"></div></div></div><div class="mdc-u-grid mdc-u-grid-gutter-xl"><section role="contentinfo" data-layer-region="article-about-authors" class="mdc-u-grid mdc-u-grid-col-md-12 AboutAuthor_mck-c-about-author__nRJzu"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-c-heading--border___K8dj3_2734c4f mdc-u-align-center"></h5><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline mck-u-links-inline--secondary mdc-u-mt-5"><div><p><strong><a href="/sitecore/service/notfound.aspx?item=web%3a%7b84678d1c-4492-40d5-b2f0-b1050a1429c7%7d%40en">Jacques Bughin</a></strong> and <strong><a href="/our-people/james-manyika">James Manyika</a></strong> are directors of the McKinsey Global Institute, and <strong><a href="/our-people/michael-chui">Michael Chui</a></strong> is an MGI partner; <strong>Nicolaus Henke</strong> and <strong><a href="/our-people/tamim-saleh">Tamim Saleh</a></strong> are senior partners in McKinsey&rsquo;s London office, <strong><a href="/our-people/bill-wiseman">Bill Wiseman</a></strong> is a senior partner in the Taipei office, and <strong>Guru Sethupathy</strong> is a consultant in the Washington, DC, office.</p></div></div></div></section><section class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-screen-only"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-5 mdc-u-grid-col-lg-end-9"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-c-heading--border___K8dj3_2734c4f mdc-u-align-center">Explore a career with us</h5><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f mdc-c-link-container--align-center___ar3mu_2734c4f"><a data-component="mdc-c-link" href="/careers/search-jobs" class="mdc-c-button___U4iY2_2734c4f mdc-c-button--secondary___Boipq_2734c4f mdc-c-button--size-large___jwpUy_2734c4f" aria-label="Search Openings" data-layer-event-prefix="CTA Link" data-layer-action="click" data-layer-category="careers" data-layer-subcategory="search" data-layer-text="Search Openings"><span class="mdc-c-link__label___Pfqtd_2734c4f">Search Openings</span></a></div></div></section></div></main></div><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="StandalonePromo" class="RelatedArticle_mck-c-article-related__GGA76 mck-u-screen-only" data-layer-region="related-articles"><div class="mdc-o-container__wrapper is-wrapped mdc-u-spaced-mobile"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-u-align-center">Related Articles</h5><div class="mdc-u-grid mdc-u-grid-col-md-3 RelatedArticle_items-container__s2uD0"><div class="mdc-u-grid mdc-u-grid-gutter-lg Card_card__diA2r Card_hover-effect__RGb9b"><div class="Card_wrapper-image__8b4P6"><a data-component="mdc-c-link" href="/capabilities/mckinsey-digital/our-insights/making-data-analytics-work-for-you-instead-of-the-other-way-around" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-makin-0 { aspect-ratio: 16/9 }</style><img alt="data-analytics-v2-1536x1536-300_Standard" class="picture-uniqueKey-makin-0" src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/making%20data%20analytics%20work%20for%20you%20instead%20of%20the%20other%20way%20around/data-analytics-v2-1536x1536-300_standard.jpg?cq=50&amp;mw=767&amp;car=16:9&amp;cpy=Center" loading="lazy"/></picture></a></div><div class="Card_wrapper-text__U6Y3k"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f Card_content-block__pF6Z1"><span>Article - 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<i>McKinsey Quarterly</i></span><h6 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-6"><a data-component="mdc-c-link" href="/capabilities/mckinsey-digital/our-insights/straight-talk-about-big-data" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>Straight talk about big data</div></a></h6></div></div></div><div class="mdc-u-grid mdc-u-grid-gutter-lg Card_card__diA2r Card_hover-effect__RGb9b"><div class="Card_wrapper-image__8b4P6"><a data-component="mdc-c-link" href="/capabilities/mckinsey-digital/our-insights/digital-globalization-the-new-era-of-global-flows" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-digit-0 { aspect-ratio: 16/9 }</style><img alt="MGIGlobalFlows1536x1536_Standard_Standard" class="picture-uniqueKey-digit-0" src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20globalization%20the%20new%20era%20of%20global%20flows/mgiglobalflows1536x1536_standard_standard.jpg?cq=50&amp;mw=767&amp;car=16:9&amp;cpy=Center" loading="lazy"/></picture></a></div><div class="Card_wrapper-text__U6Y3k"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f Card_content-block__pF6Z1"><span>Report - <i>MGI Research</i></span><h6 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-6"><a data-component="mdc-c-link" href="/capabilities/mckinsey-digital/our-insights/digital-globalization-the-new-era-of-global-flows" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>Digital globalization: The new era of global flows</div></a></h6></div></div></div></div></div></div></div></main></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"locale":"en","dictionary":{},"sitecoreContext":{"route":{"name":"The age of analytics Competing in a data driven world","displayName":"The age of analytics Competing in a data driven world","fields":null,"databaseName":"web","deviceId":"fe5d7fdf-89c0-4d99-9aa3-b5fbd009c9f3","itemId":"3be6cfe8-f5ca-46a2-b8a3-1c3766d7e33c","itemLanguage":"en","itemVersion":1,"layoutId":"ae753eb4-a035-40b4-83bf-4b4438df6742","templateId":"683910db-02ba-40ba-92e7-726c880160a9","templateName":"ArticleJSS","placeholders":{"jss-main":[{"uid":"232bb7e9-289f-492d-a916-2b6185e44a84","componentName":"ArticleTemplate","dataSource":"","fields":{"data":{"articleTemplate":{"title":{"jsonValue":{"value":"The age of analytics: Competing in a data-driven world"}},"sEOTitle":{"value":""},"description":{"jsonValue":{"value":"Big data\u0026rsquo;s potential just keeps growing. Taking full advantage means companies must incorporate analytics into their strategic vision and use it to make better, faster decisions."}},"sEODescription":{"value":""},"displayDate":{"jsonValue":{"value":"2016-12-07T00:00:00Z"}},"body":{"value":"[[DownloadsSidebar]] \u003cp\u003e\u003cstrong\u003eIs big data all hype?\u003c/strong\u003e To the contrary: earlier research may have given only a partial view of the ultimate impact. A new report from the McKinsey Global Institute (MGI), \u003cem\u003eThe age of analytics: Competing in a data-driven world\u003c/em\u003e, suggests that the range of applications and opportunities has grown and will continue to expand. Given rapid technological advances, the question for companies now is how to integrate new capabilities into their operations and strategies\u0026mdash;and position themselves in a world where analytics can upend entire industries.\u003c/p\u003e\n[[Video Analytics]]\n\u003cp\u003eA 2011 MGI report highlighted \u003ca href=\"/capabilities/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation\"\u003ethe transformational potential of big data\u003c/a\u003e. Five years later, we remain convinced that this potential has not been oversold. In fact, the convergence of several technology trends is accelerating progress. The volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, virtual-reality applications, and billions of mobile phones. Data-storage capacity has increased, while its cost has plummeted. Data scientists now have unprecedented computing power at their disposal, and they are devising algorithms that are ever more sophisticated.\u003c/p\u003e\n\u003cp\u003eEarlier, we estimated the potential for big data and analytics to create value in five specific domains. Revisiting them today shows uneven progress and a great deal of that value still on the table (exhibit). The greatest advances have occurred in location-based services and in US retail, both areas with competitors that are digital natives. In contrast, manufacturing, the EU public sector, and healthcare have captured less than 30 percent of the potential value we highlighted five years ago. And new opportunities have arisen since 2011, further widening the gap between the leaders and laggards.\u003c/p\u003e\n[[Exhibit 1]]\n[[Disruptor1UP Learn more]]\n\u003cp\u003eLeading companies are using their capabilities not only to improve their core operations but also to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most situation in some markets. The leading firms have remarkably deep analytical talent taking on various problems\u0026mdash;and they are actively looking for ways to enter other industries. These companies can take advantage of their scale and data insights to add new business lines, and those expansions are increasingly \u003ca href=\"/capabilities/strategy-and-corporate-finance/our-insights/the-new-global-competition-for-corporate-profits\"\u003eblurring traditional sector boundaries\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eWhere digital natives were built for analytics, legacy companies have to do the hard work of overhauling or changing existing systems. Adapting to an era of data-driven decision making is not always a simple proposition. Some companies have invested heavily in technology but have not yet changed their organizations so they can make the most of these investments. Many are struggling to develop the talent, business processes, and organizational muscle to capture real value from analytics.\u003c/p\u003e\n\u003cp\u003eThe first challenge is incorporating data and analytics into a \u003ca href=\"/capabilities/mckinsey-digital/our-insights/making-data-analytics-work-for-you-instead-of-the-other-way-around\"\u003ecore strategic vision\u003c/a\u003e. The next step is developing the right business processes and building capabilities, including both data infrastructure and talent. It is not enough simply to layer powerful technology systems on top of existing business operations. All these aspects of transformation need to come together to realize the full potential of data and analytics. The challenges incumbents face in pulling this off are precisely why much of the value we highlighted in 2011 is still unclaimed.\u003c/p\u003e\n\u003cp\u003eThe urgency for incumbents is growing, since leaders are staking out large advantages, and hesitating increases the risk of being disrupted. Disruption is already happening, and it takes multiple forms. Introducing new types of data sets (\u0026ldquo;orthogonal data\u0026rdquo;) can confer a competitive advantage, for instance, while massive integration capabilities can break through organizational silos, enabling new insights and models. \u003ca href=\"/industries/technology-media-and-telecommunications/our-insights/competition-at-the-digital-edge-hyperscale-businesses\"\u003eHyperscale digital platforms\u003c/a\u003e can match buyers and sellers in real time, transforming inefficient markets. Granular data can be used to personalize products and services\u0026mdash;including, most intriguingly, healthcare. New analytical techniques can fuel discovery and innovation. Above all, businesses no longer have to go on gut instinct; they can use data and analytics to make faster decisions and more accurate forecasts supported by a mountain of evidence.\u003c/p\u003e\n[[Disruptor1UP Read next]]\n\u003cp\u003eThe next generation of tools could unleash even bigger changes. New machine-learning and deep-learning capabilities have an enormous variety of applications that stretch into many sectors of the economy. Systems enabled by machine learning can provide customer service, manage logistics, analyze medical records, or even write news stories.\u003c/p\u003e\n\u003cp\u003eThese technologies could generate productivity gains and an improved quality of life, but they carry the risk of causing job losses and dislocations. Previous MGI research found that \u003ca href=\"/capabilities/mckinsey-digital/our-insights/four-fundamentals-of-workplace-automation\"\u003e45 percent of work activities could be automated\u003c/a\u003e using current technologies; some 80 percent of that is attributable to existing machine-learning capabilities. Breakthroughs in natural-language processing could expand that impact.\u003c/p\u003e\n\u003cp\u003eData and analytics are already shaking up multiple industries, and the effects will only become more pronounced as adoption reaches critical mass\u0026mdash;and as machines gain unprecedented capabilities to solve problems and understand language. Organizations that can harness these capabilities effectively will be able to create significant value and differentiate themselves, while others will find themselves increasingly at a disadvantage.\u003c/p\u003e"},"isFullScreenInteractive":{"boolValue":false},"hideStickySocialShareBar":{"boolValue":false},"desktopID":{"value":""},"mobileID":{"value":""},"desktopURL":{"value":""},"mobileURL":{"value":""},"desktopPaddingPercentage":{"value":""},"mobilePaddingPercentage":{"value":""},"desktopOverrideHeight":{"value":""},"mobileOverrideHeight":{"value":""},"cerosOembedURL":{"value":""},"cerosRenderMode":{"targetItem":null},"cerosBackgroundColor":{"targetItem":null},"hideByLine":{"boolValue":false},"tableOfContentsTitle":{"value":"TABLE OF CONTENTS"},"accessStatus":{"targetItem":{"key":{"value":"AllUsers"},"value":{"value":"All 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the McKinsey Global Institute, and \u003cstrong\u003e\u003ca href=\"/our-people/michael-chui\"\u003eMichael Chui\u003c/a\u003e\u003c/strong\u003e is an MGI partner; \u003cstrong\u003eNicolaus Henke\u003c/strong\u003e and \u003cstrong\u003e\u003ca href=\"/our-people/tamim-saleh\"\u003eTamim Saleh\u003c/a\u003e\u003c/strong\u003e are senior partners in McKinsey\u0026rsquo;s London office, \u003cstrong\u003e\u003ca href=\"/our-people/bill-wiseman\"\u003eBill Wiseman\u003c/a\u003e\u003c/strong\u003e is a senior partner in the Taipei office, and \u003cstrong\u003eGuru Sethupathy\u003c/strong\u003e is a consultant in the Washington, DC, office.\u003c/p\u003e"},"authors":{"targetItems":[{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"27357F3A3A344242AF1824C21FC77A91","name":"Nicolaus Henke","authorTitle":{"value":"Nicolaus Henke"},"description":{"value":"Nico is a senior partner at McKinsey and chairman of QuantumBlack, McKinsey\u0026rsquo;s advanced analytics and 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