For Multinational Companies, Localization Matters More Than EverSKIP TO CONTENTHarvard Business Review LogoHarvard Business Review LogoAI and machine learning|For Multinational Companies, Localization Matters More Than EverSubscribeSign InLatestMagazineTopicsPodcastsStoreReading ListsData & VisualsCase SelectionsHBR ExecutiveSearch hbr.orgSubscribeLatestPodcastsThe MagazineStoreWebinarsNewslettersAll TopicsReading ListsData & VisualsCase SelectionsHBR ExecutiveMy LibraryAccount SettingsSign InExplore HBRLatestThe MagazinePodcastsStoreWebinarsNewslettersPopular TopicsManaging YourselfLeadershipStrategyManaging TeamsGenderInnovationWork-life BalanceAll TopicsFor SubscribersReading ListsData & VisualsCase SelectionsHBR ExecutiveSubscribeMy AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesSign InHarvard Business Review LogoAI and machine learningFor Multinational Companies, Localization Matters More Than Ever by Muqsit Ashraf, Tomas Castagnino and Giju MathewJanuary 26, 2026Deagreez/Getty ImagesPostPostShareSavePrintSummary.   Leer en españolLer em portuguêsPostPostShareSavePrintFor decades, multinational companies treated localization as a surface-layer adjustment. They tweaked marketing, packaging, or pricing to suit regional tastes. But in today’s fractured world, such superficial localization is no longer good enough. Trade policies conflict. Data laws clash. And many governments now enforce data sovereignty laws and mandates for local sourcing and technology transfer. They require companies to perform key operations, stretching from research and development to manufacturing and data processing, within their country, instead of merely selling products from abroad. The result is a profound shift in how global companies operate. They duplicate supply chains, adjust to local markets in real time, and integrate national and regional suppliers, even at the cost of scale efficiencies, to ensure redundancy and tailor best practices for every market.Muqsit Ashraf is the Group Chief Executive, Accenture Strategy, and a member of the Accenture Global Management Committee.Tomas Castagnino is chief economist at Accenture Research, and speaks and writes extensively on macro-trends at the intersection of work, technology, and industry change.Giju Mathew is a Senior Principal with Accenture Research.PostPostShareSavePrintRead more on AI and machine learning or related topics Data management, Global strategy, Social and global issues, International business, Operations and supply chain management and Supply chain managementPartner CenterStart my subscription!Explore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceExplore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceFollow HBRFacebookX Corp.LinkedInInstagramYour NewsreaderHarvard Business Review LogoAbout UsCareersPrivacy PolicyCookie PolicyCopyright InformationTrademark PolicyTerms of UseHarvard Business Publishing:Higher EducationCorporate LearningHarvard Business ReviewHarvard Business SchoolCopyright ©2026 Harvard Business School Publishing. All rights reserved. Harvard Business Publishing is an affiliate of Harvard Business School.

In recent years, multinational companies have largely viewed localization as a secondary adjustment, primarily focused on modifying marketing materials, packaging, or pricing to align with localized consumer preferences. However, the contemporary global landscape, characterized by conflicting trade policies, disparate data regulations, and increasingly stringent mandates for local operations, fundamentally alters this approach. Governments are now imposing requirements that necessitate substantial modifications to global operational models. These mandates extend beyond simple sales activities to encompass critical functions such as research and development, manufacturing, and data processing. Companies are now compelled to conduct these operations within the borders of the respective nation, rather than merely exporting products. This shift involves the duplication of supply chains, continuous adaptation to local market dynamics, and the integration of national and regional suppliers—a process that often sacrifices previously held efficiencies in favor of enhanced redundancy and the adoption of tailored best practices for each distinct market.

The authors, Muqsit Ashraf, Tomas Castagnino, and Giju Mathew, emphasize that the traditional surface-level approach to localization is no longer sufficient. The rise of data sovereignty laws, which dictate the storage and processing of data within a country’s borders, particularly complicates matters. These laws, coupled with governmental demands for local sourcing and technology transfer, force companies to rethink their entire value chains. Companies are compelled to establish physical presences, build local infrastructure, and cultivate relationships with local partners. This represents a considerable administrative and logistical burden.

Specifically, the authors highlight the implications of data localization. Governments worldwide are enacting laws requiring companies to store and process data generated within their borders. This directly impacts cloud computing, data analytics, and many other technology-driven operations. The implementation of these regulations has spurred significant changes in how multinational corporations manage their data assets and develop their IT strategies. The increasing focus on data sovereignty has driven a trend towards distributed computing and localized data centers – a move that adds to operational complexity and potentially increases costs.

Furthermore, the shift compels companies to adapt their supply chains to meet local regulations. The need for local manufacturing, assembly, and distribution networks forces a re-evaluation of global sourcing strategies. Companies must prioritize partnerships with local suppliers, invest in local talent, and ensure compliance with national standards, even if it means compromising on economies of scale. The rise of protectionist trade policies and increased regulations are therefore directly shaping the operational architecture of multinational organizations, demanding a move away from standardized, globalized processes.

The authors suggest that success in this evolving environment requires a more proactive and nuanced approach to localization. It's no longer about simple translation or brand adaptation; it's about fundamentally understanding and responding to the specific legal, regulatory, and cultural contexts of each market. This requires a deep understanding of local business practices, a willingness to invest in local partnerships, and a flexible operational structure capable of adapting to changing circumstances. Ultimately, the ability to effectively navigate these complexities will be a key determinant of a company’s competitive advantage in the 21st-century global economy.