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Using digital twins to unlock supply chain growth | McKinsey
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mdc-u-grid-col-md-end-7 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-8 mdc-u-ts-10"></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_8032924 mdc-u-ts-5"><div class="mck-u-links-inline">Complexity, COVID-19, and competition have upended supply chain organizations. They can reignite revenue growth and deepen resilience by deploying AI-powered digital twins.</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_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-c-heading--border___K8dj3_8032924"></h3><div><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924"><a data-component="mdc-c-link" href="#/download/%2F~%2Fmedia%2Fmckinsey%2Fbusiness%20functions%2Fmckinsey%20digital%2Four%20insights%2Fdigital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth%2Fdigital-twins-the-key-to-unlocking-end-to-end-supply-chain-growth_final.pdf%3FshouldIndex%3Dfalse" class="DownloadsSidebar_mck-c-downloads-sidebar__download-link__fPqFQ mdc-c-link___lBbY1_8032924" target="_self" data-layer-event-prefix="Download Link" data-layer-action="click" data-layer-report-type="" data-layer-file-name="digital-twins-the-key-to-unlocking-end-to-end-supply-chain-growth_final" data-layer-report-name="digital-twins-the-key-to-unlocking-end-to-end-supply-chain-growth_final>"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-md___yi5fA_8032924 mck-download-icon"></span><span class="mdc-c-link__label___Pfqtd_8032924"> (7 pages)</span></a></div></div></div></div> <p><strong>The post-COVID-19 era has created</strong> lasting fissures in the supply chain. Amid increasing globalization, rising customer expectations, and double-digit shipping growth,<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_bottom__9aoSL FootNote_inactive__VZfCp" aria-describedby="bb46979d-bf35-45d8-b2a5-6950979c9bf6"><sup class="FootNote_footnotesup__e73z_">1</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="bb46979d-bf35-45d8-b2a5-6950979c9bf6" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">“Air Cargo Market Analysis,” International Air Transport Association, March 2024.</span></span></span></a></span> supply chain organizations—not just manufacturers and suppliers but also the warehouses and transporters they rely on—are under duress. They grapple with issues related to operational efficiency, demand forecasting, inventory management, and fulfillment. This complexity affects every part of the supply chain in every industry: retail, technology, automotive, industrial, food services, telecommunications, and more. The result is stalled growth and missed revenue opportunities.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="" data-module-gradient-position="bottom-right" class="mck-c-inline-module-container SideBar_mck-c-sidebar__bgimg-wrapper__Qj4Dt mck-o-sm-left-span SideBar_mck-c-sidebar__sidebar-wrapper__Dpjw2 SideBar_mck-c-sidebar__sidebar-wrapper--istablet__IQ6ii mck-u-screen-only mck-c-module-wrapper" data-layer-region="sidebar"><div class="SideBar_mck-c-sidebar__epoAm mck-o-md-center"><div class="SideBar_mck-c-sidebar__share-icons-wrapper__9gB_c"><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924 mdc-c-link-container--display-column___X0HDD_8032924 SideBar_mck-c-sidebar__share-icons___eQy6"><button data-component="mdc-c-button" aria-label="Expandable Sidebar" type="button" id="button_id" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium SideBar_mck-c-sidebar__toggle-btn__EL8iE" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-category="sidebar" data-layer-subcategory="open" data-layer-text="open sidebar"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--radial___y3csX_8032924 mdc-c-icon--size-xxl___cL3ZT_8032924 mck-plus-no-circle-icon"></span></button></div></div><div class="SideBar_mck-c-sidebar__content-outer__UdWCq"><div class="SideBar_mck-c-sidebar__eyebrow__5GSEq"></div><div class="SideBar_mck-c-sidebar__content__raEwe"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-u-ts-3 SideBar_mck-c-sidebar__content-heading__NJekY"><div>About the authors</div></h2><div class="SideBar_mck-c-sidebar__content-description__4p9iI mdc-u-ts-7"><div class="mdc-o-content-body">This article is a collaborative effort by <a href="/our-people/alberto-oca">Alberto Oca</a>, <a href="/our-people/alex-cosmas">Alex Cosmas</a>, <a href="/our-people/cenk-tunasar">Cenk Tunasar</a>, and <a href="/our-people/ketan-shah">Ketan Shah</a>, with Lauren O’Neil, representing views from QuantumBlack, AI by McKinsey and McKinsey’s Operations Practice.</div></div></div></div></div></div> <p>Several competing forces are exerting pressure on the supply chain: consumer demand for low-priced products delivered via fast-and-free shipping; rising wages for manufacturing, warehouse, and delivery employees; and murky visibility into future macroeconomic disruptions. McKinsey research shows that more than 90 percent of US consumers now expect two- to three-day delivery for purchases and one-third expect same-day delivery.<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_bottom__9aoSL FootNote_inactive__VZfCp" aria-describedby="202e848c-4480-4319-af23-5bfdb543fbc9"><sup class="FootNote_footnotesup__e73z_">2</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="202e848c-4480-4319-af23-5bfdb543fbc9" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline"><em><a href="/industries/retail/our-insights/retail-speaks-seven-imperatives-for-the-industry">Retail speaks: Seven imperatives for the industry</a>,</em> McKinsey and the Retail Industry Leaders Association, March 10, 2021.</span></span></span></a></span> And ever since the pandemic disrupted in-person sales, B2B companies expect their suppliers to offer omnichannel sales via online marketplaces, mobile, videoconferencing, and chat.<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_bottom__9aoSL FootNote_inactive__VZfCp" aria-describedby="bbddae83-ebf7-40e2-acd0-4c04591a7b80"><sup class="FootNote_footnotesup__e73z_">3</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="bbddae83-ebf7-40e2-acd0-4c04591a7b80" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">“<a href="/capabilities/growth-marketing-and-sales/our-insights/b2b-sales-omnichannel-everywhere-every-time">B2B sales: Omnichannel everywhere, every time</a>,” McKinsey, December 15, 2021.</span></span></span></a></span></p> <p>Fulfilling these expectations is more challenging than ever. High labor prices—including a more than 30 percent increase in warehousing wages between July 2020 and July 2024<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_bottom__9aoSL FootNote_inactive__VZfCp" aria-describedby="8a90ad11-423e-4614-9425-01964b95861c"><sup class="FootNote_footnotesup__e73z_">4</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="8a90ad11-423e-4614-9425-01964b95861c" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">“Employment statistics,” US Bureau of Labor Statistics, July 2024.</span></span></span></a></span>—make it difficult to maintain low prices while meeting margins. <a href="/capabilities/people-and-organizational-performance/our-insights/tradespeople-wanted-the-need-for-critical-trade-skills-in-the-us">Manufacturing labor shortages</a> undermine the ability to create steady inventory flows, while unexpected economic shocks such as recent inflation complicate demand forecasting. And even when the supply side is functioning well, fulfillment remains a challenge; warehouse storage rates remain constrained, causing products to reach recipients late.</p> <h2>Digital twins could heal the supply chain</h2> <!-- --> <p>Under these circumstances, organizations that do not recalibrate their supply chain operations risk falling behind. <a href="/featured-insights/mckinsey-explainers/what-is-digital-twin-technology">Digital twins</a> can help with that recalibration. Leading companies are already turning to them to ensure their supply chains are flexible, agile, and responsive enough to overcome unexpected disruptions.</p> <p>Digital twins are virtual replicas of an object, system, or process used to simulate potential situations and outcomes. Digital twins use real data (sometimes in masked or synthetic forms) to deliver analytical insights and visualizations. Many organizations use digital twins to optimize operations, plan scenarios, and aid <a href="/featured-insights/mckinsey-explainers/what-is-decision-making">decision making</a>. Market analysis indicates the global market for digital twins will grow about 30 to 40 percent annually in the next few years, reaching $125 billion to $150 billion by 2032.<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_bottom__9aoSL FootNote_inactive__VZfCp" aria-describedby="659fbfb6-f1bf-4d8d-99ac-296349a979a5"><sup class="FootNote_footnotesup__e73z_">5</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="659fbfb6-f1bf-4d8d-99ac-296349a979a5" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">Average growth calculated from digital twin market reports from Roots Analysis (41 percent CAGR for 2024–32 to reach $150 billion in 2032), December 2023; and GMI Insights (33 percent CAGR for 2024–32 to reach $125 billion in 2032), March 2024.</span></span></span></a></span></p> <p>Digital twins can be used to model the interaction between physical and digital processes all along the supply chain—from product ideation and manufacturing to warehousing and distribution, from in-store or online purchases to shipping and returns. Thus, digital twins paint a clear picture of an optimal end-to-end supply chain process. What’s more, paired with today’s advances in predictive AI, digital twins can become both predictive and prescriptive. They can predict future scenarios to suggest areas for improvement or growth, ultimately leading to a self-monitoring and self-healing supply chain. In other words, digital twins empower the switch from heuristic-based supply chain management to dynamic and granular optimization, providing a 360-degree view of value and performance leakage.</p> <p>To understand how a self-healing supply chain might work in practice, let’s look at one example: using digital twins, a retailer sets dynamic SKU-level safety stock targets for each fulfillment center that dynamically evolve with localized and seasonal demand patterns. Moreover, this granular optimization is applied not just to inventory management but also to every part of the end-to-end supply chain—from procurement and product design to manufacturing and demand forecasting. For example, the retailer’s granular production planning could be done in coordination with downstream transportation decisions and inventory positioning. Dynamic planning might identify, for instance, a high-volume commodity item with cross-sell potential, where higher manufacturing costs for the item are offset by lower end-to-end logistics costs through bundled shipping and higher customer conversion. This type of complex predictive modeling is what digital twins do best. Typical results in such a scenario are up to a 20 percent improvement in fulfilling consumer promise (achieving the delivery date communicated to the consumer), a 10 percent reduction in labor costs, and a 5 percent revenue uplift. </p> <h2>Digital twins optimize today’s SCM software</h2> <p>Today’s supply chain management (SCM) software—which includes a range of products, such as advanced planning and scheduling (APS) tools, warehouse management systems (WMS), and transportation management systems (TMS)—has automated large parts of the supply chain in the past decade, dramatically streamlining how suppliers, buyers, and shippers intersect.</p> <p>Digital twins can integrate with existing SCM tools, functioning as an innovation layer that sits on top of the tech stack. In this manner, digital twins can optimize data inputs into SCM tools, generating predictive analytics to address and respond to multiple potential scenarios. For example, a global OEM created a digital twin to optimize the policies it fed into its TMS platform for outbound logistics. As a result, the OEM reduced costs for freight and damages by 8 percent.</p> <p>Digital twins help augment SCM tools in several ways:</p> <ul> <li><em>End-to-end connections:</em> Digital twins can connect SCM tools throughout the supply chain to provide an integrated view of performance and up- and downstream decision impacts. This eliminates a siloed approach in which each tool only optimizes its local variables, with little coordination among them. For example, one retailer used digital twins to connect their planning, inventory deployment, and transportation management tools.</li> <li><em>Resiliency in dynamic markets:</em> As volatility continues to increase post-COVID-19, supply chain operators must continually update their policies due to both fluctuating demand and intermittent supply shocks, such as port disruptions or availability of materials. When combined with digital twins, SCM tools provide real-time visibility into granular performance, paired with predictive and prescriptive analytics to dynamically identify risks and recommend policy changes for rapid resolution. For example, one OEM used automated sense-and-respond digital-twin capabilities to identify shifts in carrier performance and surcharges, effectively reducing last-mile transportation costs by 5 percent.</li> <li><em>Multiple objectives:</em> Digital twins can optimize across competing priorities and complex constraints for rapid response to market changes. For example, one automotive OEM used digital twins to dynamically shape demand based on shifting supply availability and operational complexity, collectively solving across both sales and operational objectives.</li> <li><em>Variability:</em> Digital twins combined with SCM tools can test for a distribution of potential scenarios by analyzing metrics, such as lead time, demand, and supplier reliability, while also considering what-if outcomes. For instance, a consumer-packaged-goods company measured variable demand and labor in its warehouse and identified the opportunity to reduce total distribution center costs by 15 percent. This exemplifies network resiliency.</li> </ul> <h2>A deep dive into digital twins</h2> <p>Seeing digital twins in action is the best way to understand how they can deliver value at key points in the supply chain. Explore the below potential use cases to see how digital twins can solve real pain points throughout the supply chain to improve efficiency and resiliency.</p> <h4 style="text-align:center">Forecasting and demand planning</h4> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-md-center Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot1-demand-planning.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Isometric illustration of two people analyzing various charts and graphs, symbolizing data analysis and strategic demand planning." src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot1-demand-planning.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Isometric illustration of two people analyzing various charts and graphs, symbolizing data analysis and strategic demand planning.</div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="StandalonePromo" class="Accordion_mck-c-accordion__D1U2s mck-c-module-wrapper mck-o-container--inline-module mck-c-inline-module-container mck-o-md-center" data-module-name="accordion" data-layer-region="accordion"><div class="mck-o-container"><div class="UpModule_mck-c-up__irSw8"><div data-component="mdc-c-accordion" class="mdc-c-accordion"><div class="mdc-c-accordion__items___yF0jA_8032924"><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-0" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-0" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div>Predicting demand</div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div></div></div></div></div></div> <h4 style="text-align:center">Sourcing and production planning</h4> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-md-center Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot2-production-planning.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Isometric illustration showcasing a streamlined sourcing, manufacturing, and logistics process involving the use of digital twins." src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot2-production-planning.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Isometric illustration showcasing a streamlined sourcing, manufacturing, and logistics process involving the use of digital twins.</div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="StandalonePromo" data-module-gradient-position="top-right" class="Accordion_mck-c-accordion__D1U2s mck-c-module-wrapper mck-o-container--inline-module mck-c-inline-module-container mck-o-md-center" data-module-name="accordion" data-layer-region="accordion"><div class="mck-o-container"><div class="UpModule_mck-c-up__irSw8"><div data-component="mdc-c-accordion" class="mdc-c-accordion"><div class="mdc-c-accordion__items___yF0jA_8032924"><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-0" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-0" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div><p>Optimizing supply</p></div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div></div></div></div></div></div> <h4 style="text-align:center">Distribution center network</h4> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-md-center Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot3-distribution-network.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Isometric illustration of a network of distribution centers connected by lines. Data streams between the centers represent the flow of goods, inventory levels, and efficiency." src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot3-distribution-network.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Isometric illustration of a network of distribution centers connected by lines. Data streams between the centers represent the flow of goods, inventory levels, and efficiency.</div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="StandalonePromo" class="Accordion_mck-c-accordion__D1U2s mck-c-module-wrapper mck-o-container--inline-module mck-c-inline-module-container mck-o-md-center" data-module-name="accordion" data-layer-region="accordion"><div class="mck-o-container"><div class="UpModule_mck-c-up__irSw8"><div data-component="mdc-c-accordion" class="mdc-c-accordion"><div class="mdc-c-accordion__items___yF0jA_8032924"><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-0" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-0" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div><p><span style="line-height: 107%;">Network design</span></p></div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-1" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-1" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div>Inventory management and positioning</div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-2" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-2" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div>Warehouse optimization</div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div></div></div></div></div></div> <h4 style="text-align:center">End customers</h4> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-md-center Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot4-customer.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Illustration showing the flow of packages and data between a warehouse and customers, highlighting the logistics of online shopping." src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20twins%20the%20key%20to%20unlocking%20end%20to%20end%20supply%20chain%20growth/dt-supplychain-spot4-customer.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Illustration showing the flow of packages and data between a warehouse and customers, highlighting the logistics of online shopping.</div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="StandalonePromo" class="Accordion_mck-c-accordion__D1U2s mck-c-module-wrapper mck-o-container--inline-module mck-c-inline-module-container mck-o-md-center" data-module-name="accordion" data-layer-region="accordion"><div class="mck-o-container"><div class="UpModule_mck-c-up__irSw8"><div data-component="mdc-c-accordion" class="mdc-c-accordion"><div class="mdc-c-accordion__items___yF0jA_8032924"><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-0" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-0" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div><p><span style="line-height: 107%;">Fulfillment</span></p></div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div><div class="mdc-c-accordion__item___TaDQ0_8032924 Accordion_mck-c-accordion__item__vmGJ9"><h4 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924"><button data-component="mdc-c-button" aria-label="" type="button" id="accordion-panel-1" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-accordion__title-wrapper___ujaRh_8032924" aria-controls="accordion-panel-1" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-location="accordion" data-layer-text="expand"><div class="mdc-c-accordion__title___S2Csf_8032924 mdc-u-font-face-secondary"><div>Reverse logistics</div></div><span class="mdc-c-accordion__icon___MnUrM_8032924"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-lg___5rPck_8032924 mck-arrow-down-thin-icon"></span></span></button></h4></div></div></div></div></div></div> <h2>Understanding the benefits of digital twins</h2> <p>Supply chain organizations are leveraging digital twins to optimize both their long-term strategies and everyday operations. The most common ways we have seen supply chain companies deploy digital twins are for inventory positioning and forecasting, to manage the flow of goods within the four walls of warehouses and factories, and to aid in production planning. But these are just a few of the ways digital twins are being implemented throughout the supply chain. No matter how digital twins are used, the benefits are clear:</p> <ul> <li><em>Strategic:</em> Digital twins can derisk long-term planning and broader digital transformations by simulating potential outcomes. This kind of what-if predictive modeling gives companies confidence in the end-to-end impact of their strategic plans. For example, a retailer used a granular digital twin of its distribution network to test the bottom-up implications of a new design for its distribution center. The company had previously used top-down analysis to determine the size and location of a potential new cross-dock. But when teams used a digital twin to model all the potential constraints of that cross-dock placement, they found they could resize and relocate it on 50 percent less real estate without compromising functionality.</li> <li><em>Operational:</em> Beyond informing one-time strategy decisions, digital twins can function as “one model to rule them all,” optimizing daily decisioning across different operations. In other words, rather than a system of disjointed predictive models, a digital twin can combine many models for integrated forecasting and decision making—dynamically comparing competing trade-offs across the supply chain to suggest granular operational changes. For example, the same retailer used its digital twin to not only optimize its cross-dock footprint in its distribution center but also to optimize its daily inventory positioning decisions—forecasting weekly days-of-supply policies to balance cost, service levels, and sustainability. The result was a 10 percent improvement in regional distribution center utilization and 5 percent reduction in fulfillment costs.</li> </ul> <h2>Getting started with digital twins</h2> <p>While supply chain organizations recognize the value digital twins can provide, few have implemented them at scale. Unlike many SCM solutions that are plug and play, digital twins may require a customized build to implement. Because digital twins routinely ingest large quantities of proprietary, masked, or synthetic data, they are almost always custom-built, which takes considerable time and investment. Supply chain organizations must have in-house data science and development teams capable of building digital twins that use advanced AI algorithms, or partner with outside vendors expert in these areas.</p> <p>Organizations that aspire to embark on the digital-twin journey should focus on five key tenets for success:</p> <ul> <li><em>North Star road map:</em> Determine the vision for a future supply chain operation built on data and technology. Identify end-to-end use cases that support the North Star vision and then build a road map of use cases by prioritizing for impact—profit and loss or delivery—and feasibility. Typically, companies first prioritize use cases with quick speed-to-impact to prove value early in the journey.</li> <li><em>Data visibility:</em> For each use case in the end-to-end road map, identify the data inputs and outputs needed. Build a complementary road map for the organization’s data products that supports the use case road map, prioritizing data elements that will be shared across multiple high-impact implementations. Develop these data products iteratively with agile development. To get started, digital twins require a semiregular pipeline of digitized and standardized data, but it’s possible to fill data gaps with more static sources such as, for example, average throughput in a warehouse versus daily staffing levels.</li> <li><em>Technology architecture:</em> Digital-twin architecture is largely composed of existing data sources and technology, stitched together via APIs and middleware. Typically, a marginal increase in compute capacity is required to support a twin, so ensure that tech teams have the flexibility to scale current compute resources as needed.</li> <li><em>Talent:</em> Assess the skill levels of team members needed to deliver digital twins, including product managers, data engineers, data scientists, user interface/user experience designers, and full-stack developers. Digital twins are most effectively delivered with agile methodologies for rapid development cycles, so product managers may require agile upskilling and training.</li> <li><em>Optimization and simulation:</em> Identify the company’s first digital twin use case and deploy it. Build on the data products to create optimization and simulation modules that capture use case impact. Then, iteratively expand use cases and combine modules for integrated simulations and end-to-end optimization. Note that teams can start developing simulation and optimization modules before the data product is complete to capture early impact and then integrate these modules later.</li> </ul> <hr/> <p>End-to-end supply chain optimization requires more than just implementing technology; it also requires a mindset shift at the leadership level and throughout the organization. Internally, companies that use digital twins must endeavor to eliminate internal silos and replace piecemeal institutional knowledge with data-driven decisioning. Externally, companies should carefully analyze their roles in the interconnected global supply chain. In an increasingly complex and interconnected world, organizations across the supply chain can use digital twins to predict potential disruptions and what-if scenarios that could affect their businesses. No one can predict the next pandemic, war, or economic shock with certainty, but digital twins can help companies react and adapt to these eventualities.</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_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-c-heading--border___K8dj3_8032924 mdc-u-align-center"></h5><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_8032924 mdc-u-ts-8 mck-u-links-inline mck-u-links-inline--secondary mdc-u-mt-5"><div><p><strong><a href="/our-people/alberto-oca">Alberto Oca</a></strong> is a partner in McKinsey’s Atlanta office, where <strong>Lauren O’Neil</strong> is an associate partner; <a href="/our-people/alex-cosmas"><strong>Alex Cosmas</strong></a> is a partner in the New York office; <strong><a href="/our-people/cenk-tunasar">Cenk Tunasar</a></strong> is a partner in the Boston office; and <strong><a href="/our-people/ketan-shah">Ketan Shah</a></strong> is a partner in the Chicago office. </p> <hr /> <p>This article was edited by Kristi Essick, an executive editor in the Bay Area 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_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-c-heading--border___K8dj3_8032924 mdc-u-align-center">Explore a career with us</h5><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924 mdc-c-link-container--align-center___ar3mu_8032924"><a data-component="mdc-c-link" href="/careers/search-jobs" class="mdc-c-button___U4iY2_8032924 mdc-c-button--secondary___Boipq_8032924 mdc-c-button--size-large___jwpUy_8032924" 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_8032924">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_8032924 mdc-c-heading--title___5qyOB_8032924 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="/featured-insights/mckinsey-explainers/what-is-digital-twin-technology" class="mdc-c-link___lBbY1_8032924"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-what-0 { aspect-ratio: 16/9 }</style><img alt="Isometric style image of an airplane next to a digitized mirror of itself. 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They can reignite revenue growth and deepen resilience by deploying AI-powered digital twins."}},"sEODescription":{"value":"Complexity, COVID, and competition have upended supply chain organizations. Reignite revenue growth and deepen resilience by deploying AI-powered digital twins."},"displayDate":{"jsonValue":{"value":"2024-11-20T00:00:00Z"}},"body":{"value":"[[Audio 1]]\n[[DownloadsSidebar]]\n\u003cp\u003e\u003cstrong\u003eThe post-COVID-19 era has created\u003c/strong\u003e lasting fissures in the supply chain. Amid increasing globalization, rising customer expectations, and double-digit shipping growth,[[Footnote 1]] supply chain organizations\u0026mdash;not just manufacturers and suppliers but also the warehouses and transporters they rely on\u0026mdash;are under duress. They grapple with issues related to operational efficiency, demand forecasting, inventory management, and fulfillment. This complexity affects every part of the supply chain in every industry: retail, technology, automotive, industrial, food services, telecommunications, and more. The result is stalled growth and missed revenue opportunities.\u003c/p\u003e\n[[Sidebar Author]]\n\u003cp\u003eSeveral competing forces are exerting pressure on the supply chain: consumer demand for low-priced products delivered via fast-and-free shipping; rising wages for manufacturing, warehouse, and delivery employees; and murky visibility into future macroeconomic disruptions. McKinsey research shows that more than 90 percent of US consumers now expect two- to three-day delivery for purchases and one-third expect same-day delivery.[[Footnote 2]] And ever since the pandemic disrupted in-person sales, B2B companies expect their suppliers to offer omnichannel sales via online marketplaces, mobile, videoconferencing, and chat.[[Footnote 3]]\u003c/p\u003e\n\u003cp\u003eFulfilling these expectations is more challenging than ever. High labor prices\u0026mdash;including a more than 30 percent increase in warehousing wages between July 2020 and July 2024[[Footnote 4]]\u0026mdash;make it difficult to maintain low prices while meeting margins. \u003ca href=\"/capabilities/people-and-organizational-performance/our-insights/tradespeople-wanted-the-need-for-critical-trade-skills-in-the-us\"\u003eManufacturing labor shortages\u003c/a\u003e\u0026nbsp; undermine the ability to create steady inventory flows, while unexpected economic shocks such as recent inflation complicate demand forecasting. And even when the supply side is functioning well, fulfillment remains a challenge; warehouse storage rates remain constrained, causing products to reach recipients late.\u003c/p\u003e\n\u003ch2\u003eDigital twins could heal the supply chain\u003c/h2\u003e\n[[MostPopularArticles 5]]\n\u003cp\u003eUnder these circumstances, organizations that do not recalibrate their supply chain operations risk falling behind. \u003ca href=\"/featured-insights/mckinsey-explainers/what-is-digital-twin-technology\"\u003eDigital twins\u003c/a\u003e\u0026nbsp;can help with that recalibration. Leading companies are already turning to them to ensure their supply chains are flexible, agile, and responsive enough to overcome unexpected disruptions.\u003c/p\u003e\n\u003cp\u003eDigital twins are virtual replicas of an object, system, or process used to simulate potential situations and outcomes. Digital twins use real data (sometimes in masked or synthetic forms) to deliver analytical insights and visualizations. Many organizations use digital twins to optimize operations, plan scenarios, and aid \u003ca href=\"/featured-insights/mckinsey-explainers/what-is-decision-making\"\u003edecision making\u003c/a\u003e. Market analysis indicates the global market for digital twins will grow about 30 to 40 percent annually in the next few years, reaching $125 billion to $150 billion by 2032.[[Footnote 5]]\u003c/p\u003e\n\u003cp\u003eDigital twins can be used to model the interaction between physical and digital processes all along the supply chain\u0026mdash;from product ideation and manufacturing to warehousing and distribution, from in-store or online purchases to shipping and returns. Thus, digital twins paint a clear picture of an optimal end-to-end supply chain process. What\u0026rsquo;s more, paired with today\u0026rsquo;s advances in predictive AI, digital twins can become both predictive and prescriptive. They can predict future scenarios to suggest areas for improvement or growth, ultimately leading to a self-monitoring and self-healing supply chain. In other words, digital twins empower the switch from heuristic-based supply chain management to dynamic and granular optimization, providing a 360-degree view of value and performance leakage.\u003c/p\u003e\n\u003cp\u003eTo understand how a self-healing supply chain might work in practice, let\u0026rsquo;s look at one example: using digital twins, a retailer sets dynamic SKU-level safety stock targets for each fulfillment center that dynamically evolve with localized and seasonal demand patterns. Moreover, this granular optimization is applied not just to inventory management but also to every part of the end-to-end supply chain\u0026mdash;from procurement and product design to manufacturing and demand forecasting. For example, the retailer\u0026rsquo;s granular production planning could be done in coordination with downstream transportation decisions and inventory positioning. Dynamic planning might identify, for instance, a high-volume commodity item with cross-sell potential, where higher manufacturing costs for the item are offset by lower end-to-end logistics costs through bundled shipping and higher customer conversion. This type of complex predictive modeling is what digital twins do best. Typical results in such a scenario are up to a 20 percent improvement in fulfilling consumer promise (achieving the delivery date communicated to the consumer), a 10 percent reduction in labor costs, and a 5 percent revenue uplift. \u003c/p\u003e\n\u003ch2\u003eDigital twins optimize today\u0026rsquo;s SCM software\u003c/h2\u003e\n\u003cp\u003eToday\u0026rsquo;s supply chain management (SCM) software\u0026mdash;which includes a range of products, such as advanced planning and scheduling (APS) tools, warehouse management systems (WMS), and transportation management systems (TMS)\u0026mdash;has automated large parts of the supply chain in the past decade, dramatically streamlining how suppliers, buyers, and shippers intersect.\u003c/p\u003e\n\u003cp\u003eDigital twins can integrate with existing SCM tools, functioning as an innovation layer that sits on top of the tech stack. In this manner, digital twins can optimize data inputs into SCM tools, generating predictive analytics to address and respond to multiple potential scenarios. For example, a global OEM created a digital twin to optimize the policies it fed into its TMS platform for outbound logistics. As a result, the OEM reduced costs for freight and damages by 8 percent.\u003c/p\u003e\n\u003cp\u003eDigital twins help augment SCM tools in several ways:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eEnd-to-end connections:\u003c/em\u003e Digital twins can connect SCM tools throughout the supply chain to provide an integrated view of performance and up- and downstream decision impacts. This eliminates a siloed approach in which each tool only optimizes its local variables, with little coordination among them. For example, one retailer used digital twins to connect their planning, inventory deployment, and transportation management tools.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eResiliency in dynamic markets:\u003c/em\u003e As volatility continues to increase post-COVID-19, supply chain operators must continually update their policies due to both fluctuating demand and intermittent supply shocks, such as port disruptions or availability of materials. When combined with digital twins, SCM tools provide real-time visibility into granular performance, paired with predictive and prescriptive analytics to dynamically identify risks and recommend policy changes for rapid resolution. For example, one OEM used automated sense-and-respond digital-twin capabilities to identify shifts in carrier performance and surcharges, effectively reducing last-mile transportation costs by 5 percent.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eMultiple objectives:\u003c/em\u003e Digital twins can optimize across competing priorities and complex constraints for rapid response to market changes. For example, one automotive OEM used digital twins to dynamically shape demand based on shifting supply availability and operational complexity, collectively solving across both sales and operational objectives.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eVariability:\u003c/em\u003e Digital twins combined with SCM tools can test for a distribution of potential scenarios by analyzing metrics, such as lead time, demand, and supplier reliability, while also considering what-if outcomes. For instance, a consumer-packaged-goods company measured variable demand and labor in its warehouse and identified the opportunity to reduce total distribution center costs by 15 percent. This exemplifies network resiliency.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003eA deep dive into digital twins\u003c/h2\u003e\n\u003cp\u003eSeeing digital twins in action is the best way to understand how they can deliver value at key points in the supply chain. Explore the below potential use cases to see how digital twins can solve real pain points throughout the supply chain to improve efficiency and resiliency.\u003c/p\u003e\n\u003ch4 style=\"text-align: center;\"\u003eForecasting and demand planning\u003c/h4\u003e\n[[image 1]]\n[[Accordion 1]]\n\u003ch4 style=\"text-align: center;\"\u003eSourcing and production planning\u003c/h4\u003e\n[[image 2]]\n[[Accordion 2]]\n\u003ch4 style=\"text-align: center;\"\u003eDistribution center network\u003c/h4\u003e\n[[image 3]]\n[[Accordion 3]]\n\u003ch4 style=\"text-align: center;\"\u003eEnd customers\u003c/h4\u003e\n[[image 4]]\n[[Accordion 4]]\n\u003ch2\u003eUnderstanding the benefits of digital twins\u003c/h2\u003e\n\u003cp\u003eSupply chain organizations are leveraging digital twins to optimize both their long-term strategies and everyday operations. The most common ways we have seen supply chain companies deploy digital twins are for inventory positioning and forecasting, to manage the flow of goods within the four walls of warehouses and factories, and to aid in production planning. But these are just a few of the ways digital twins are being implemented throughout the supply chain. No matter how digital twins are used, the benefits are clear:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eStrategic:\u003c/em\u003e Digital twins can derisk long-term planning and broader digital transformations by simulating potential outcomes. This kind of what-if predictive modeling gives companies confidence in the end-to-end impact of their strategic plans. For example, a retailer used a granular digital twin of its distribution network to test the bottom-up implications of a new design for its distribution center. The company had previously used top-down analysis to determine the size and location of a potential new cross-dock. But when teams used a digital twin to model all the potential constraints of that cross-dock placement, they found they could resize and relocate it on 50 percent less real estate without compromising functionality.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eOperational:\u003c/em\u003e Beyond informing one-time strategy decisions, digital twins can function as \u0026ldquo;one model to rule them all,\u0026rdquo; optimizing daily decisioning across different operations. In other words, rather than a system of disjointed predictive models, a digital twin can combine many models for integrated forecasting and decision making\u0026mdash;dynamically comparing competing trade-offs across the supply chain to suggest granular operational changes. For example, the same retailer used its digital twin to not only optimize its cross-dock footprint in its distribution center but also to optimize its daily inventory positioning decisions\u0026mdash;forecasting weekly days-of-supply policies to balance cost, service levels, and sustainability. The result was a 10 percent improvement in regional distribution center utilization and 5 percent reduction in fulfillment costs.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003eGetting started with digital twins\u003c/h2\u003e\n\u003cp\u003eWhile supply chain organizations recognize the value digital twins can provide, few have implemented them at scale. Unlike many SCM solutions that are plug and play, digital twins may require a customized build to implement. Because digital twins routinely ingest large quantities of proprietary, masked, or synthetic data, they are almost always custom-built, which takes considerable time and investment. Supply chain organizations must have in-house data science and development teams capable of building digital twins that use advanced AI algorithms, or partner with outside vendors expert in these areas.\u003c/p\u003e\n\u003cp\u003eOrganizations that aspire to embark on the digital-twin journey should focus on five key tenets for success:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eNorth Star road map:\u003c/em\u003e Determine the vision for a future supply chain operation built on data and technology. Identify end-to-end use cases that support the North Star vision and then build a road map of use cases by prioritizing for impact\u0026mdash;profit and loss or delivery\u0026mdash;and feasibility. Typically, companies first prioritize use cases with quick speed-to-impact to prove value early in the journey.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eData visibility:\u003c/em\u003e For each use case in the end-to-end road map, identify the data inputs and outputs needed. Build a complementary road map for the organization\u0026rsquo;s data products that supports the use case road map, prioritizing data elements that will be shared across multiple high-impact implementations. Develop these data products iteratively with agile development. To get started, digital twins require a semiregular pipeline of digitized and standardized data, but it\u0026rsquo;s possible to fill data gaps with more static sources such as, for example, average throughput in a warehouse versus daily staffing levels.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eTechnology architecture:\u003c/em\u003e Digital-twin architecture is largely composed of existing data sources and technology, stitched together via APIs and middleware. Typically, a marginal increase in compute capacity is required to support a twin, so ensure that tech teams have the flexibility to scale current compute resources as needed.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eTalent:\u003c/em\u003e Assess the skill levels of team members needed to deliver digital twins, including product managers, data engineers, data scientists, user interface/user experience designers, and full-stack developers. Digital twins are most effectively delivered with agile methodologies for rapid development cycles, so product managers may require agile upskilling and training.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eOptimization and simulation:\u003c/em\u003e Identify the company\u0026rsquo;s first digital twin use case and deploy it. Build on the data products to create optimization and simulation modules that capture use case impact. Then, iteratively expand use cases and combine modules for integrated simulations and end-to-end optimization. Note that teams can start developing simulation and optimization modules before the data product is complete to capture early impact and then integrate these modules later.\u003c/li\u003e\n\u003c/ul\u003e\n\u003chr /\u003e\n\u003cp\u003eEnd-to-end supply chain optimization requires more than just implementing technology; it also requires a mindset shift at the leadership level and throughout the organization. Internally, companies that use digital twins must endeavor to eliminate internal silos and replace piecemeal institutional knowledge with data-driven decisioning. Externally, companies should carefully analyze their roles in the interconnected global supply chain. In an increasingly complex and interconnected world, organizations across the supply chain can use digital twins to predict potential disruptions and what-if scenarios that could affect their businesses. No one can predict the next pandemic, war, or economic shock with certainty, but digital twins can help companies react and adapt to these eventualities.\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":true},"tableOfContentsTitle":{"value":"TABLE OF CONTENTS"},"accessStatus":{"targetItem":{"key":{"value":"RegisteredUsers"},"value":{"value":"Registered Users"}}},"articleType":{"targetItem":{"displayName":"Article"}},"hasSpecialReport":{"boolValue":false},"contentType":{"targetItem":{"displayName":"Article"}},"sourcePublication":{"targetItem":null},"externalPublication":{"value":""},"excludeFromClientLink":{"boolValue":false},"originalPublishDate":{"jsonValue":{"value":"2024-11-20T00:00:00Z"}},"footnotes":{"value":"\u003col\u003e\n \u003cli\u003e\u0026ldquo;Air Cargo Market Analysis,\u0026rdquo; International Air Transport Association, March 2024.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003e\u003ca href=\"/industries/retail/our-insights/retail-speaks-seven-imperatives-for-the-industry\"\u003eRetail speaks: Seven imperatives for the industry\u003c/a\u003e,\u003c/em\u003e McKinsey and the Retail Industry Leaders Association, March 10, 2021.\u003c/li\u003e\n \u003cli\u003e\u0026ldquo;\u003ca href=\"/capabilities/growth-marketing-and-sales/our-insights/b2b-sales-omnichannel-everywhere-every-time\"\u003eB2B sales: Omnichannel everywhere, every time\u003c/a\u003e,\u0026rdquo; McKinsey, December 15, 2021.\u003c/li\u003e\n \u003cli\u003e\u0026ldquo;Employment statistics,\u0026rdquo; US Bureau of Labor Statistics, July 2024.\u003c/li\u003e\n \u003cli\u003eAverage growth calculated from digital twin market reports from Roots Analysis (41 percent CAGR for 2024\u0026ndash;32 to reach $150 billion in 2032), December 2023; and GMI Insights (33 percent CAGR for 2024\u0026ndash;32 to reach $125 billion in 2032), March 2024.\u003c/li\u003e\n\u003c/ol\u003e"},"contributoryPractice":{"targetItems":[{"displayName":"McKinsey Digital"},{"displayName":"QuantumBlack, AI by McKinsey"}]},"aboutTheAuthors":{"value":"\u003cp\u003e\u003cstrong\u003e\u003ca href=\"/our-people/alberto-oca\"\u003eAlberto Oca\u003c/a\u003e\u003c/strong\u003e is a partner in McKinsey\u0026rsquo;s Atlanta office, where \u003cstrong\u003eLauren O\u0026rsquo;Neil\u003c/strong\u003e is an associate partner; \u003ca href=\"/our-people/alex-cosmas\"\u003e\u003cstrong\u003eAlex Cosmas\u003c/strong\u003e\u003c/a\u003e\u0026nbsp;is a partner in the New York office; \u003cstrong\u003e\u003ca href=\"/our-people/cenk-tunasar\"\u003eCenk Tunasar\u003c/a\u003e\u003c/strong\u003e is a partner in the Boston office; and \u003cstrong\u003e\u003ca href=\"/our-people/ketan-shah\"\u003eKetan Shah\u003c/a\u003e\u003c/strong\u003e is a partner in the Chicago office. \u003c/p\u003e\n\u003chr /\u003e\n\u003cp\u003eThis article was edited by Kristi Essick, an executive editor in the Bay Area office.\n\u003c/p\u003e"},"authors":{"targetItems":[{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"38988940138F457EB208D6B7EA7E98A9","name":"Alberto Oca","authorTitle":{"value":"Alberto Oca"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/alberto oca/alberto_oca_standard_profile_1536x1152.jpg","alt":"Alberto Oca"},"emailLinks":{"value":"Alberto_Oca@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/albertooca/"},"description":{"value":"Advises clients in consumer, retail, pharma, and private equity in setting and implementing the digital supply chain strategy to transform operational performance and capabilities"},"locations":{"targetItems":[{"name":"Atlanta","displayName":"Atlanta"}]},"firmTitle":{"value":"Partner"},"thumbnailImage":{"alt":"Alberto Oca","src":"/~/media/mckinsey/our people/alberto oca/alberto_oca_headshot_988x741.jpg"},"url":{"path":"/our-people/alberto-oca"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"0E0B9B5A182C46F1B3F997669E71ED82","name":"Alex Cosmas","authorTitle":{"value":"Alex Cosmas"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/alex cosmas/alex cosmas-15140_fc-mask_profile_1536x1152.png","alt":""},"emailLinks":{"value":"Alex_Cosmas@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/alexcosmas"},"description":{"value":"Helps travel and logistics companies capture real value from data science and artificial intelligence"},"locations":{"targetItems":[{"name":"New York","displayName":"New York"}]},"firmTitle":{"value":"Partner"},"thumbnailImage":{"alt":"","src":"/~/media/mckinsey/our people/alex cosmas/alex cosmas-15140_fc-mask_headshot_988x741.png"},"url":{"path":"/our-people/alex-cosmas"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"CA7D5BA79389467D9CB0887524E15549","name":"Cenk Tunasar","authorTitle":{"value":"Cenk Tunasar"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/cenk tunasar/cenk_tunasar_standard_profile_1536x1152.jpg","alt":"Cenk Tunasar"},"emailLinks":{"value":"Cenk_Tunasar@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/cenk-tunasar-5200101/"},"description":{"value":"Helps organizations use advanced analytics tools and artificial intelligence to dramatically improve their performance "},"locations":{"targetItems":[{"name":"Boston","displayName":"Boston"}]},"firmTitle":{"value":"Partner"},"thumbnailImage":{"alt":"Cenk Tunasar","src":"/~/media/mckinsey/our people/cenk tunasar/cenk_tunasar_headshot_988x741.jpg"},"url":{"path":"/our-people/cenk-tunasar"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"A3214FCFCE8F4CF8800914046AB56815","name":"Ketan Shah","authorTitle":{"value":"Ketan Shah"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/ketan shah/ketan-shah_profile_1536x1152.jpg","alt":"Ketan 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O’Neil"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[]}}]},"interactiveToUse":{"targetItem":null},"enableArticleComponents":{"boolValue":false},"relatedArticles":{"targetItems":[{"sourcePublication":{"targetItem":null},"publicationSource":null,"externalPublication":{"value":""},"title":{"value":"What is digital-twin technology?"},"url":{"path":"/featured-insights/mckinsey-explainers/what-is-digital-twin-technology"},"eyebrow":{"targetItem":{"name":"Article"}},"articleType":{"targetItem":{"name":"Article"}},"contentType":{"targetItem":{"name":"Article"}},"description":{"value":"A digital twin is a digital replica of a physical object, person, system, or process, contextualized in a digital version of its environment. 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