As companies adopt more digital technologies, such as collaborative robots, artificial intelligence, and analytics, the way their supply chains function will radically change. So too will the nature of work itself.
It's no secret that robotics, edge computing, cognitive technologies, and other innovations are creating new, previously unthinkable capabilities in modern supply chains, such as 24/7 connectivity, enhanced visibility, and efficiency. This level of innovation will only explode as even more of these innovative technologies transform traditional, linear supply chains into a set of dynamic networks known as digital supply networks.
It's also no secret that the workforce in these digital supply networks will face urgent and systemic disruptions as technological adoption increases. Employees throughout an enterprise's supply chain will likely be using technologies that they've never heard of before—or are new to the market. Meanwhile, the success of the business may hinge on the ability of the workforce to adapt and integrate new technologies in just a matter of months. As digital supply networks (DSNs) rapidly evolve, develop, and advance with technology, it's time for organizations to ask a key question: What role does talent play in the future of the supply chain, and how can the supply chain workforce adapt?Â
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[Figure 1] Four-tiered model of how technology will change work in DSNsEnlarge this image
Deloitte's recent report with MHI, the 2018 MHI Annual Industry Report, shows that shifting talent skills and needs can offer huge opportunities and some notable risks for the supply chain.1 Sixty-three percent of supply chain executives in our survey noted that hiring and retaining a skilled workforce was a top challenge. Even beyond retention, 70 percent said their current workforce lacked the technology-related skills to succeed in the future.
While there are often doom-and-gloom portrayals of a coming "robot apocalypse," properly prepared organizations and their employees stand to reap huge benefits from the advent of emerging digital technologies as people and machines enter an exciting era of collaboration. Leaders can get a head start on planning for these changes by identifying where they are in the journey toward adopting digital technologies and understanding how technology may impact their supply chain talent's roles and responsibilities. This understanding will help them prepare for the future when certain roles may be improved or augmented, replaced, or transformed into entirely new roles.Â
To help companies better prepare for these changes, Deloitte has created a four-tiered model of how supply chain employees' roles may evolve as the organization adopts increasingly smart technologies. (See Figure 1.) This model begins with companies adopting new digital technologies. The middle stages occur as the technologies change how the company is organized and what the worker's responsibilities and tasks are. At the very top tier, the technology enables a change to the organization's core business model. It is important to note that the tiers are not mutually exclusive, and that organizations can be in different tiers in different parts of their business at the same time.
Tier 4:Adopting the TechnologyÂ
In Tier 4, workers first learn to use the new connected and cognitive technologies. Roles in this tier generally remain the same, but workers accomplish tasks more quickly and effectively due to the technologies' ability to improve efficiency and accuracy and heighten abilities in general.Â
For example, in 2015 the French sporting goods retailer Decathlon implemented real-time inventory tracking in over 400 stores.2 To accomplish this goal, the retailer used new, but relatively simple equipment: radio-frequency identification (RFID) tags and scanners. An RFID reader was integrated into existing checkout scanners to conduct sales transactions and track inventory levels. Sales grew by 2.5 percent as visibility increased and stock shrinkage fell.3 The system did not significantly change how the workers did their jobs. While they did use a new piece of equipment to scan the RFID tag, the core business process remained largely the same. This is an example of a new technology application bringing new value to the business without significantly changing the worker's job or role.
As the Decathlon example shows, it's key at this stage to learn these technologies front-to-back and to be able to apply them creatively while compensating for their shortcomings and accentuating their strengths. Keeping training courses and methods up-to-date to accomplish this can be a huge challenge because technology is changing so fast. But new technologies can also provide new training opportunities. Augmented reality (AR), for example, can create immersive training environments that are easily and inexpensively updated. NASA is an interesting example of an organization that is already experimenting with AR to provide realistic training for in-flight refueling procedures.4 AR technologies could, similarly, help supply chain practitioners visualize exactly where a product is in the warehouse or teach them how to use heavy machinery and robotic tools in a safe, controlled environment.
Tier 3:Adapting the organizationÂ
By Tier 3, the pace of technological change starts to prompt changes in how teams organize and communicate. In traditional supply chains, groups have been organized by function, such as product development, procurement, and marketing. But in a digital supply network where information is moving in real time, these groups now need more integration and the ability to respond to new information quickly.Â
Additionally, the shift to digital supply networks may require organizations to emphasize new roles. For example, they may need employees to analyze the wealth of data created by the DSN. Indeed advanced technology jobs, such as data scientists and robotics experts, are expected to grow in importance as acting upon data in the DSN becomes a central feature of the "future of work." Companies that employ data scientists, robotics experts, and other advanced technology professionals will be able to make the most of the vast amounts of data the DSN creates, which in turn will give them a competitive advantage. The creation of new roles may require companies to turn to nontraditional sources of talent—like the gig economy, new partners, or remote workers—to help fill talent needs that the business itself isn't yet prepared to address internally.
To make the most out of digitally enabled supply networks, employees will need to work across silos—and even with external stakeholders, including customers and suppliers. The Deloitte and MIT Sloan Management Review study, "Achieving Digital Maturity," for example, found that 71 percent of digitally maturing organizations are increasingly organized around cross-functional teams.5 Working cross functionally can help supply networks consider production processes holistically and explore how new roles can interact.Â
Tier 2:Shaping the value-added worker
Tier 2 is characterized by "human-machine teaming," where technology frees human workers entirely from some tasks, allowing them to pursue new ones that can create more value. Technology generally takes over predictable, analytical tasks, such as processing invoices, for which new "robotic colleagues" are typically better suited than humans. As a result, human workers can be more creative, relying on intuition, storytelling, and other attributes to generate further insight into how the organization can create value and succeed. This type of work could include improving high-level strategy, exploring new opportunities for technological integration, or working hands-on with suppliers and other stakeholders to build relationships.Â
But which value-added tasks should an organization prioritize having its workers do? The answer may not yet be clear, but relationship-building and "soft skills" are increasingly essential to top performance.
Tier 1:Evolving business models
In Tier 1, supply chain strategies continue to evolve. As entirely new roles and tasks unfold within the organization, new business opportunities are discovered and created. These new business opportunities help foster value-added workers and can even lead an organization to overhaul entire business models. This development then commences a cycle: As the business model evolves, new roles arise for that model. These new roles, in turn, help create new opportunities for future business model creation and evolution.Â
Focus on the human
It can be difficult to figure out how to start creating a digital supply chain and what that means for employees' jobs and responsibilities. Yet technological adoption and a tier-based analysis can often be simpler than it may seem. While the tiers can be helpful to understanding the future of the DSN and the future of the workforce, companies also need to translate that knowledge into specific actions.Â
Companies can consider using the following leading practices as their DSNs advance:Â
Determine how—and which—technologies support strategic goals:Â As you work toward creating a digital supply network, remember that technology adoption itself isn't a goal—improving your business is. Think of technology as something that supports the business and helps employees better perform the jobs of the future, not as an end in and of itself.
Plan for an increasingly multidisciplinary workforce:Â As companies develop their talent, they need to make sure they emphasize problem-solving skills and having an open, creative mindset as much as (or even more than) they would specific technical skills. For example, companies traditionally have wanted buyers who are skilled in transaction processing; now they may be looking for buyers who understand commodity markets and are skilled in negotiation. To get these multidisciplinary skills, they may need to extend the workforce outside of the four walls of the organization to include new geographies, remote workers, and "gig economy" workers.Â
Emphasize the human—and the machine: As machines take on certain responsibilities and tasks that people used to perform, organizations should carefully redeploy workers into roles where they can interact with other people, identify business opportunities, and build relationships. This may require looking outside traditional talent pipelines or pursuing talent without a traditional STEM (science, technology, engineering, and math) or supply-chain background—and being aware of exactly what machines excel at, too.Â
Reexamine human capital strategy while encouraging new ideas: Because DSNs use new digital technologies and have a less linear structure, they typically have greater agility and more visibility than traditional supply chains. This allows them to be more flexible and adaptable. Talent should be the same way: Future workers need to be radically different than they are now. Organizations that encourage human workers to be flexible, adapt their skills, and embrace change could reap huge benefits in the uncharted future. Skills like creativity, relationship-building, and problem-solving are universally useful in the future of work; they allow employees to approach new tasks confidently, learn skills quickly, and recognize how they fit into the broader business. Â
Smart planning
There is no one-size-fits-all approach to creating a DSN. But the future of work and the dawning era of human-machine collaboration demand that companies be smart about what's next or they may risk being left behind by better prepared competitors. A tiered approach to technology adoption in the DSN and open-minded leadership—that displays the very same "soft skills" and adaptability necessary for the future workforce—can help savvy organizations reap benefits.Â
By organizing technological adoption in the DSN into tiers and the relationship to the human workforce in the same way, supply chain leaders can begin to understand how to evolve their future business and talent structures effectively. If they fail to do this sort of planning, they may risk unpleasant surprises, challenging adjustments, and lost productivity. The intersection between the future workforce and future technologies in the digital supply network must now become a priority.
Nobody can predict the future. The digital technologies currently reshaping the DSN would have been almost unthinkable in scale, scope, and utility even a decade ago. Organizations can, however, use history, sound reasoning, creativity, and communication to prepare their structure and workforce for the future that awaits them. By staying flexible and continually reevaluating priorities, needs, and tactics to execute broader business strategy, companies with advanced DSNs and equally advanced workforces can be better prepared for the demands of the future.Â
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Notes: 1. MHI and Deloitte, "The 2018 MHI Annual Report: Overcoming Barriers to NextGen Supply Chain Innovation," 2018, https://www.mhi.org/publications/report. 2. Freddie Roberts, "Delivering the goods: Eight examples of IoT transforming supply chain," Internet of Business, November 14, 2016, https://internetofbusiness.com/8-real-life-examples-iot-supply-chain/. 3. Claire Swedberg, "Decathlon sees sales rise and shrinkage drop, aided by RFID," RFID Journal, December 7, 2015, https://www.rfidjournal.com/articles/view?13815. 4. Peter Merlin, "Fused reality: Making the imagined seem real," NASA, September 29, 2015, https://www.nasa.gov/centers/armstrong/features/fused_reality.html. 5. Gerald C. Kane, Doug Palmer, Anh Nguyen Phillips, David Kiron, and Natasha Buckley, "Achieving digital maturity: Adapting your company to a changing world," MIT Sloan Management Review, July 13, 2017, https://sloanreview.mit.edu/projects/achieving-digital-maturity/.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."
Progress in generative AI (GenAI) is poised to impact business procurement processes through advancements in three areas—agentic reasoning, multimodality, and AI agents—according to Gartner Inc.
Those functions will redefine how procurement operates and significantly impact the agendas of chief procurement officers (CPOs). And 72% of procurement leaders are already prioritizing the integration of GenAI into their strategies, thus highlighting the recognition of its potential to drive significant improvements in efficiency and effectiveness, Gartner found in a survey conducted in July, 2024, with 258 global respondents.
Gartner defined the new functions as follows:
Agentic reasoning in GenAI allows for advanced decision-making processes that mimic human-like cognition. This capability will enable procurement functions to leverage GenAI to analyze complex scenarios and make informed decisions with greater accuracy and speed.
Multimodality refers to the ability of GenAI to process and integrate multiple forms of data, such as text, images, and audio. This will make GenAI more intuitively consumable to users and enhance procurement's ability to gather and analyze diverse information sources, leading to more comprehensive insights and better-informed strategies.
AI agents are autonomous systems that can perform tasks and make decisions on behalf of human operators. In procurement, these agents will automate procurement tasks and activities, freeing up human resources to focus on strategic initiatives, complex problem-solving and edge cases.
As CPOs look to maximize the value of GenAI in procurement, the study recommended three starting points: double down on data governance, develop and incorporate privacy standards into contracts, and increase procurement thresholds.
“These advancements will usher procurement into an era where the distance between ideas, insights, and actions will shorten rapidly,” Ryan Polk, senior director analyst in Gartner’s Supply Chain practice, said in a release. "Procurement leaders who build their foundation now through a focus on data quality, privacy and risk management have the potential to reap new levels of productivity and strategic value from the technology."
Businesses are cautiously optimistic as peak holiday shipping season draws near, with many anticipating year-over-year sales increases as they continue to battle challenging supply chain conditions.
That’s according to the DHL 2024 Peak Season Shipping Survey, released today by express shipping service provider DHL Express U.S. The company surveyed small and medium-sized enterprises (SMEs) to gauge their holiday business outlook compared to last year and found that a mix of optimism and “strategic caution” prevail ahead of this year’s peak.
Nearly half (48%) of the SMEs surveyed said they expect higher holiday sales compared to 2023, while 44% said they expect sales to remain on par with last year, and just 8% said they foresee a decline. Respondents said the main challenges to hitting those goals are supply chain problems (35%), inflation and fluctuating consumer demand (34%), staffing (16%), and inventory challenges (14%).
But respondents said they have strategies in place to tackle those issues. Many said they began preparing for holiday season earlier this year—with 45% saying they started planning in Q2 or earlier, up from 39% last year. Other strategies include expanding into international markets (35%) and leveraging holiday discounts (32%).
Sixty percent of respondents said they will prioritize personalized customer service as a way to enhance customer interactions and loyalty this year. Still others said they will invest in enhanced web and mobile experiences (23%) and eco-friendly practices (13%) to draw customers this holiday season.
The practice consists of 5,000 professionals from Accenture and from Avanade—the consulting firm’s joint venture with Microsoft. They will be supported by Microsoft product specialists who will work closely with the Accenture Center for Advanced AI. Together, that group will collaborate on AI and Copilot agent templates, extensions, plugins, and connectors to help organizations leverage their data and gen AI to reduce costs, improve efficiencies and drive growth, they said on Thursday.
Accenture and Avanade say they have already developed some AI tools for these applications. For example, a supplier discovery and risk agent can deliver real-time market insights, agile supply chain responses, and better vendor selection, which could result in up to 15% cost savings. And a procure-to-pay agent could improve efficiency by up to 40% and enhance vendor relations and satisfaction by addressing urgent payment requirements and avoiding disruptions of key services
Likewise, they have also built solutions for clients using Microsoft 365 Copilot technology. For example, they have created Copilots for a variety of industries and functions including finance, manufacturing, supply chain, retail, and consumer goods and healthcare.
Another part of the new practice will be educating clients how to use the technology, using an “Azure Generative AI Engineer Nanodegree program” to teach users how to design, build, and operationalize AI-driven applications on Azure, Microsoft’s cloud computing platform. The online classes will teach learners how to use AI models to solve real-world problems through automation, data insights, and generative AI solutions, the firms said.
“We are pleased to deepen our collaboration with Accenture to help our mutual customers develop AI-first business processes responsibly and securely, while helping them drive market differentiation,” Judson Althoff, executive vice president and chief commercial officer at Microsoft, said in a release. “By bringing together Copilots and human ambition, paired with the autonomous capabilities of an agent, we can accelerate AI transformation for organizations across industries and help them realize successful business outcomes through pragmatic innovation.”
That challenge is one of the reasons that fewer shoppers overall are satisfied with their shopping experiences lately, Lincolnshire, Illinois-based Zebra said in its “17th Annual Global Shopper Study.” While 85% of shoppers last year were satisfied with both the in-store and online experiences, only 81% in 2024 are satisfied with the in-store experience and just 79% with online shopping.
In response, most retailers (78%) say they are investing in technology tools that can help both frontline workers and those watching operations from behind the scenes to minimize theft and loss, Zebra said.
Just 38% of retailers currently use artificial intelligence-based prescriptive analytics for loss prevention, but a much larger 50% say they plan to use it in the next one to three years. Retailers also said they plan to invest in self-checkout cameras and sensors (45%), computer vision (46%), and RFID tags and readers (42%) within the next three years to help with loss prevention.
Those strategies could help improve the brick-and-mortar shopping experience, as 78% of shoppers say it’s annoying when products are locked up or secured within cases. Part of that frustration, according to consumers, is fueled by the extra time it takes to find an associate to them unlock those cases. Seventy percent of consumers say they have trouble finding sales associates to help them during in-store shopping. In response, some just walk out; one in five shoppers has left a store without getting what they needed because a retail associate wasn’t available to help, an increase over the past two years.
Additional areas of frustrations identified by retailers and associates include:
The difficulty of implementing "click and collect" or in-story returns, despite high shopper demand for them;
The struggle to confirm current inventory and pricing;
Lingering labor shortages; and
Increasing loss incidents.
“Many retailers are laying the groundwork to build a modern store experience,” Matt Guiste, Global Retail Technology Strategist, Zebra Technologies, said in a release. “They are investing in mobile and intelligent automation technologies to help inform operational decisions and enable associates to do the things that keep shoppers happy.”
The survey was administered online by Azure Knowledge Corporation and included 4,200 adult shoppers (age 18+), decision-makers, and associates, who replied to questions about the topics of shopper experience, device and technology usage, and delivery and fulfillment in store and online.