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Four years of supply chain chaos have left C-suites tired of playing defense

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This is an excerpt of the original article. It was written for the July-August 2024 edition of Supply Chain Management Review. The full article is available to current subscribers.

July-August 2024

Artificial intelligence is everywhere these days. But what if it isn’t? I would guess that at least 50%, and probably closer to 70%, of the article pitches I receive these days involve AI. Most conversations I’ve had at conferences this year have at least touched on AI and its impact on the supply chain. Almost every technology company touts its AI-infused software. It seems that AI is not only mainstream, it’s Main Street.
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The sense of resolve out there seems at first counterintuitive, given the holding pattern of weak demand and continued uncertainty, even after COVID. Inflation, China de-risking, the brutality of Ukraine and Gaza, attacks on Suez shipping, Panama Canal drought, hacked data and ransomware demands—another day, another headline scare. That said, many of the broad market indicators driving demand and supply chain growth are positive. Despite a temptation to preserve capital and wait for some catalyst to provide greater market clarity, businesses are also wary of waiting too long; volatility may also prove resilient. And in the meantime, supply chain complexity is straining conventional business-to-business (B2B) models run on manual processes, spreadsheets and legacy software. Now may be just the time to shift focus from defensive resilience to building a more proactive set of capabilities with the same tools, to work with the market environment they have, not the one they wish they had. The greater risk may lie with inaction.

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Sorry, but your login has failed. Please recheck your login information and resubmit. If your subscription has expired, renew here.

From the July-August 2024 edition of Supply Chain Management Review.

July-August 2024

Artificial intelligence is everywhere these days. But what if it isn’t? I would guess that at least 50%, and probably closer to 70%, of the article pitches I receive these days involve AI. Most conversations I’ve…
Browse this issue archive.
Access your online digital edition.
Download a PDF file of the July-August 2024 issue.

The sense of resolve out there seems at first counterintuitive, given the holding pattern of weak demand and continued uncertainty, even after COVID. Inflation, China de-risking, the brutality of Ukraine and Gaza, attacks on Suez shipping, Panama Canal drought, hacked data and ransomware demands—another day, another headline scare.

That said, many of the broad market indicators driving demand and supply chain growth are positive: the roiling supply-demand dislocation from lockdowns and climate events has eased; interest rates appear to be stabilizing at around 3%-5% across OECD countries with inflation moderating, unemployment holding steady around 4%-6% and global GDP growth forecast in the 3% range for 2024-2025. On the supply side, investments in digital optimization, automation and process improvements have also made supply chains more resilient; end-to-end visibility enables faster, more agile response to disruption and sharper decision-making to boost performance, manage risk and control costs.

Despite a temptation to preserve capital and wait for some catalyst to provide greater market clarity, businesses are also wary of waiting too long; volatility may also prove resilient. And in the meantime, supply chain complexity is straining conventional business-to-business (B2B) models run on manual processes, spreadsheets and legacy software. Customers are demanding on-time/in-full reliability; compliance requirements around trade and sustainability are expanding. Wage, input and logistics cost pressures must be managed. Companies sense opportunity during this period of relatively weak demand and slower orders. Now may be just the time to shift focus from defensive resilience to building a more proactive set of capabilities with the same tools, to work with the market environment they have, not the one they wish they had. The greater risk may lie with inaction.

Create your own future

The buoyant mood reflected in last year’s Kearney Supply Chain Institute/Amazon Web Services survey of chief operating officers has moderated somewhat in the 2024 survey just released. Given recent macroeconomic, trade and geopolitical uncertainties, the share of respondents forecasting robust revenue growth for their companies—in the 10%-20% range—for the coming 12 months slipped from 63% to a still significant 38%, nearly half of those forecasting growth higher than 15%.

In 2024 COOs are prioritizing investments in digital, automation and AI, mainly in warehouse automation, AI/ML, Internet of Things (IoT) visibility and risk monitoring; resilience is a top priority for 56% of respondents, with 85% of those actively recalibrating their firms’ manufacturing footprints, in many cases involving nearshoring or reshoring to manage risk, and re-evaluating supplier relationships in the interest of resilience and/or sustainability.

COOs are allocating significant resources to attracting new customers and developing new channels via innovation, operational efficiencies and new products. At the same time, they are clear-eyed in their assessment of market headwinds. They see geopolitical instability as the greatest external supply chain risk and rank slow organizational decision-making as the biggest internal obstacle.

Underlying all strategic and investment decision-making, cost considerations loom large. COOs are prioritizing initiatives generating the quickest return on investment (ROI) through cost savings, such as equipment, maintenance and logistics costs. Top-of-mind initiatives include reducing reactive maintenance costs; improving statistical forecasting focused on key drivers; and optimizing the organization’s distribution strategy. Some priorities, like changing the manufacturing footprint, require complex analysis and difficult trade-offs among labor, energy, tax, and other cost impacts.

Resilience remains an organizational imperative. The product-at-all-costs mindset that saw many organizations overpaying to reduce supply chain risk and maintain stocking levels has given way to single-sourcing agreements and lean inventory arrangements. And while COOs are still open to keeping or moving manufacturing operations and transportation onshore to optimize quality control or delivery service performance, cost is receiving a heavier weight relative to risk management this year.

It’s time to rewire

Conventional supply chain models tend to reflect the times in which they’re developed and the supporting technologies then available. Most originated in the 1990s, as globalization was on the rise, and were designed for reliability, low cost and a predictable operating environment.

Most goods trade entailed predictable, high-volume business-to-business (B2B) shipments driven by longstanding supplier, vendor and customer relationships. Demand fluctuated within relatively narrow ranges. Merchandise was pushed out to large regional distribution centers for incremental sales into primary and secondary markets. Shipment track and trace was based on completed EDI transaction steps in the order process.

The model has steadily broken down over the past two decades as global sourcing patterns, just-in-time manufacturing and omnichannel e-commerce have steadily extended supply chain length and complexity. Then came the severe supply-demand disruption from COVID, compounded by climate. Environmental and sustainability measurement and reporting compliance objectives—in particular tracking and reporting of scope 3 supplier and vendor emissions—now promise further end-to-end challenges.

Companies have benefited from lessons learned as the pandemic severely stress-tested supply chains and accelerated the development of modular, software-based freight technology solutions. Resulting efficiencies from optimization and automation now demand accelerated, even dynamic, implementation through connectivity and collaboration among partners.

Technology comes to the rescue

Global proliferation of data centers and increased processing power from advanced chipsets have brought big data, AI, and machine learning capability to more businesses, more quickly, at lower cost, than ever before. Fully integrated real-time, end-to-end, actionable visibility is suddenly within reach, as:

  • AI and ML deliver instant, continuously updated data, analysis, predictive insights, prescriptive recommendations and control tower visualizations in near-real time;
  • Risk monitoring continuously scans the internal supply chain network—workflow, status and performance of people, physical facilities and equipment—and then incorporates partner reporting and external contextual data, to sense disruption early;
  • Mathematical optimization simplifies, prioritizes and automates workflow at the strategic, tactical, and operational levels; and
  • Distributed ledger technologies such as blockchain securely track goods, documents and payments, report and verify SKU-level provenance, and automate fulfillment/payment under smart contracts.

Suddenly it becomes easier to envision new end-to-end possibilities, building on the same capabilities put in place earlier during COVID to add resilience. The added processing and analytic capacity provide a foundation for altogether new, growth-focused supply chain configurations. 

Why not, for example, embed sustainability objectives within the procurement and logistics functions, where suppliers and logistics vendors are evaluated and selected? Or embed cybersecurity response within the supply chain where some of the most serious threats reside, alongside the most effective system monitoring and onboarding safeguards? Or build product redesign into a nearshoring strategy that simplifies portfolios, bypasses scarce materials and questionable suppliers and eliminates costly assembly steps customers may not even need or want?

Some examples of digital operations initiatives Kearney has undertaken with global clients to regenerate their supply chains for performance and long-term growth include the following.

  • Telecommunications. Minimum viable product models helped a global telco improve its demand forecasting by 23%; more efficient allocation of smartphone and accessory supply among retail outlets and distribution centers reduced on-hand inventory by 5% and annual fulfillment costs by nearly a third.
  • Grocery/department store retail. Cost-to-serve models applied to real-time data provided a major food retailer and supermarket/department store operator with continuous live tracking of freight operations, freight analytics to reduce empty miles and CO2 emissions, and dynamic optimization of freight terms trade-offs. Service performance improved by 5%-10%, saving $50 million in working capital expenditures; cost of goods sold (COGS) and CO2 emissions fell by 1%-2% each.
  • Household/personal care products. Adding digital twin modeling to a large household consumer products brand’s scenario planning enabled the firm to confidently incorporate a natural cosmetics line into its product portfolio over a 10-year planning horizon. The digital twin model is now used to assess future scenarios and responses, stress-test network resilience and predict direct, indirect, opportunity, and other concept costs.

What are the next practices?

Ubiquitous, affordable AI adds a new layer of future supply chain capability—proactive, dynamic end-to-end visibility. With near-zero latency partners can “see” all operations and processes at work in real-time to monitor performance, spot potential disruption as or before it happens and respond dynamically, in accordance with predefined business rules and contractual arrangements.

Generative AI, still in the early development stages, will go a step further, building an infinitely scalable army of specialist AI bots, or agents, to perform specific functions in real-time. These agents can operate as a single, always-on, connected force, performing their functions automatically subject to predefined business rules, and escalating where necessary to human intervention, responding to queries and direction in natural language.

In the process, the current linear supply chain model will evolve into a more dynamically configured, networked system of capabilities delivering customer, societal and business value. End-to-end data will become more accessible, contextual and correlated in real-time, enabling more sophisticated optimization and contractual collaboration among partners on strategic, sustainability or other initiatives.

As data sets build over time, they will become more predictive—and prescriptive—in identifying operational improvements to boost resilience, performance, margins and customer satisfaction. AI will monitor the end-to-end network and draw from millions of complex internal and external data points in seconds, incorporating customer, partner and market signals to make routine adjustments while escalating to human intelligence and intervention to resolve more complex trade-off decisions. Analytics will test and rank complex probability scenarios for more accurate, detailed demand forecasting, supplier or carrier selection and negotiations, carbon emissions reduction and more.

Standardization and digital integration of business platforms across the organization dramatically increase the speed and granularity with which supply chains can be configured both internally and externally. Companies will be able to stand up temporary networked value chains, drawn from specialized, global partner and talent ecosystems, to seize short-term opportunities, or manage a sudden disruptive event.

Leaders are seizing the initiative

Forward-looking companies are retaking control of their futures post-COVID, recognizing that a pandemic-driven “product-at-all-costs” strategy was always unsustainable and that, rather than trying to predict an uncertain future, it’s more useful to be prepared for anything. They should instead prepare for any eventuality and assess the likeliest probabilities.

Businesses need to build an end-to-end, real-time, actionable window into their supply chains, to view and plan for the full range of risks and opportunities open to them, rank the probability of each in the moment and over time, and begin to move forward.

The same data processing, connectivity and analytic capabilities providing visibility to manage volatility can also optimize a manufacturer’s global footprint, boost on-time, in-full performance and build a brand image around sustainability to reach new markets and customers.

Waiting to act in hope that a different future arrives is counterproductive. Businesses can’t control externalities like conflict, climate, pandemic or inflation, but they can control how they adapt and respond. The future belongs to those ready and willing to open the door and walk through.

About the authors:

Suketu Gandhi is a partner and global co-lead of strategic operations at Kearney. He can reached at [email protected]. Rupal Deshmukh is a partner at Kearney. She can be reached at [email protected]. Gillis Jonk is a vice president of strategy and M&A at Kearney.  He can be reached at [email protected]. Sachin Narang is global senior knowledge  manager at Kearney. He can be reached at [email protected].

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Four years of supply chain chaos have left C-suites tired of playing defense. Armed with lessons learned from the COVID pandemic, leading companies envision a new, AI-enabled supply chain not just rewired for resilience but regenerated for long-term growth, performance, and sustainability.
(Photo: Getty Images)
Four years of supply chain chaos have left C-suites tired of playing defense. Armed with lessons learned from the COVID pandemic, leading companies envision a new, AI-enabled supply chain not just rewired for resilience but regenerated for long-term growth, performance, and sustainability.

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