Recommendation engines, dynamic pricing, conversational CX—AI can unlock them all. But without trustworthy, unified data, AI simply amplifies bad patterns. Inspired by No AI without data: Why digital success starts with the basics, this episode separates signal from noise: the trillion-dollar cost of poor data quality, why “garbage in, garbage out” still rules, and the concrete steps leaders are taking to fix foundations before scaling AI.

What You’ll Learn in This Episode:

Why AI Fails (and How Data Breaks It)

• The “data goldmine” myth: lots of data ≠ useful data
• Hidden data factory: the staggering productivity drain of bad data
• How flaws cause AI misfires: overfitting, edge-case blind spots, spurious correlations, bias, and data drift

The Foundational Fix—A Practical Blueprint

1. Audit reality: map systems (including shadow spreadsheets), ownership, and gaps
2. Product master cleanup: normalize attributes, units, categories, and hierarchies
3. Customer master cleanup: dedupe, resolve parent/child relationships, link true buying history
4. Transaction discipline: capture why (promo, override, contract) to distinguish signal from noise
5. Integration layer: ETL/ELT into a governed warehouse/lake for a single source of truth
6. Governance & DQM: owners, rules, SLAs, privacy (GDPR/HIPAA), and controls embedded in workflows

From Cost Center to Growth Engine

• Cut the hidden factory (free analysts & data scientists to build, not mop up)
• Enable reliable AI: pricing, recommendations, inventory optimization, service automation
• Build resilience: continuous data quality, monitoring, and model retraining to counter drift

Organization & Culture—Making ‘Data First’ Stick

• Cross-functional accountability: sales, finance, ops, IT share metrics and incentives
• “Design for capture”: make high-quality data entry the easiest path for frontline teams
• Iterate in quarters, not years: ship foundations, measure lift, scale patterns

Key Takeaways:

• You can’t buy your way around data quality—AI learns whatever you feed it.
• Clean product, customer, and transaction data is the fastest path to dependable AI.
• Governance turns one-off cleans into durable capability (and lower operating costs).
• Embed “why” at the point of entry to convert exceptions into learnable signals.
• Get the data right and everything improves: pricing, CX, supply chain, analytics.

Subscribe for more pragmatic playbooks on turning AI ambition into measurable outcomes. Visit The Future of Commerce for deep dives on data governance, architecture patterns, and AI implementation. Share this episode with ops leaders, data teams, and execs who own revenue and risk.

Existing home sales don’t count as new GDP output, but they trigger a burst of spending that powers dozens of industries. When sales sink, that “turnover multiplier” fades—hitting retailers, manufacturers, and last-mile logistics fast. This episode, inspired by U.S. home sales decline: How companies can offset the ripple effect, connects the macro dots (7% mortgage rates, rate-lock, inventory scarcity) to the micro results (weaker durable-goods demand, slower last-mile, cautious consumers).

We highlight four strategies leaders are deploying to offset the drag—from IKEA x Best Buy pop-ups to Pro-segment plays, international expansion, AI shopping-agent readiness, and granular scenario modeling—so companies can protect margins now and position for the rebound.

What You’ll Learn in This Episode:

Why a Frozen Housing Market Ripples Everywhere

• Existing home sales projected near ~4M in 2025 vs. ~5–5.5M pre-pandemic
• Rate-lock squeezes churn: owners won’t swap 3% mortgages for ~7%
• Housing ≈16% of GDP: ~12% stable “housing services” vs. ~4% volatile RFI (the tripwire)

Where the Drag Shows Up First

• Durable goods tied to moves: furniture, appliances, electronics
• Logistics signal: softer last-mile for big-ticket deliveries
• Retailers/manufacturers citing the freeze in H1 2025 results

The Four-Part Corporate Playbook

A. New Business Models & Markets

• In-store adjacency: IKEA pop-ups inside Best Buy to capture room-by-room buyers
• Pro focus: revamped contractor programs to balance DIY softness
• International hedge: expansion where housing is healthier (e.g., Mexico)

B. Experience-Led Retail

• Turn stores into multi-function hubs: events, design consults, visualization tools
• Sell outcomes (spaces & solutions), not just SKUs

C. Tapping New AI-Driven Channels

• Prepare for independent AI shopping agents (e.g., Remark, Rufus, Muse)
• Structure product data, attributes, pricing, availability for machine findability

D. Intelligent Scenario Modeling

• Move beyond linear forecasts to granular simulations:
• Interest-rate paths by quarter
• Regional inventory + store signals
• Category-level demand elasticity
• Use outputs to shift inventory, hedge inputs, and adapt pricing dynamically

Signals to Watch in H2

• Persistent rate-lock, slower household formation
• Durable-goods resilience vs. lag effects
• Where the multiplier hits next (self-storage, landscaping, subscriptions, etc.)

Key Takeaways:

• The “small” 4% RFI slice is the economy’s tripwire—when turnover stalls, many categories feel it.
• You can’t control rates or inventory, but you can decouple growth from move-driven demand.
• Experience-led stores, Pro segments, and international footprints cushion the blow.
• AI shopping agents are a new channel—optimize for machines, not just humans.
• Scenario modeling turns volatility into an advantage by guiding inventory, pricing, and sourcing in real time.

Subscribe for more deep dives on macro shocks and practical playbooks. Visit The Future of Commerce for research and case studies on demand resilience, AI-ready data, and scenario modeling. Share this episode with leaders in retail, CPG, logistics, and durable goods who need an actionable plan for a slow-churn housing market.

Generative AI is rapidly becoming a game-changer for customer experience (CX), but the real differentiator isn’t the technology itself—it’s how organizations adapt. Inspired by GenAI is reshaping CX, but only for organizations ready to reinvent themselves, this episode unpacks the organizational shifts required to truly harness AI’s potential.

We highlight the reinvention imperative: why sustainable CX gains demand new processes, redefined team roles, and flexible technology stacks. From orchestrating customer interactions to hyper-personalizing journeys, we explore the top 11 GenAI use cases already deployed in contact centers, sales, and marketing—and the measurable results they’re delivering.

What You’ll Learn in This Episode:

The Reinvention Imperative

• Why GenAI tools alone don’t guarantee transformation
• How organizational redesign, employee experience, and strategy integration drive success

Delegating the Drudgery

• How AI agents orchestrate customer interactions and reduce manual busywork
• Freeing CX teams to focus on creativity, innovation, and strategy

Shortening the Cycle

• Why the era of long, static redesign projects is over
• How composable martech and GenAI enable continuous, rapid CX evolution

From Personas to People

• How GenAI makes hyper-personalization and individualized journeys possible
• Stepwise approaches to testing, scaling, and iterating personalization

Real-World GenAI Use Cases

• Contact Centers: Auto-generating replies, automating QA, creating knowledge articles, and summarizing after-call work
• Sales Teams: AI-powered lead generation, personalized communications, meeting summaries, and onboarding automation
• Marketing: AI-generated ad copy, content creation, and real-time social media management

Key Takeaways:

• GenAI is commoditizing fast; competitive advantage comes from reinvention, not tools
• AI agents free CX teams from orchestration, enabling higher-value human creativity
• Continuous iteration, not static projects, defines the new CX pace
• Hyper-personalization moves customer journeys from broad personas to individualized experiences
• Real-world deployments across CX functions show clear, measurable impact today

Subscribe to our podcast for insights on CX, digital transformation, and AI strategy. Visit The Future of Commerce for in-depth coverage of GenAI and customer experience innovation. Share this episode with CX leaders, digital strategists, and business executives preparing for the AI-driven future.

The modern shopping journey is nonlinear, unpredictable, and driven by rising expectations. Inspired by How to power personalized, AI-driven customer experiences for digital shopping, this episode unpacks how generative AI is closing the “experience gap” by transforming static commerce into fluid, intelligent journeys.

We’ll explore how composable commerce, SAP Commerce Cloud, and endorsed partners like Coveo enable businesses to deliver real-time personalization, conversational product guidance, and seamless integration across channels. Case studies from Blackwoods, Nespresso Oceania, and Xero show how AI search and discovery translate into measurable gains in adoption, conversions, and customer satisfaction.

What You’ll Learn in This Episode:

The Rise of Generative AI in CX

• How GenAI shifts experiences from functional to conversational
• Guided decision-making that prevents customers from bouncing to Google
• Extending personalization into the post-purchase lifecycle

The Experience Gap

• Why customer expectations outpace many brands’ capabilities
• The cost of siloed systems in delivering real-time relevance

Composable Commerce as the Strategic Answer

• Modular architectures replacing rigid monoliths
• SAP’s composable storefront and OCC APIs enabling flexibility
• Why endorsed partnerships (like Coveo for AI search) reduce integration complexity

How AI Makes Shopping Seamless

• Hybrid search blending keyword + semantic search
• Real-time re-ranking and session-aware personalization
• Generative answering with source-cited responses for trust

Case Studies in Action

• Blackwoods: 66% digital adoption growth, 70% add-to-cart boost, 45% higher CSAT
• Nespresso Oceania: 182% conversion lift from search, 10% higher order values
• Xero: 20% reduction in human support cases in just six weeks

Key Takeaways:

• Generative AI is becoming the nervous system of modern customer experience
• Personalization must extend across the entire lifecycle, not just pre-purchase
• Composable commerce enables agility while leveraging best-in-class AI tools
• Strategic integrations with endorsed partners reduce complexity and accelerate ROI
• Brands already embracing AI are seeing measurable, bottom-line business impact

Subscribe to our podcast for insights on customer experience, digital commerce, and AI-driven personalization. Visit The Future of Commerce for in-depth analysis on how technology is reshaping shopping journeys. Share this episode with CX leaders, digital commerce teams, and marketers working to bridge the experience gap.

Once seen as a resource-intensive, slow-moving sector, the pulp and paper industry is now at the forefront of sustainability, digital transformation, and profitability. In this episode, we examine how mills are embracing advanced biotechnology, AI, and ERP process transparency to reduce waste, diversify products, and gain competitive advantages.

We dig into real-world innovations—from turning black liquor into biocomposites and bioethanol to deploying SAP Signavio for process mining—and how these technologies are helping companies meet aggressive environmental targets while boosting their bottom line. Learn why eliminating “process debt” in ERP systems is the hidden lever for enabling AI and why data-driven decision-making is becoming the ultimate competitive differentiator in this industry’s reinvention.

What You’ll Learn in This Episode:

1. Industry Transformation

• How pulp and paper is moving beyond paper production into biochemicals, bioenergy, and premium sustainable packaging
• Why sustainability is now seen as a profit driver, not a cost

2. Waste-to-Value Innovation

• Black liquor biorefining into lignin biocomposites, PLA bioplastics, and tall oil products
• Converting sulfite liquors into industrial lignosulfonates and bioethanol using advanced yeast strains

3. Digital Optimization & ERP Transparency

• The concept of “process debt” and why outdated ERP processes hinder growth
• How SAP Signavio and SAP LeanIX provide visibility and structure for AI-driven optimization

4. AI-Driven Operations

• Predictive maintenance reducing downtime and cost
• Real-time quality analytics and process optimization in paper manufacturing
• AI market growth in pulp and paper projected to hit $15B by 2034

5. Data as a Competitive Advantage

• Using platforms like FisherSolve for sustainability benchmarking and supply chain decision-making
• How science-based targets are reshaping supplier relationships

Key Takeaways:

• The pulp and paper industry is becoming a model for sustainable, profitable transformation
• Biotech is enabling waste streams to become high-value product lines
• ERP process transparency is the critical enabler for AI and continuous optimization
• Data-driven decision-making is redefining competitive advantage in manufacturing
• Sustainability initiatives are directly linked to revenue growth and market differentiation

Subscribe to our podcast for expert insights on manufacturing transformation, ERP optimization, and the intersection of sustainability and profitability. Visit The Future of Commerce for in-depth coverage of how legacy industries are leveraging digital tools to reinvent themselves. Share this episode with industry leaders, sustainability strategists, and operations professionals looking to drive both environmental and economic gains.

Retail’s “canary in the coal mine” moment has arrived. The H1 2025 Retail Recap Report reveals a sector under strain from economic volatility, shifting consumer habits, tariff pressures, and rising job losses. In this episode, we unpack the numbers and narratives driving this change, from cautious shoppers and evolving mall spaces to mounting supply chain costs and looming risks for the second half of the year.

Drawing on retail performance data, executive insights, and industry forecasts, we connect the dots between consumer psychology, policy impacts, and the strategic crossroads facing retailers. Whether targeting high-income spenders or pivoting to extreme value propositions, businesses must navigate a retail landscape that’s fundamentally shifting beneath their feet.

What You’ll Learn in This Episode:

1. The State of Consumer Spending

• Why warehouse clubs and dollar stores are thriving
• Caution in grocery spending and reluctance to try new brands
• Health and wellness as a persistent priority amid belt-tightening

2. Economic Indicators Behind the Slowdown

• Inflation masking weaker sales volumes
• H1 driven by high-income spenders while low-income visits drop sharply
• McDonald’s reports double-digit declines in low-income customer visits

3. Tariff Pressures and Their Consumer Impact

• $100M in projected costs for Under Armour from tariffs alone
• Goldman Sachs estimates tariffs could add $2,400 annually to household expenses
• Price impacts on clothing, cars, and fresh produce

4. Job Market Shifts in Retail

• Retail job cuts up 249% YoY, totaling over 80,000 in H1
• Signs of systemic change beyond seasonal adjustments

5. Tourism and Service Sector Headwinds

• WTTC forecasts $29B drop in U.S. international tourism spending
• U.S. as the only country projected to see a decline in 2025

6. What to Expect in H2 2025

• Holiday season uncertainty despite typical seasonal uptick
• Strategic fork: target the wealthy or pivot hard to value retail
• Inflation, interest rates, and tariffs as ongoing headwinds

Key Takeaways:

• Consumer caution is reshaping where and how people spend
• Tariffs are directly raising household costs and straining retailer margins
• Job cuts and slowing tourism add to the sector’s instability
• Retailers face a stark strategic choice for the rest of 2025
• The middle ground in retail is eroding, redefining economic health indicators

Subscribe to our podcast for expert analysis on retail trends, economic indicators, and consumer behavior shifts. Visit The Future of Commerce for deeper insights into how market forces and policy decisions are shaping the retail landscape. Share this episode with retail strategists, policy watchers, and anyone navigating the challenges of 2025’s volatile economy.

If you’ve ever checked online stock, headed to the store, and found empty shelves—or seen a promotion vanish at the register—you’ve felt the friction of outdated retail systems. In this episode, inspired by Unified commerce benefits: Powering retail renewal and marketplace AI, we uncover how unified commerce fixes these gaps by integrating every channel, system, and data point into one real-time view.

We also explore how marketplace AI builds on this unified foundation to automate listings, optimize inventory, personalize recommendations, and dynamically adjust pricing across major e-commerce platforms. From solving everyday shopping frustrations to giving retailers the agility to adapt instantly, this pairing is transforming retail at every level.

What You’ll Learn in This Episode:

1. Unified Commerce vs. Omnichannel

• Why omnichannel often hides disconnected back-end systems
• How unified commerce unifies data for a true single source of truth
• The operational and customer experience benefits of real-time integration

2. The Core Benefits of Unified Commerce

• Accurate, instant inventory visibility across channels
• Seamless returns and consistent pricing everywhere
• Real-time updates flowing into financial, supply chain, and marketing systems

3. AI as the Next Layer of Retail Intelligence

• Using unified data to power predictive analytics and personalization
• Optimizing fulfillment and supply chain agility with AI
• Shifting from reactive to proactive retail strategy

4. Marketplace AI in Action

• Automated product listings and catalog synchronization
• Dynamic pricing based on demand, competition, and stock levels
• AI-powered product discovery and intent-based search
• Personalization that adapts to real-time browsing and purchase signals

5. The Strategic Imperative for Retailers

• Why marketplace AI’s full potential requires unified commerce
• The role of cloud migration and legacy system integration
• Building scalability and competitive edge through data quality

Key Takeaways:

• Unified commerce eliminates data silos, enabling consistent, personalized customer experiences
• Real-time data is the foundation for effective AI in retail and marketplace management
• Marketplace AI extends unified commerce into external platforms with automation and optimization
• Retailers that invest in unified systems gain speed, agility, and measurable profit growth
• For shoppers, it means accurate stock, consistent pricing, and tailored recommendations everywhere

Subscribe to our podcast for expert insights on retail transformation, AI in commerce, and customer experience innovation. Visit The Future of Commerce for deep dives into how technology is reshaping the way we shop and sell. Share this episode with retail leaders, e-commerce strategists, and marketplace managers looking to future-proof their operations.

B2B buyers now expect the same speed, personalization, and precision they enjoy in consumer shopping—and that expectation is redefining digital commerce. In this episode, inspired by How Boston Scientific uses AI search to transform B2B commerce + boost conversions, we break down how AI-powered search is closing the experience gap, boosting conversions, and creating measurable ROI.

With insights from Boston Scientific’s digital transformation journey, we explore how they tackled search performance challenges, integrated Coveo’s AI relevance platform into SAP Commerce Cloud, and deployed an “intent box” to unify search and chat into a single entry point. The results: faster customer experiences, empowered sales teams, higher retention, and a staggering 300% growth in online order revenue.

What You’ll Learn in This Episode:

The Experience Gap in B2B Commerce

• Why B2B buyers expect Amazon-level experiences
• Harvard Business Review study: 70% say AI is essential for e-commerce’s future
• Common barriers: data privacy, skills gaps, executive alignment

What Makes AI-Powered Search Different

• Enriched intent detection that understands buyer needs
• Automatic re-ranking and behavior-based recommendations
• Question answering and dynamic content filtering to reduce friction

Boston Scientific’s Search Transformation

• Integrating Coveo’s AI platform with SAP Commerce Cloud
• Centralizing content from 55+ sources into one intelligent index
• Personalizing search results for both customers and sales reps

The “Intent Box” Innovation

• Unifying search and chat into one smart entry point
• Delivering fast, accurate, contextual answers from anywhere in the site
• Changing the way customers interact with digital channels

Measurable Impact and ROI

• 20%+ jump in search conversion rates
• Customers discovering and purchasing new products via search
• Reduced customer service calls and improved self-service
• 300% increase in online order revenue

Key Lessons for AI Success in B2B

• Start with the business problem, not the platform
• Focus on relevance, not just channels
• Partner with providers who offer both technology and strategic guidance

Key Takeaways:

1. AI search can close the B2B experience gap and boost customer satisfaction
2. Unified, intent-driven experiences speed up buying and selling
3. Strategic alignment between tech and business goals drives ROI
4. Integration with existing platforms preserves flexibility while adding intelligence
5. Relevance is the ultimate metric for digital commerce success

Subscribe to our podcast for expert insights on AI in commerce, B2B digital transformation, and customer experience innovation. Visit The Future of Commerce for in-depth research on how technology is driving measurable business results. Share this episode with digital leaders, e-commerce managers, and sales enablement teams looking to close the experience gap.

A slowdown in retail sales is rippling through the industry, with new tariffs and supply chain volatility forcing retailers to rethink everything from pricing to inventory management. In this episode, inspired by Retail and tariffs: Stockpiles, agility, and a supply chain reckoning, we break down the economic forces and operational shifts behind the headlines.

Drawing on the latest NRF Retail Monitor data, RELX Solutions’ supply chain study, and real-world cases from Target to the toy industry, we explore how consumer caution, trade policy, and global disruptions are converging—and how retailers are responding with AI, automation, and supplier diversification to stay resilient.

What You’ll Learn in This Episode:

1. The Current State of Retail Sales

• June 2025 marks the first monthly sales decline since February
• Consumer caution is slowing momentum despite year-over-year growth in some categories
• Digital goods stand out with a 24% YoY increase, while big-ticket items slump

2. Why Consumer Psychology Matters

• Uncertainty around tariffs and the economy is driving a “wait-and-see” approach
• How sentiment influences spending beyond inflation or interest rate changes

3. The Supply Chain Pressure Cooker

• Findings from RELX Solutions: 60% of companies restructuring supply chains
• Top pain points: demand volatility, trade disruptions, lack of real-time data
• Moves toward nearshoring, automation, and AI for agility

4. Three Major Pressure Points and Solutions

1. Supplier diversification: real-time info-sharing and AI trade-off modeling
2. Inventory planning: unified data, AI simulation engines, and multi-echelon optimization
3. Demand planning: dynamic AI forecasting that adapts to policy changes

5. Case Studies in Change

• Target: Ending competitor price-matching amid tariff cost pressures
• Toy industry: 145% tariffs on Chinese imports threaten half of SME toy makers

6. Technology as the Strategic Lever

• AI-driven visibility and optimization for resilience
• Inventory pooling and RFID for better tracking and cost control
• Predictive analytics to match stock levels with volatile demand

Key Takeaways:

• Retail sales are slowing as consumer caution deepens amid economic uncertainty
• Tariffs and trade policy shifts are driving supply chain reinvention at scale
• AI and automation are essential tools for resilience and agility
• Retail policies, from price-matching to product availability, are shifting in real time
• The impact reaches every shopper’s cart—what’s available, and at what price

Subscribe to our podcast for expert insights on retail strategy, supply chain innovation, and the evolving consumer landscape. Visit The Future of Commerce for in-depth research on how global trade and technology are reshaping retail. Share this episode with supply chain leaders, retail strategists, and consumer market analysts navigating the current volatility.

In today’s fast-moving, high-volatility markets, the old way of managing pricing—manual processes, siloed data, reactive decisions—just can’t keep up. This episode, inspired by AI agent pricing: Faster, smarter decision making for margin growth, examines how AI agents are changing the game for sales, pricing, and revenue management.

We dive into what makes agentic AI different from traditional automation, why human-AI collaboration is key, and how unified technology platforms create the environment these agents need to thrive. Real-world examples, including Pricevex’s specialized pricing agents, show how businesses can detect margin leaks, optimize discounting, accelerate quoting, and capture premium opportunities—at scale.

What You’ll Learn in This Episode:

1. The Shift to Agentic AI

• How AI agents differ from past automation tools
• Why they act as “always-on” co-pilots for margin-impacting decisions
• Gartner’s prediction: AI agents augmenting or automating 50% of business decisions by 2027

2. Core Characteristics of an AI-Agent-Ready Platform

• Always-on, proactive data scanning
• Composable, connected architecture for real-time integration
• Transparent, explainable recommendations to build trust
• User-friendly, natural language interaction

3. Practical Applications in Pricing

• Margin leakage detection for unprofitable products and contracts
• Discount strategy optimization to prevent revenue loss
• Quote intelligence to speed complex deal cycles
• Upside opportunity spotting to boost premium sales

4. Pricevex in Action

• Seamless integration with SAP Commerce Cloud and SAP Sales Cloud
• Instant, AI-driven pricing recommendations for complex configurations
• Automated approval workflows and real-time system sync

5. The Strategic Role of Unified Platforms

• Why best-of-breed architectures often create complexity and cost traps
• Benefits of suite-as-a-service for pre-integration and vendor consolidation
• The “flywheel effect” where integrated applications, data, and AI feed each other

6. Looking Ahead: AI and Business Strategy

• AI literacy as a driver of 20% higher financial performance
• Challenges of managing synthetic data at scale
• The role of semantics in improving AI model accuracy and reducing costs
• Gartner’s 2029 prediction: AI guidance influencing board-level decisions

Key Takeaways:

• AI agents enable faster, more precise decision-making in pricing and revenue management.
• Unified, composable platforms remove the silos that limit AI’s effectiveness.
• Transparency and explainability are essential for trust in AI-driven recommendations.
• Vendor consolidation supports efficiency, scalability, and consistent data for AI models.
• Businesses that combine human expertise with agentic AI will set the pace in their industries.

Subscribe to our podcast for expert insights on AI in pricing, sales, and business strategy. Visit The Future of Commerce for in-depth research on how technology is transforming decision-making. Share this episode with pricing leaders, CIOs, and revenue strategists who want to harness AI for margin growth.

Manufacturing execution systems (MES) have long driven efficiency in paper and packaging operations. But many of these systems—often 20 to 30 years old—are now a drag on agility, innovation, and competitiveness. This episode, inspired by Rethinking manufacturing execution systems in paper and packaging, dives into why legacy MES platforms are reaching their limits and what the next generation of manufacturing technology looks like.

We examine the growing demand for semantically rich, unified data to power AI and intelligent agents, and the need to rethink the MES–ERP relationship. From moving quality management into ERP to leveraging open, adaptable MES platforms like SAP Digital Manufacturing, the conversation highlights real-world partner solutions that blend modern core capabilities with deep industry specialization.

What You’ll Learn in This Episode:

1. Why Legacy MES Is Hitting Its Limits

• How decades-old, heavily customized systems create rigidity
• The talent gap as expert maintainers retire
• Why outdated MES can’t keep pace with AI-driven ERP advancements

2. The Shift to Semantically Rich, Unified Data

• The importance of contextualized data for AI insights
• Avoiding costly data replication through centralized data platforms
• Turning historical production data into predictive gold

3. Breaking Down MES–ERP Silos

• Rethinking which functions belong in ERP vs. MES
• Quality management as a case study in migration to ERP
• Enabling top-floor-to-shop-floor process optimization

4. The Platform-and-Partner Model

• How SAP Digital Manufacturing provides a robust, adaptable MES core
• The role of partners in delivering industry-specific last-mile capabilities
• Examples: Delaware’s DM4Mill, ConCircle’s ConMill suite, T-Con’s die roll optimization

5. Future-Ready Manufacturing

• The need for openness, scalability, and deep integration
• Leveraging cross-industry innovation for sustained competitiveness
• Why platform-based MES may be the only viable path forward in the AI era

Key Takeaways:

• Legacy MES platforms are becoming liabilities in the face of AI and advanced ERP capabilities.
• Semantically rich, unified data is essential for predictive analytics and intelligent automation.
• Rethinking the MES–ERP divide unlocks new operational efficiencies.
• Platform-based MES with partner-driven specialization delivers both modernity and industry fit.
• Adaptation speed will determine competitive advantage in manufacturing.

Subscribe to our podcast for expert insights on manufacturing innovation, AI in industry, and digital transformation strategies. Visit The Future of Commerce for in-depth research on how technology is reshaping production systems. Share this episode with manufacturing leaders, operations managers, and technology strategists navigating the MES evolution.