Mapping the Digital Future of Industrial Manufacturing

Whether it’s the challenge of managing configure-to-order product portfolios, the pressures of evolving project-based sales cycles, or the need to respond quickly to supply shocks, today’s industrial manufacturing environment demands more than incremental improvement. It requires a digital-first operating model.

“Today, industrial manufacturers are facing one of the toughest operating environments to date,” said Ryan Manes, Senior Director at o9, as he opened the 2025 State of the Industrial Manufacturing Industry keynote.

In this session, Ryan walked through the core challenges facing the sector, o9’s digital approach to overcoming them, and the real-world outcomes achieved by industrial companies embracing transformation.

Eight challenges defining the future of manufacturing

Ryan outlined eight key obstacles that continue to impact performance across the industry:

• Highly configurable products: With thousands of components and frequent engineering changes, predicting the right stock levels—and using up previous revisions—is exceptionally difficult. “Manufacturers must balance long lead time raw materials against much shorter customer delivery expectations,” said Ryan. The result? Inflated inventories, late deliveries, and poor customer experiences.
  
• Disconnected sales and supply chain teams: In deal-based environments, forecasts live in spreadsheets or emails, with limited collaboration. “The supply chain team struggles to simulate demand’s impact or assess financial outcomes,” Ryan explained.
  
• Project complexity and milestone coordination: For products requiring onsite installation—like elevators, wind turbines, or telecom towers—planners must align materials, labor, and timelines across dozens of dependencies. Spreadsheets simply can’t keep up.
  
• Multi-tiered manufacturing networks: Many companies struggle to manage dependent demand across complex routings, with capacity and labor constraints causing frequent disruptions. “Manufacturers have difficulty coordinating thousands of parts and managing shortages, which cause line stoppages, OEE challenges, and excess WIP,” Ryan noted.
  
• Inventory overloads without root cause visibility: Whether from inaccurate forecasts, MOQs, or over-ordering, excess inventory ties up working capital. Yet many companies can’t pinpoint why.
  
• Limited supplier collaboration: While OEMs may share forecasts with suppliers, two-way collaboration is rare. “Suppliers struggle to analyze volatile week-over-week changes,” said Ryan, causing ripple effects across the network.
  
• Unmitigated risk exposure: While many companies now map suppliers and monitor global risk, few can tie disruptions back to actual transactional orders, making it difficult to take the right mitigation steps.
  
• Business model disruption: Just as e-commerce transformed retail, new business models, like EV manufacturers selling direct-to-consumer, are reshaping industrial markets. “The data is there from telematics and predictive maintenance,” said Ryan. “But companies still struggle to harness it.”

Moving from tribal to digital operating models

At the core of o9’s approach is a fundamental shift: from tribal knowledge and siloed systems to a digitally connected enterprise operating model. “o9 brings best practice processes and technologies to drive a major step change,” Ryan said.

With o9’s enterprise knowledge graph, companies can bring together data from spreadsheets, ERPs, CRM tools, and more into a single platform. This becomes the foundation for integrated business planning, cross-functional collaboration, and intelligent scenario planning.

Instead of multi-day processes to prepare IBP decks, companies can “view executive-level dashboards and run what-if scenarios on the fly with live data,” Ryan explained.

A unified planning platform for real-world complexity

Ryan then walked through how o9 supports each planning domain:

• Demand planning: o9 supports automated demand generation, collaborative demand management, and machine learning-driven forecasting. “For deal-based sales models, o9 integrates to your CRM system and automatically imports opportunities,” Ryan said, allowing teams to track win probabilities and planning BOM changes in real time.
  
• Supply planning: With LP and heuristic engines, o9 can generate level-loaded MPS, purchase requirements, and distribution plans. “What-if scenarios simulate operational and financial outcomes, allowing users to optimize across revenue, margins, and costs like premium freight,” Ryan noted.
  
• Inventory optimization: The platform enables time-phased, multi-echelon inventory targets, with alerts, dashboards, and root cause insights.
  
• Supplier collaboration and risk: Two-way collaboration rooms, KPI tracking, and global risk data ingestion allow teams to manage supplier capacity, performance, and risk in a single view.

Real-world results: Two transformation stories

To show what this looks like in practice, Ryan shared two client success stories.

A global technology provider reimagines complexity

One client, a leading global technology provider, faced staggering challenges: 100,000+ SKUs, a 90% unique configure-to-order model, BOMs up to 12 levels deep, and lead times of 72 weeks, even as 75% of orders were marked as ASAP.

After a failed attempt with another advanced planning system, they turned to o9.

“We enabled them to assess all deals above $1 million—down from a previous threshold of $5 million—in under 24 hours,” said Ryan. This resulted in a 10x increase in deal coverage and a 70% reduction in response time.

They also introduced ML-based deal predictability, helping teams prioritize at-risk opportunities and improve alignment between deal planning and supply planning.

A global Tier-1 automotive supplier gains resilience

Another customer, a top-tier global automotive supplier, was up against major forecast volatility, limited supply-side visibility, and siloed S&OP processes.

But, with the help o9’s platform, they were able to:

• Analyze EDI bias and improve forecast accuracy over OEM estimates
  
• Integrate third-party data like IHS market forecasts and dealer inventory
  
• Run fully constrained plans with real-time scenario simulations
  
• Improve supplier collaboration via request-commit workflows
  
• Establish a cross-functional IBP process, including suppliers and customers

The results were substantial:

• 30% reduction in premium freight costs
  
• 6% improvement in inventory turns
  
• 88% adoption rate across the organization
  
• 6–15 point improvement in forecast accuracy vs. EDI

Ryan’s message is simple.

From improving forecast accuracy to driving cross-functional collaboration, the o9 platform is designed to meet the needs of the most complex manufacturing networks. And as business models evolve, digital flexibility is truly essential.

Watch the full keynote from Ryan Manes below.

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