Steering logistics into the fast lane with AI and data
APR. 10, 2025
8 Min Read
Redwood Logistics CPO reveals how AI, data connectivity, and automation are revolutionizing supply chains.
In an exclusive Q&A at PROMAT 2025, Michael Reed, Chief Product Officer at Redwood Logistics, shared insights on how cutting-edge technology is reshaping the logistics landscape with Lumenalta President, Michael Hagler.
Redwood Logistics, a company managing billions in freight and working with some of the world's largest brands, has been at the forefront of supply chain digitization through strategic investments in AI, data connectivity, and automation.
The two discussed how logistics executives should leverage technology for competitive advantage in an increasingly complex industry environment.
Strategic vision: Connecting the dots in a fragmented industry
Hagler: “Let's start with the big picture—what's Redwood's strategic vision for technology, data, and AI?”
Reed: “At Redwood, our vision is centered around making supply chains more connected, intelligent, and automated,” explained Reed. “The logistics industry has been historically fragmented, with siloed systems and manual processes.”
Redwood focuses on three core areas:
- Data connectivity – Unifying scattered logistics data through their integration platform, Redwood Connect.
- AI-driven optimization – Leveraging machine learning for predictive analytics to optimize transportation costs and mitigate risks.
- Automation & workflow intelligence – Freeing supply chain teams from repetitive tasks through automated workflows.
Reed noted that these investments weren't made overnight. “We've been investing in this for several years, but we've really accelerated over the last three to five years,” he shared. “The shift was driven by customer demand—supply chains were becoming more unpredictable, and companies needed better data to make agile decisions.”
Building the business case: Demonstrable ROI
For executives looking to secure buy-in for technology investments, Reed offers a framework that worked for Redwood:
Hagler: “It's one thing to have a vision, but another to get buy-in. How did Redwood make the case for investing in these areas?”
Reed: “When you're asking for significant technology investment, leadership wants to see clear business value,” Reed says. Their approach focused on three areas:
- Cost reduction – Demonstrating how AI-powered route optimization reduces transportation spending by 10-15%
- Operational efficiency – Showing how workflow automation cuts manual workload by 30-40%
- Revenue growth – Using predictive analytics to improve demand forecasting
The results speak for themselves: “One of our customers reduced their freight spend by $3 million annually by leveraging our AI-driven mode selection technology, which optimizes the balance between speed and cost.”
The integration challenge: Redwood Connect
A significant portion of the conversation centered on Redwood Connect, the company's logistics integration platform.
Hagler: “You mentioned Redwood Connect—let's dive deeper. What is it, and how does it reduce costs?”
Reed: “Redwood Connect is our logistics integration platform, designed to seamlessly connect shippers, carriers, and technology systems without heavy IT lift,” Reed explains.
The platform addresses a fundamental challenge in logistics: disjointed systems. “The biggest challenge is that companies use disjointed systems—ERP, TMS, WMS, visibility platforms, spreadsheets—none of them talk to each other efficiently. That fragmentation leads to slow decision-making and missed cost-saving opportunities.”
“Lumenalta really understood this challenge,” Reed continued. “They helped us build Redwood Connect with the flexibility to handle multiple integration patterns and data formats that we encounter across different customer environments. Their technical approach made implementation much faster for our customers.”
By automating the flow of real-time data across systems, Redwood Connect enables:
- More accurate pricing and procurement decisions
- Faster, AI-driven mode selection to optimize freight costs
- Automated invoice audits, reducing overcharges and disputes
Reed cited a compelling case study: “For one of our retail customers, we eliminated 80% of manual data entry, allowing them to reallocate staff to more strategic roles.”
The foundation: Data quality first
Before diving into advanced AI applications, Reed emphasizes the importance of data quality:
“Our early investments in data quality were foundational. Without clean, structured, and accessible data, even the best AI and automation tools wouldn't deliver real value,” Reed states.
These investments enabled:
- Seamless system integrations through standardized and cleansed data
- Accurate predictive analytics from high-quality data
- Reliable, automated workflows for freight audits and procurement
“One of the things I appreciated about working with Lumenalta on Redwood Connect was their methodical approach to data quality,” Reed added. “They understood that without addressing underlying data issues first, the platform wouldn't deliver the value we needed. Their expertise in data cleansing and normalization was critical to making the entire system work.”
The human element: Cultural transformation
Technology implementation is as much about people as it is about code:
Hagler: “Becoming a technology-driven organization requires changes beyond just the code. What were some of the people impacts that you encountered along the way, within your teams or with your partners?"”
Reed identifies several key challenges:
- Building trust in AI –“Many teams were skeptical of AI-driven decisions. We focused on education, small wins, and showing AI as an assistive tool, not a replacement.”
- Upskilling & collaboration – “We invested in data literacy training and improved communication between IT and operations.”
- Shifting mindsets –“Logistics is risk-averse, but AI requires experimentation. We fostered a 'fail fast, learn faster' approach.”
- Partner readiness – “Not all partners were tech-ready. We built flexible integrations and provided support.”
Practical steps for logistics executives
For executives looking to begin their journey with AI and data, Reed offers pragmatic advice:
Reed: “Start by assessing your data maturity and defining real ROI metrics,” Reed advises. “Many companies rush into AI and automation without understanding whether their data is clean, structured, or even accessible.”
He recommended three key steps:
- Audit your data – Identify where critical supply chain data lives and whether it's usable
- Define ROI goals – Clarify whether you're trying to cut costs, improve efficiency, or enhance service levels
- Start with small, quick wins – Implement targeted projects like automating freight audits or using AI for demand forecasting
“And don’t hesitate to seek out the right partners,” Reed added. “Working with experts like Lumenalta gave us a significant head start. They brought specialized experience in logistics data integration that would have taken us years to develop internally.”
Lessons learned: Avoiding common pitfalls
Drawing from Redwood’s experience, Reed shares valuable insights:
Hagler: “What are the biggest lessons Redwood has learned along the way?”
Reed: “Data integration is the hardest part,” he emphasizes. “Before AI can work, you need to fix data fragmentation. Many companies underestimate this step.”
Other key takeaways included:
- Success metrics should go beyond cost savings to include agility and risk management
- Cultural readiness is critical—without it, even the best tools won't help
- Change management is essential for adoption
“Looking back, I'm glad we partnered with Lumenalta on Redwood Connect,” Reed reflected. "They understood these challenges and built a solution that addressed the real-world complexities of logistics data integration. Their experience helped us avoid many common pitfalls that could have delayed or derailed our progress.”
Implementing generative AI: Where to begin
As the conversation concludes, Reed provides specific advice on generative AI implementation:
Reed: “The best way to start is by using GenAI to augment existing workflows, not replace them.”
He recommends starting with:
He recommends starting with:
- Automated report summaries that quickly analyze supply chain data
- Intelligent customer service through AI-driven chatbots
- Contract and rate analysis to identify cost-saving opportunities
His parting advice: “Start now, but start smart. AI and automation aren't futuristic concepts anymore—they’re essential to staying competitive in logistics. Focus on data quality, clear ROI goals, and cultural alignment, and you'll be well-positioned for success.”
