Wiley Jones, Co-founder and CEO of Doss, recently joined Scott Luton and Marty Parker on Supply Chain Now to discuss what has—and hasn't—changed in end-to-end demand planning. Here are the key insights from that conversation.

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What Hasn't Changed in Demand Planning

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Does Demand Planning Matter For You?

Before diving into complex forecasting models, organizations need to assess whether traditional demand planning is even appropriate for their business model:

"You first have to decide whether or not demand planning should be important to you... There are reasons to care about demand planning which have to do with being sensitive to selling out on a product or being sensitive to holding too much inventory."

Companies in rapid growth phases making high-conviction bets on new product lines won't benefit from the same demand planning approaches as established businesses with decades of historical data and stable SKUs. External factors like tariffs can also render historical data less relevant for forecasting.

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"Mise en Place" — Organize the Inputs

The second timeless truth is that effective demand planning requires bringing together multiple data sources—your catalog of offerings, historical sales data, future projections, promotions, and more. This data preparation, which we liken to the culinary concept of "mise en place" (putting everything in its place), remains a fundamental challenge:

"In order to plan for future demand, we have to merge together a few concepts... What is our catalog of offerings? What historical order sales data do we have to draw from? What future projections can we merge in?"

This comprehensive picture of supply and demand continues to be a persistent challenge for businesses, regardless of technological advancements.

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What Has Changed in Modern Demand Planning

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Systems Integration Is Easier Than Ever

Quoting Larry Ellison's 1999 statement that "easy, simple, seamless systems integration is beyond the state of the art," we highlighted how dramatically this has changed:

"For the first time in our lifetimes, it's getting easier and easier to use tools like generative AI to normalize and structure data and bring together all of the things that you actually need to make decisions as a business."

Today's AI tools can take data from disparate sources—CRMs, ERPs, PLM systems—and normalize it in ways that were previously impossible. This foundational change is enabling more sophisticated and responsive demand planning.

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Build Solutions Specific To Your Ops

Modern AI can now understand the semantics and context behind data in ways that traditional statistical models never could:

"Language models are able to understand, 'Well, I sell a bunch of these widgets, I'm a kind of business that sells more at Christmas time. Here's what our lead times are.' This is what we need to be producing because it takes that semantic context of the holidays and characterizes it against sales. That's not something that you could do with a simple regression back in Excel."

Recent research has shown that language models can perform seasonal forecasting better than any traditional forecasting models. This represents a fundamental shift in what's possible for demand planning.

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Automate High-Quality Data Collection

The foundation of effective demand planning remains high-quality data, but the way we collect and validate that data has transformed. Organizations now have unprecedented opportunities to automate data collection and cleaning.

During the conversation, we discussed how Walmart cleaned up approximately 800 million records in their master data system using AI—a task that would have taken 100 years using traditional methods but was completed in just a few months with AI assistance.

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Real-World Impact: Doss in Action

At Doss, we help companies operate more efficiently by creating a system of record that manages the flow of goods, services, and capital. Our approach works across diverse industries, as illustrated by these examples:

• A peanut butter company using Doss to manage everything from e-commerce orders to almond purchases from California farms to TikTok influencer promotions
• A 150-year-old board game company modernizing while maintaining quality and domestic manufacturing
• A demolition business ensuring safety and compliance while literally "blowing up buildings"

The common thread? Moving companies away from mundane, repetitive tasks toward high-leverage activities that drive growth. As Wiley put it during the podcast: "Over the near term, efficiency is about saving hours. Over the long term, it's about saving people."

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No Software Can Save You Without Courage

Perhaps the most powerful takeaway from the conversation was our observation about the limitations of technology alone:

"There's no software that can come and save you if you don't have the courage to go in and change your business."

This truth resonates across industries and organizational sizes. The willingness to transform how you operate is the prerequisite for any technological solution to deliver its full potential.

As Marty Parker noted, this advice applies to businesses of all sizes facing disruption: "It's not going to save Blockbuster if they don't change their business model. It's not going to save Sears and Pennies if they don't respond to Amazon."

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The Path Forward

For supply chain leaders looking to modernize their demand planning approaches, the message is clear: leverage new technologies, but start with the courage to change. The most successful organizations are those willing to challenge the status quo, embrace new tools, and focus their human capital on high-leverage activities that drive growth.

Want to learn how we can help transform your operations?

This blog post was adapted from Wiley's appearance on Supply Chain Now, episode #1405. Listen to the full conversation here.

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