Doss co-founder and CEO Wiley Jones recently joined Jordan Buckner from Foodbevy to discuss how CPG brands can approach demand planning to effectively balance inventory with sales forecasts. Here are the key takeaways from that conversation.

Understanding When Demand Planning Matters

Before diving into complex forecasting models, organizations need to assess whether traditional demand planning is 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."

Durable demand is the critical factor. If your business has predictable, repeatable patterns in customer purchasing behavior (whether seasonal or otherwise), demand planning becomes essential. If you're in an early growth stage with inconsistent sales or are making high-conviction bets on new product lines, a traditional demand planning approach may be less relevant.

The Fundamental Balance

At its core, demand planning addresses two primary concerns:

1. Avoiding stock-outs - Ensuring you have enough product to meet demand
2. Preventing over-inventory - Not producing more than you can sell in a reasonable timeframe

As Wiley puts it: "We look at that as the top and the bottom of the boundary conditions of what we're trying to optimize for... You can think of them like bumpers in a bowling lane - you just want to bounce between those two."

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The Current Challenges of Demand Planning

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Data Collection Is The Biggest Pain Point

For most CPG brands, the most time-consuming aspect of demand planning isn't the forecasting itself but gathering the necessary data:

"Almost all of the work is answering: I know what we're selling, I know what we're holding in stock, and I know what we're producing."

Companies often struggle with:

• Extracting data from multiple channels (Shopify, EDI orders from retailers, emails)
• Gathering inventory counts from 3PLs or warehouses
• Tracking production schedules from co-manufacturers
• Understanding lead times from suppliers

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The Planning Cycle Often Breaks Down

Even after spending extensive time gathering data, the demand planning process often breaks down due to:

1. Time constraints - "If you put 80 hours into coming up with this answer and then you have to decide to nuke it, it really disincentivizes especially small teams from going and putting in that rigorous leg work."
2. Emotional decision-making - "Demand planning is so deeply connected to the strategy of the company and the strategy of the company is so deeply connected to your own conviction in what you think is right."
3. Manual work overload - Teams spend "90% of their effort" on data collection and manual projections rather than strategic decision-making.

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A Better Framework for Demand Planning

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Start With Your Business Context

Understanding your business's specific characteristics is crucial before applying any demand planning model:

• Do you sell to end consumers or businesses?
• What channels do you sell through? (DTC, retail, wholesale)
• How do you handle inventory and warehousing?
• What are your lead times and shelf life constraints?
• How complex is your SKU mix?

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Focus on the Three Core Elements

Any effective demand planning process requires three fundamental pieces:

1. A clear picture of historical sales data across all channels
2. Current inventory positions of both finished goods and production materials
3. Production schedules and procurement timelines with accurate lead times

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Separate Machine Work from Human Judgment

The ideal demand planning process should:

• Use systems and automation to handle data collection and routine calculations (the "survival needs")
• Reserve human judgment for scenario planning and strategic decisions
• Automate the execution of plans once decisions are made

"Humans should be involved in tweaking and iterating on what we think the scenarios should be... We don't want an AI system to go in and try to understand your business; we want you to apply your judgment into the base model."

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Getting Started with Demand Planning

If you're looking to improve your demand planning process:

1. Map your data flows - Document where your data currently lives and how it needs to flow
2. Start with the highest-leverage problems - "Don't try to do everything all at once. Start by saying the most painful thing for me is pulling data out of X - okay, go solve that problem first."
3. Build incrementally - Begin with your item master list and historical sales, then gradually add more sophistication
4. Create a single source of truth - Ensure your entire team works from the same data foundation

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When You Don't Have Predictable Demand

For brands without durable demand patterns (such as those launching with new retailers or running one-time promotions):

1. Create upper and lower bounds for your projections
2. Develop multiple scenarios with different assumptions
3. Identify the risks associated with each scenario
4. Build contingency plans for the most critical scenarios

"It's about your conviction and what you think is going to happen and laying out multiple bounds of scenarios and then assigning what you think are the risks there and then going in trying to proactively mitigate those."

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The Technology Evolution

While you can build demand planning models in Excel or Google Sheets, these approaches often break down as your business scales:

"Where does it actually start to break? Well, if you are doing this currently in a system like Excel... there's not a lot of ability to apply the rigor to prevent people from going out of bounds."

More sophisticated solutions provide:

• Consistent data types and validation
• Better traceability of decisions
• Improved collaboration across teams
• Greater durability and maintainability as your business grows

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A Final Thought

Effective demand planning is about finding the right balance between automation and human judgment. By automating away the mechanical aspects of data collection and calculation, your team can focus on the strategic decisions that actually drive your business forward.

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