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Ecommerce has become one of the most important growth channels for consumer products and retail companies. But for many organizations, channels like Amazon introduce volatility, complexity, and execution pressure that traditional planning processes were not designed to handle. According to global benchmark data from the Salesforce Shopping Index, digital channels now capture over $1.2 trillion in global holiday spend alone.
The challenge is not selling to a new customer, but managing a channel where demand signals change quickly, availability expectations are high, penalties can be costly, and inventory decisions must be made across an increasingly complex network.
When planning fails, the financial impact is immediate and staggering: stockouts cost U.S. retailers tens of billions of dollars annually, while over $758 billion in unsold inventory remains tied up globally, exacerbating customer fines, expedited freight costs, and declining stakeholder confidence.
“Having navigated multiple Prime Days and Black Fridays as a Global Supply Planning Director, I’ve seen firsthand how promotional spikes can create demand that is many multiples of normal run rates—and how quickly a lack of visibility can lead to costly stockouts or expedited freight penalties.”
Tony Schlader
Account Executive, Consumer Products
Why Is Ecommerce Demand Harder to Forecast?
Ecommerce demand is harder to forecast because historical shipments do not capture every factor that changes online demand. Promotions, search ranking, pricing, media spend, reviews, competitor actions, and stock availability can alter demand quickly. Stockouts and marketplace suppression can also hide the demand that would have occurred if a product had remained available.
When I was leading supply chain transformations in the consumer goods space, our biggest hurdle wasn't just predicting demand—it was the disconnect between our legacy ERP systems and the real-time velocity of channels like Amazon. We had to move away from relying on historical data, which is like driving a car while looking in the rearview mirror.
Because of this velocity, Amazon and other ecommerce channels create demand patterns that are often more volatile than traditional retail. Promotions, search ranking, pricing changes, competitor activity, media spend, customer reviews, and inventory availability can all influence demand in real time.
Yet many companies still forecast ecommerce using the same historical shipment-based methods they use for traditional channels. That creates a disconnect.
Shipment history may show what was supplied, but it does not always show what customers actually wanted. If a product was out of stock, constrained, suppressed in search results, or impacted by a promotion, the historical signal can be misleading. The forecast then carries those distortions forward.
The result is a cycle of overreaction and underreaction. Companies build too much inventory on the wrong items, run short on the right items, and struggle to separate true demand changes from temporary noise.
How Forecast Errors Create Stockouts and Excess Inventory
Forecast errors create stockouts when demand is understated and excess inventory when demand is overstated. Under-forecasting can reduce sales, service levels, and digital shelf visibility. Over-forecasting can place inventory in the wrong location, tie up working capital, and increase storage, markdown, and obsolescence costs.
The issue becomes more difficult when inventory is spread across plants, distribution centers, Amazon fulfillment locations, third-party logistics providers, and retail channels. Having enough inventory in total is not enough. The inventory must be in the right place, at the right time, in the right quantity.
For many organizations, ecommerce planning breaks down because inventory policies are not optimized across the full network. Teams manage safety stock, replenishment, allocation, and deployment in silos. One location may expedite product while another holds excess. Amazon may face a stockout while another channel is over-inventoried.
This is where ecommerce becomes a network planning challenge, not just a forecasting challenge.
I’ve sat in the boardrooms where CFOs demanded answers for skyrocketing expedited shipping costs, and I've worked with the purchasing teams frustrated by a lack of E2E visibility. The organizations that win today are the ones that give their planners a single source of truth—breaking down the functional silos between sales, supply chain, and finance.
How Should Brands Plan for Prime Day, Black Friday, and Cyber Week?
Ecommerce demand volatility reaches its peak during major promotional moments. As highlighted in the recent Prime Day recap analysis, events like Prime Day, Singles’ Day, Cyber Week, Black Friday, and category-specific promotions consistently set record revenue highs while driving severe demand spikes that are many multiples of normal run rates.
Brands should prepare for Prime Day, Black Friday, Cyber Week, Singles’ Day, and other major promotions by building event-specific demand scenarios before inventory is committed. Tinuiti reported that Prime Day 2026 generated $26.4 billion in online spending, up 9.3% year over year, while consumer order values and household spending declined. This combination shows why brands must model demand, assortment, discount, margin, and inventory risks together.
For brands selling through Amazon, these events represent both an enormous opportunity and a significant risk. Forecasts developed months earlier must account for promotional lift, marketing investments, competitor actions, inventory constraints, and shifting consumer behavior. Small forecasting errors can have outsized consequences.
When inventory is insufficient, companies risk:
- Lost sales during the highest-demand periods of the year
- Reduced product ranking and visibility
- Missed promotional opportunities
- Increased stockout rates and lower service levels
- Diminished market share that may persist after the event ends
Overestimating demand creates a different challenge. Excess inventory left behind after a tentpole event can increase storage costs, tie up working capital, and force future markdowns or promotional activity.
Unlike a typical week of demand, there is often little opportunity to recover once a tentpole event begins. Inventory must already be in the right location, replenishment plans must already be aligned, and suppliers must already be prepared to respond.
Success during these events depends on an organization's ability to connect forecasting, inventory planning, supply planning, and execution into a single coordinated process.
Ecommerce Planning Signals and Actions
| Planning challenge | Signal to monitor | Planning response | KPI |
|---|---|---|---|
| Promotion-driven volatility | Promotion, media, pricing, and search data | Build event-based demand scenarios | Forecast accuracy |
| Stockouts | Lost-sales and availability data | Correct constrained demand history | In-stock rate |
| Inventory in the wrong node | Node-level inventory and demand | Optimize inventory across the network | Inventory turns |
| Peak-event uncertainty | Demand ranges and supply constraints | Compare expected, upside, and downside scenarios | Service level |
| Slow exception response | Supplier, customer, and fulfillment alerts | Prioritize inventory reallocation decisions | Expedite cost |
Optimized Inventory Requires a Connected Planning Model
To serve ecommerce profitably, companies need to move beyond static inventory targets and disconnected replenishment rules.
They need to understand how demand variability, supply constraints, lead times, service targets, margin, and fulfillment costs interact across the network. Inventory decisions should account for where the product is needed, how quickly it can move, the required service level, and the trade-offs among cost, revenue, and customer performance.
The inventory challenge becomes particularly acute ahead of major ecommerce events. As tracked in Adobe's Holiday Shopping Report, consumers spend hundreds of billions of dollars online within compressed promotional windows. Inventory must not only be available across the network but also positioned weeks in advance to support expected demand surges. A stockout during Prime Day or Cyber Week can result in more lost revenue than weeks of normal demand, while excess inventory after the event can lead to months of carrying and markdown costs.
In practical terms, this means planning teams need the ability to:
- Sense demand changes
- Identify forecast bias and demand-shaping events
- Optimize inventory by node and channel
- Balance Amazon requirements with broader network priorities
- Simulate service, cost, and revenue trade-offs
- Reallocate inventory before problems become execution issues
Digital tools like Multi-Echelon Inventory Optimization (MEIO) provide the enterprise architecture required to deploy these capabilities at scale. For global consumer goods organizations, optimizing inventory positioning across distribution networks delivers a 7% reduction in inventory holdings while lifting On-Time In-Full (OTIF) fulfillment by 3% to 5%.
“A true connected planning process and toolset allows companies, customers, and suppliers to operate from a shared view of demand, supply, inventory, and risk. That makes it easier to align on priorities, resolve exceptions, and keep products flowing. ”
Tony Schlader
Account Executive, Consumer Products
How Customer and Supplier Collaboration Improves Ecommerce Execution
Customer and supplier collaboration improves ecommerce execution by giving teams a shared view of promotions, demand, inventory, capacity, lead times, and risks. This helps companies resolve exceptions faster and coordinate supply decisions before availability or fulfillment is affected.
On the customer side, companies need better visibility into promotions, ordering patterns, inventory positions, service expectations, and future demand drivers. With Amazon, this may include vendor forecasts, purchase orders, sell-through signals, chargebacks, availability metrics, and promotional plans.
On the supplier side, companies need clear visibility into capacity, material constraints, lead times, production schedules, and potential risks. When demand shifts quickly, supply teams need to know whether suppliers can respond, where constraints exist, and what alternatives are available.
When this information is managed through spreadsheets, emails, portals, and disconnected systems, response time slows. Teams spend more time reconciling data than making decisions.
A true connected planning process and toolset allows companies, customers, and suppliers to operate from a shared view of demand, supply, inventory, and risk. That makes it easier to align on priorities, resolve exceptions, and keep products flowing.
How o9 Supports Ecommerce Supply Chain Planning
o9 supports ecommerce supply chain planning by connecting demand planning, inventory optimization, supply planning, and supplier collaboration on one planning foundation. By combining sell-in, point-of-sale, customer, supplier, inventory, promotion, and network data, planning teams can detect changes earlier, evaluate business trade-offs, and coordinate decisions across functions and channels.
This enables planning teams to:
- Improve forecast accuracy using richer demand signals
- Detect demand shifts, bias, and exceptions earlier
- Optimize inventory across the end-to-end network
- Evaluate trade-offs between service, cost, and working capital
- Collaborate with customers and suppliers in a shared planning environment
- Respond faster when ecommerce demand changes
The cost of disconnected planning is not abstract. One fast-growing ecommerce retailer found that the shared spreadsheets it relied on were quietly creating silos and stalling growth. By moving to a connected planning model with o9, the company hyper-localized its forecasts, optimized inventory across its fulfillment network and reduced out-of-stocks and waste simultaneously. It achieved the kind of dual improvement that disconnected systems make nearly impossible.
Ecommerce growth creates complexity. But with the right planning model, companies can turn that complexity into a competitive advantage.
About the authors
Tony Schlader
Account Executive, Consumer Products
Tony Schlader is an Account Executive at o9 Solutions, supporting the Consumer Products industry. He has 14 years of experience in supply chain management and logistics within the consumer products and healthcare industries. He holds a Bachelor's Degree in Supply Chain Management from Michigan State University.
