On demand Webinar

How to Ignite Your Inventory Potential: Expert Q&A Session

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Summary for busy teams

  • Problem: Overstock, stockouts, and spreadsheet-led buying decisions drain cash, inflate warehousing and handling costs, and often end in discounting that erodes margin.
  • Solution: Use forecasting and inventory planning to turn historical sales + live stock signals into smarter purchase decisions—supported by connected systems—so teams prevent excess earlier and respond faster when demand shifts.
  • Who it’s for: Retailers and ecommerce operators managing broad assortments (variants like size/color, seasonal drops, continuity lines) who need tighter control without slowing growth.
  • Outcome: Reduced carrying costs, fewer missed-sales moments, cleaner assortments, faster replenishment decisions, better availability, and stronger profitability, while cutting avoidable waste.

In this session, Mark and David break down why inventory discipline is one of the most practical ways to reduce waste while improving cash flow and margins. They unpack the hidden costs behind overbuying, storage, insurance, freight, operational drag, and last-minute markdowns, and show how better forecasting helps teams stay closer to the “right amount” of stock. You’ll hear how fashion brands can plan at variant level, how new products can be forecast by linking to comparable past items, and why proactive overstock signals matter while there’s still time to act. The takeaway: inventory becomes an asset when decisions are data-led, repeatable, and connected across teams.

What you'll learn in this Masterclass

  • How “right stock, right place, right time” protects margin and reduces avoidable waste
  • Why proactive overstock detection beats end-of-season firefighting
  • How forecasting at variant level (size/color) improves decisions for fashion and complex ranges
  • How to plan new SKUs by linking them to prior products (and even weighting multiple predecessors)
  • The difference between inventory management (accuracy + execution) and inventory planning (future buys + POs)
  • Why spreadsheets break down as SKU counts and channels scale—and where automation saves time and errors
  • How to think about AI in forecasting responsibly: value first, hype last

Why forecasting, buying, and cost control get complicated in retail

Inventory sits in the middle of every competing priority: growth, availability, cash flow, and customer experience. The problem is that decisions are often made under pressure—lead times, seasonal shifts, and “we can’t afford to sell out” fear create reactive purchasing. As product catalogs expand, this becomes less manageable with manual processes, and mistakes scale fast.

Common friction points include:

  • Excess stock that looks “fine” until it starts compounding costs (space, handling, insurance, capital tied up)
  • Stockouts on winners that send shoppers to competitors and waste acquisition spend
  • Unclear true profitability because holding costs aren’t fully understood or allocated
  • SKU sprawl where a small set drives results, but the long tail absorbs cash and complexity
  • Data inconsistency when teams pull metrics from different weeks/sources and don’t trust the numbers

Frameworks & tactics covered

Getting honest about the real cost of inventory

  • Move beyond simple “price minus COGS” thinking profitability requires fuller cost visibility
  • Factor in carrying costs: warehousing, insurance, security, and the operational overhead of holding stock
  • Include landed cost (freight, duties, shipping, insurance) so margin decisions reflect reality
  • Aim for “better than perfect”: even partial accuracy beats ignoring holding costs entirely

 Preventing overstock before it becomes dead stock

  • Monitor sell-through and future risk, not just what’s already sitting on shelves
  • Act early while there’s still time to promote, bundle, or adjust pricing strategically
  • Use alternative recovery paths when needed: bundles, donations (where appropriate), outlet partnerships

 Forecasting new products without guessing blindly

  • Anchor forecasts to comparable historical items whenever possible
  • Link new versions of products to previous SKUs to inherit meaningful demand history
  • Use weighted history when a new item replaces multiple older products

Faster decisions through better systems

  • Use automated, connected reporting to reduce manual errors and time lost to spreadsheet upkeep
  • Build confidence in decisions by relying on consistent, timely, “single source” reporting
  • Standardize how teams judge winners/losers so assortment decisions become repeatable

 AI and forecasting: a disciplined mindset

  • AI can improve forecasting, but only when it’s implemented carefully and tested against outcomes
  • Avoid “AI for marketing”—prioritize accuracy, explainability, and customer value over hype

Who this is for

This session is particularly useful for:

  • Ecommerce and Retail Ops leads responsible for availability and execution
  • Inventory planners, supply chain teams, and warehouse managers
  • Buyers and merchandisers managing size/color variants and seasonal cycles
  • Finance teams focused on working capital, holding cost, and margin leakage
  • Founders/COOs scaling SKU counts and channels without scaling chaos

Key takeaways

  • Overstock and stockouts are two sides of the same planning problem, and both destroy profitability in different ways
  • Carrying costs are real, compounding, and often underestimated; measure them to make better assortment calls
  • The earlier you spot future overstock risk, the more options you have to recover value
  • New product forecasting works best when tied to similar historical products, not gut feel.
  • Spreadsheets can start the journey, but automation and integrated data win as complexity grows
  • AI belongs in forecasting, but only when it improves accuracy and trust, not when it’s used as a label

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