STORIES · SALES & DISTRIBUTION
The customer sees the offer. The organization must see the entire system behind it.
Sales and distribution connect the customer, channels, pricing, product data, availability, inventory and logistics. In an omnichannel model, every one of these elements affects the others, and a locally rational decision can reduce the performance of the system as a whole.
Transformation begins when stores, e-commerce, B2B, marketplaces, purchasing and logistics stop operating on separate versions of data and objectives and start working with shared rules, accountability and metrics.
4 STORIES
- 01OMNICHANNEL & PRODUCT AVAILABILITYA commercial organization operating across e-commerce, stores, B2B and marketplaces
- 02PRICE, DISCOUNT & MARGIN DISCIPLINEB2B distribution with a broad portfolio and individual customer terms
- 03PRODUCT DATA & CONVERSIONA broad product catalogue published simultaneously across many channels
- 04DEMAND FORECASTING & INVENTORY TURNOVERDistribution covering stable, seasonal and project-based assortment
OMNICHANNEL & PRODUCT AVAILABILITY
OMNICHANNEL · E-COMMERCE · OMS · ATP · ERP · WMS · ORDER ROUTING
How to turn five versions of availability into one promise to the customer
CONTEXT
A commercial organization operating simultaneously across e-commerce, physical stores, B2B sales, marketplaces and project-based sales. Tens of thousands of SKUs, owned inventory, dropshipping and products available only on order. Each channel had evolved independently and developed its own logic for determining availability.
PROBLEM
The question 'is this product available?' had several correct answers. E-commerce saw the central warehouse. A store saw its own shelf. A B2B salesperson saw their own reservations. Marketplaces received periodically updated data. Inbound stock, reservations tied to unfinished quotations and inventory in other locations remained outside the channel's view. The effect worked both ways: some customers ordered products the organization could not deliver, while the same SKU remained unused elsewhere. Excess and shortage existed simultaneously. The real problem was not the warehouse. Inventory was being managed as the property of individual channels instead of as an organizational resource.
CHANGE
One shared Available-to-Promise model was introduced across all channels. It separated physical stock from the quantity the organization could actually promise to a customer. The model included inventory across locations, active reservations, inbound stock with confirmed delivery dates and returns. Channels stopped answering customers with a stock quantity and started answering with a reliable date. The second step was intelligent order routing to the appropriate fulfilment location. Delivery cost, customer location, inventory age and the risk of creating a shortage elsewhere were taken into account. The technical change was connected to a new internal settlement model. A location fulfilling an order generated by another channel received appropriate economic recognition. Only then did omnichannel stop being a systems architecture and start working operationally.
MY ROLE
Responsibility for the availability model, ERP/WMS/channel integration architecture and the rules for reservation and order routing. In parallel, designing the internal settlement model that removed conflicts of interest between channels and locations.
RESULT
Cancellations caused by unavailable inventory fell to a marginal level. Inventory turnover improved because products were no longer locked into the location where they happened to be stored. The organization released working capital without reducing service levels. Inventory visibility began replacing safety stock held 'just in case'.
ADVANTAGE
The same inventory started supporting more sales. Availability stopped being an accident of channel and location and became a parameter the organization could manage deliberately.
FROM THE PROJECT
Analysis of cancelled orders showed that some apparent stock shortages involved products physically present in the warehouse but reserved for quotations that had remained open for months.
Reservations had no expiry date.
Introducing expiry rules and full visibility of inventory blocks released stock before the main integration had even been launched.
Before ordering more inventory, check how much of what you already have has been promised to someone who has long forgotten about it.
PRICE, DISCOUNT & MARGIN DISCIPLINE
PRICING · CPQ · CRM · ERP · BI · TRANSACTIONAL PROFITABILITY
How to recover margin no one consciously gave away
CONTEXT
B2B distribution with a broad portfolio, individual customer terms, multiple discount groups, supplier promotions, project pricing and historical special conditions. Margin was reported at company level, but decisions affecting it were made at individual quotation-line level.
PROBLEM
A salesperson making a pricing decision knew the purchase price and sales target but did not see the full cost of serving the customer or the economic consequence of the discount being granted. Special terms remained active long after the project for which they had been granted had ended. Discounting was treated as a way to close a transaction rather than as a cost. Revenue grew while profit did not. A healthy average margin concealed a long tail of transactions below the profitability threshold.
CHANGE
Pricing was redesigned as a decision process. The foundation became transactional profitability, including not only purchase cost but also logistics, payments, returns, after-sales service and the cost of capital tied up in inventory. Segmentation by revenue was replaced by segmentation based on customer value and cost to serve. Decision thresholds defined the autonomy of salesperson, manager and executive management. CPQ provided a price recommendation while the quotation was being prepared, based on comparable transactions, customer profile and category characteristics. Special prices received expiry dates. Discounts gained an owner. The sales incentive system shifted from revenue to margin after cost to serve.
MY ROLE
Responsibility for the transactional profitability model, pricing architecture and decision rules. Integration of sales, purchasing and cost data, and leading the change in the incentive system and customer terms requiring correction.
RESULT
Margin improved primarily through eliminating unprofitable transactions rather than through mechanical price increases. Quotation lead time shortened because negotiation boundaries were defined in advance. Discount became a measurable value with an owner and was evaluated against the outcome it was intended to purchase.
ADVANTAGE
Price became an organizational decision rather than the outcome of an individual negotiation. The company regained the ability to choose consciously when, to whom and in exchange for what it was worth giving away part of the margin.
FROM THE PROJECT
The most uncomfortable project material was a simple chart of transactional profitability.
It showed the exact point at which the company stopped earning money.
A large part of the unprofitable tail came from one of the organization's strongest salespeople. Not because they were performing poorly. Quite the opposite: they were doing exactly what the organization rewarded, more effectively than others.
Nobody gives margin away consciously. It disappears through hundreds of small decisions, each of which looks reasonable on its own.
PRODUCT DATA & CONVERSION
PIM · E-COMMERCE · MARKETPLACE · SEARCH · MERCHANDISING · ERP · DATA QUALITY
How to sell what the customer cannot find
CONTEXT
Dozens of suppliers, multiple data formats and one broad product catalogue published simultaneously across e-commerce, marketplaces, B2B, sales quotations and printed materials. The same product had different names, descriptions and sets of attributes depending on the channel.
PROBLEM
Store traffic was growing while conversion remained flat. Analysis of internal search showed that some customers ended their session before ever reaching a product. Not because of price. Because of data. Products without complete attributes disappeared from filters and search results. They physically existed, were available and competitively priced, yet from the customer's perspective they were effectively not on sale. Incomplete product data also generated returns, complaints and additional customer-service workload. Product data had been treated as marketing content. In reality, it was sales infrastructure.
CHANGE
PIM became the single source of product information for all channels. A shared taxonomy, attribute model and dictionaries were created to map supplier data into the organization's structure. Data ingestion was automated and validated. A minimum information standard was defined before a product could be published. Data completeness stopped being an aspiration and became a condition of going to market. Data quality began to be measured by category and supplier. Internal search data and customer behaviour started feeding merchandising and taxonomy development.
MY ROLE
Responsibility for product-information architecture, taxonomy, attribute model and PIM integration with ERP, e-commerce and external channels. Defining the product onboarding process and the quality requirements expected from suppliers.
RESULT
Conversion increased without increasing traffic-acquisition spend. The same customer started reaching products that had previously remained invisible. Product visibility also improved in external search engines and marketplaces. Time to introduce new products across all channels fell from weeks to days, while returns and customer-service queries about basic product information decreased.
ADVANTAGE
New channels and categories could be launched without a proportional increase in manual work. The product catalogue stopped being a collection of files and became an organizational asset.
FROM THE PROJECT
In one category, customers repeatedly used an informal product name that none of the suppliers used in their official descriptions.
The products were in stock and competitively priced. The system simply did not understand the customer's language.
Adding a synonym layer based on real customer searches improved category discoverability without changing the assortment, price or advertising budget.
The customer tells you exactly what they want in the search box and what you are failing to sell them. They usually do not ask twice.
DEMAND FORECASTING & INVENTORY TURNOVER
DEMAND PLANNING · FORECASTING · S&OP · ERP · WMS · BI · INVENTORY OPTIMIZATION
How to stop buying for quarter-end targets and start buying for demand
CONTEXT
Distribution covering both stable-demand products and seasonal, promotional and project-based assortment. Lead times ranging from a few days to many weeks. Purchasing decisions were based primarily on sales history, supplier terms and buyer experience.
PROBLEM
Inventory was growing faster than sales while stock-outs were increasing at the same time. Sales history was treated as demand history, even though it did not capture customers who wanted to buy an unavailable product. Supplier discount structures encouraged larger purchases, while the cost of capital tied up in stock remained invisible in buyer metrics. The same forecasting method was applied to products sold every day and to items purchased only a few times a year. As a result, working capital remained trapped in the wrong inventory while availability of critical products remained too low.
CHANGE
Assortment was segmented according to value, frequency and predictability of demand. Stable products used forecasting models incorporating seasonality, trend and the commercial calendar. Project and low-frequency products used information from the sales pipeline and market. Unfulfilled demand was added to the model: stock-outs, abandoned baskets for unavailable products and quotations lost because of delivery time. Inventory parameters began to be recalculated regularly using target service levels, demand variability and actual supplier lead times. Sales, purchasing and finance were connected through a regular S&OP cycle. A systematic process was also introduced for identifying and liquidating dead stock, with an owner and mandatory decision date.
MY ROLE
Responsibility for the demand-planning model, assortment segmentation, replenishment rules and integration of sales, purchasing and logistics data. Designing the planning cycle and changing the metrics used to evaluate buyers.
RESULT
Inventory turnover improved while availability of critical assortment increased. The share of slow-moving and dead stock declined, releasing working capital. The number of manual purchasing decisions also fell, allowing buyers to focus on the assortment where their knowledge genuinely added more value than the model.
ADVANTAGE
Higher availability with lower inventory. Working capital stopped being hostage to supplier discount thresholds and commercial terms.
FROM THE PROJECT
The warehouse contained an SKU ordered two years earlier for a major contract that was ultimately never completed.
The product was not sold because doing so would have meant formally recognizing a loss.
After two years, the cost of financing the inventory exceeded the loss the organization had been trying to avoid. The product was sold within one quarter.
From that point onward, every inactive inventory position had an owner, a deadline and a mandatory decision.
The most expensive inventory is the stock nobody wants to make a decision about. You pay for it every month; you just never see the invoice.
COMMON DENOMINATOR
Sales and distribution are an uncompromising test of organizational coherence.
The customer expects one price, reliable availability, complete information and a predictable delivery date. They do not care how many systems, warehouses, channels or organizational structures exist on the other side of the transaction.
Technology should hide this complexity from the customer while making it visible to the organization.
EXPLORE OTHER STORIES
Do not start with technology. Start with the result.
If you see a problem, an opportunity or a change that cannot be addressed with another standard project, let's talk about the result you want to achieve.