Inventory Planning
In medieval times, people in society were dependent on each other & the market is one such place where those inter dependencies came together. But back then understanding and meeting needs didn't need high speed internet, predictive analytics or star ship enterprise delivery networks. Over the years retailers have evolved with integrated planning & execution, shelf connected and consumer connected supply chains. Today, customers have multiple options and a bouquet of choice, the inter dependencies have been redefined. The need to ensure the right inventory, available at the right time, in the right place & right quantities while balancing working capital is a prerogative for survival.
Whether online, omni-channel or brick & mortar stores, the supply planner seldom has his work cut out...
> Anticipation inventory: “additional inventory, above baseline stock to cover projected trends of increasing sales”
> Safety Stock: "quantity of stock planned to be in inventory to protect against fluctuations in demand or supply"
> Lot-size inventory: "purchase in quantities greater than which is actually needed to take advantage of discounts", dealer incentives on full truck load purchases, etc.
> Cycle stock: inventory that gradually depletes over time from regular purchases.
> Hedge inventory: rarely used –this involves buying or "contractually agreeing additional inventory at a set price when supply or pricing is at risk."
Depending on a number of demographic factors like household size, lifestyle, location & income, some basic consumer purchases on the other hand, can be classified as:
< Consumption - perhaps the most predictable element of consumer demand is regular purchases of routine consumer goods.
< Promotion - often to take advantage of discounts & markdowns, sometimes consumption increases, advance purchase or stockpile purchases are experienced.
< Emotion - Impulse purchases, often when the need is instantaneous or not anticipated.
Implications for demand management
While traditional, non-discriminant methods offers a good baseline forecast, it cannot be relied upon solely. One needs to take into account market or location-specific trends, events, seasonality, pricing, promotions and in-store activities. Most demand management tools offers a time-phased demand planning forecast. If used in collaboration with supply partners, one has the ability to envisage what, where & how much will sell, more often at an aggregate level over the extended period. Planning and considering these elements would need close alignment to the retail mix: Merchandise, Location, Store design & layout, Advertising & Promotion. Thus retailers can make more informed decisions on:
Assortment: Align with purchase patterns to provide ranges specific to local or regional customer. Using processes & data mining techniques, one can filter options to generate custom plans matching product & merchandise strategies.
Space Management: Ensure floor space has an ideal mix providing customers with an ease of shopping experience. Take advantage of drive aisles, end caps & snake cues to position impulse items.
Allocation & distribution: Use a mix of pull and push techniques to ensure credible displays. Bin levels, Min| Max & re-order point are common approaches in some automatic replenishment systems, but where no baseline demand exists, a push approach might be favored.
A further refinement would entail leveraging customer activity and product data across consumption, trend & seasonal dimensions. Below is a model of how this can be applied on a normal distribution with practical suggestions for ordering and allocation of inventory:
Finally: Sales & Operations planning is a crucial part of the process. While the dynamics might differ depending on your business, categories & supply chain, it is an iterative process:
*Remember: forecasts are seldom right but often useful...
Implications for demand management
While traditional, non-discriminant methods offers a good baseline forecast, it cannot be relied upon solely. One needs to take into account market or location-specific trends, events, seasonality, pricing, promotions and in-store activities. Most demand management tools offers a time-phased demand planning forecast. If used in collaboration with supply partners, one has the ability to envisage what, where & how much will sell, more often at an aggregate level over the extended period. Planning and considering these elements would need close alignment to the retail mix: Merchandise, Location, Store design & layout, Advertising & Promotion. Thus retailers can make more informed decisions on:
Space Management: Ensure floor space has an ideal mix providing customers with an ease of shopping experience. Take advantage of drive aisles, end caps & snake cues to position impulse items.
Allocation & distribution: Use a mix of pull and push techniques to ensure credible displays. Bin levels, Min| Max & re-order point are common approaches in some automatic replenishment systems, but where no baseline demand exists, a push approach might be favored.
A further refinement would entail leveraging customer activity and product data across consumption, trend & seasonal dimensions. Below is a model of how this can be applied on a normal distribution with practical suggestions for ordering and allocation of inventory:
Finally: Sales & Operations planning is a crucial part of the process. While the dynamics might differ depending on your business, categories & supply chain, it is an iterative process:- Begin with a forecast
- Set a target
- Create a demand plan
- Match supply capacity
- Review & refine demand plan according to supply capacity
- Create a supply plan
- Demand and Supply should now be synchronized
- Execute to the Plan
- Monitor & measure the execution.
- Reconcile & re-plan
*Remember: forecasts are seldom right but often useful...