Observe Exhibit 12. What are the underlying causes and drivers that make order patterns to look this way? Provide a discussion on these causes/drives to show how they are causing the resulting demand pattern. Examples of items to consider include transportation discounts, promotional activity, product proliferation.
The BARILLA case is an illustrative example where we can understand the effects of a phenomenon which is very common among industries that is called the Bullwhip effect. As an immediate outcome this phenomenon creates large swings in demand on the supply chain resulting from relatively small, but unplanned, variations in consumer demand that escalate with each link in the chain .Events that can trigger begin at any point in the supply chain: consumer, retailer, distributor, manufacturers, raw materials suppliers and so on. As orders progress up the chain, each level perceives a greater demand that it seeks to rectify from its own Lets discuss in more detail some of the causes that can trigger this event and we can identify in the case: • Promotions: Barilla’s sales strategy relied heavily on the use of promotions, in the form of price, transportation and volume discounts. They divided the year into 10 to 12 canvass or promotional periods, during which different products were offered at discounts. These price discounts ranged from 1.4% to 10%. Barilla’s volume discounts consisted of carton discounts offered by sales representatives and the transportations discounts consisted of free shipping to the distributors. • Sales Representatives: The compensation system for the sales reps was flawed in the sense that they were rewarded based on the amount of the products that they sold to the distributors. This was causing problems as the sales reps would try and push more products during the promotional period to get a bonus and were not able to sell as much during non-promotional periods. This led to wide variation in demand and made forecasting very difficult. • Large number of SKU’s: Barilla’s dry products were offered in 800 different packaged stock keeping units (SKUs). Most of the popular products were offered in as many as 8 different packaging options. These large numbers led to greater complexity. • Gaming Behavior: The distributors were used to having full control of their orders to Barilla and indulged in gaming by ordering different quantities in different periods. This led to variation in demand. • Bad forecasting by Distributors: The distributors did not have forecasting systems or sophisticated analytical tools for determining order quantities and this resulted in bad forecasts. • Long Lead Times: Barilla supplied its distributors between 8 and 14 days after it received their orders, the average lead-time being 10 days. This was slightly long and a lot could change in the supply chain during this period, causing rise in variability
• Batch Ordering.
In supply chain, companies decide how to place orders using inventory control mechanisms and models. The demand from the customers side can be smaller and more frequent which as a result depletes the inventory gradually. Companies wait until the inventory level reaches a predetermined minimum level (the reorder point) before the next order is placed. This requires orders to be placed periodically in batches. The supplier receives a large, highly erratic stream of orders with a spike during one cycle, but no orders for the rest of the period. Batch order can also occur for other reasons, such as orders being held until a greater shipment size is reached, as this will result in better transport rates. • Behavioural Causes
Each player in the supply chain of Barilla was acting for his own benefit and not as part of a sequence that each one is affecting each other with their action. • Shortage game.