Barilla Spa Case Brief

Name: Wayne Kennedy                             Date: 4/8/18                                         IC: Cate Meyer

Problem Statement

The ordering procedures model followed by the distribution organizations, be it DOs, GDs, or Barilla’s own depots, has not been an efficient model to address the fluctuating demand resulting in thinning margins. A lack of transparency in the distribution organizations’ (DOs, GDs, Barilla’s own depots) data has created a void in forecasting models available to Barilla, creating stockout as well as overstock issues in warehouses, thus reducing margins.  

Situation Analysis

        Currently, Barilla utilizes a distribution ordering procedure that sees its distribution organizations currently responsible for fulfilling their orders for inventory based on simple, periodic-review inventory system. This system is where a distribution warehouse will typically place orders for product, in this case, Barilla products, when inventory levels dip below a pre-determined number. In addition, distribution organizations would check inventory levels and place orders based on these levels with Barilla once a week. Product would then be shipped to the distributor with a standard lead time of 10 days.

        This ordering procedure noted above shows that the distribution organizations do not take advantage of its data, thus do not attempt to forecast the product they may need more or less of. Rather, this method of level checking can fail to forecast a swing in demand as independent demand may increase or decrease at the consumer level. The current system fails to recognize the value of data to forecast the independent demand of a Barilla product. To address the fluctuating demand and thinning margins, data needs to be transparent and shared, as it currently is not. Additionally, forecasting models should be implemented as well.

Recommendations

        As stated in the problem statement, Barilla’s main issues surround thinning margins and fluctuating demand. By implementing a system known as Just-in-Time Distribution (JITD), Barilla will be able to address these problems.

        Essentially, by shipping products only as needed, Barilla will be responding to what the independent demand is calling for, thus side stepping, rather addressing the volatile demand patterns of the distributor. If this new method is followed, distribution costs would be reduced by missing out on sales for stockout items in addition to not having to have fire sales of overstocked products. In addition, inventory levels would be reduced. Given the minimum shelf life of Barilla’s dry products of 10 to 12 weeks, Barilla’s Central Distribution Centers (CDCs) could hold onto product and distribute according to the need of a given distributor, again supplying only when needed. Finally, manufacturing costs would ultimately be reduced. This would occur because the CDCs would be distributing product to distributors more efficiently based on need, thus avoiding the fluctuating stocking problems, requiring less product for lower independent demand items, truly focusing on items that are able to sell. CDCs would not have to stock up on un-needed product.

        The negative aspects of shipping products only as needed can result in missed sales if the independent demand had an immediate uptick for all regions, thus overloading the stock currently held and creating strain at the manufacturing level. Additionally, distributors main feel pushed aside, creating a feeling that they have lost control of there stock. All of this can be addressed through forecasting.

        In addition to shipping products only as needed, a forecasting department should be created to take in data, which includes what has been shipped out of the distributor warehouses to retailers during the previous day and current stock levels for each Barilla SKU. By creating a solid forecasting method, Barilla may be able to side step any wild swings and fluctuations in the market.