DRP systems operate by breaking down the flow of finished goods from the manufacturing plant through the “Distribution Network” of warehouse and transportation modes. This is undertaken on a time-phased basis (in DRP terminology referred as time bucket) to ensure that the required goods flow through the distribution network system are available as and when required at right place, at the right time.
Integrated systems (Production, warehouse, transportation, forecast, Inventory etc) of this nature require sophisticated, computerized information systems as their basis.
Information Requirements :
a) Base Level Usage Forecast - Forecast data should be at SKU / Item level for Product axis and any level below warehouse or DC for customer. Product axis is SKU / Item level as the Company raise invoice at SKU / Item level to customer, whereas “Distribution Network Design” of that company decides the customer axis level.
b) Distribution Network Design - Distribution Network Design may change from company to company of similar Industry. For example HP and Dell company manufacturing computer machines belong to computer hardware industry but their distribution network design differ as per given below diagram.
c) Inventory Status - Inventory availability status at various distribution centre level. This includes Transit stocks (ie stocks already dispatched from factory but not reached DC)
d) Ordering data - Time phasing or schedule flow, the factory should deliver the materials to each DC. For example factory can be asked to dispatch an item to DC at Kolkata on weekly basis (Monday) whereas to another DC at Mumbai on Fortnightly basis due to lower demand in that region.
DRP Process Requirements :
a) Net Requirement (NR) computation - Forecast at SKU / DC level is used in the DRP process. However some Inventory referred as “opening stock” are already available at DC. There could be materials lying “In transit” i.e., materials which has already been dispatched from factory are yet to reach DC. These inventory i.e., opening and In transit stocks has to be adjusted or netted against the forecast volume to arrive net stock requirement at each SKU / DC.
Since demand is volatile in nature, the company may prefer to keep buffer stock referred as “Safety Stock” to meet unexpected demand fluctuation. Safety Stock criteria will differ for each item as per nature of product and each DC due to demand nature. For example Hundai Car company will keep different safety stock Norms for Santro and Accent Model due to categorization. Similarly the company keep different safety stock norms for Santro between DC at Northern and Southern Region due to demand nature.
Net Requirement is computed based on Forecast Volume + Safety Stock – opening physical stock – In transit stock.
Let us take an example of Santro car at Delhi DC. The forecast volume for next two months are 9,000 and 7,500 Units respectively. Delhi DC is already having 1,500 Units as opening stock and expected to receive In Transit stock of another 1,000 units in next two days. DC is expected to keep 5 days stocks of second month forecast volume as safety stock. Assuming 25 days are working days in a month. Then how to compute Net Requirements ?
Ist Month Forecast Volume - 9,000 units
2nd Month Forecast Volume - 7,500 units
Opening Stock - 1,500 Units
In Transit Stock - 1,000 Units
Safety Stock - 2nd Month Forecast Volume *(Safety stock days/No of Working days)
- 7500 *(5/25) = 1,500 Units
Net Requirement = 1st Forecast volume + Safety Stock – opening Stock – In Transit Stock
Net Requirement (NR) = 9000 + 1500 – 1500 – 1000 = 8000 Units
Hence the Hundai Manufacturing plant will produce 8000 units of Santro instead of 9000 units against the Delhi DC requirements. Please note that Safety Stock computation methodology differ from company to company.
b) Time Phasing Requirement : Time Phasing means when the company wants to move the products from Manufacturing plant to DC. This could be monthly, fortnightly, weekly basis. As per above example if the Hundai plant decided to send 8000 units of Santro car so as to reach Delhi DC by 3rd of August to meet August Sales. Delhi DC has to keep huge godown to accommodate all 8000 units and require more manpower to maintain the santro cars at their end. However if the company decide to send 45% of NR i.e., 3600 units on 3rd, 35% of NR i.e., 2800 units on 13th respectively and 20% of NR i.e., 1600 units on 23rd August to Delhi DC. This enable the DC to keep minimal stocks at hand with optimum storage space and manpower by providing the good service level to the customers. For FMCG company like Cadbury the time phasing for Bournvita product could be once in 3 days. Time Phasing differs for each Product and DC.
Time Phasing depends on “Distribution Network Design”. For example if manufacturing plant is located at Singapore and Central Distribution is located at Mumbai, the lead time i.e., shipping the product from Singapore to Mumbai is three months then the time phasing could vary according to demand for the product. Let us assume perfumes manufacture at French has got CDC at Mumbai and their lead time is three months. In this case the CDC may plan to get three months consolidated stocks once in three months to avoid stock out situation.
c) Planned order Release - In the earlier time phase we have given exact quantity and schedule date of stocks to be received at DC. However we need to communicate when the dispatch to be effected from plant so that the materials reach DC on scheduled date. In order to calculate the Planned order Release, we need to know the Lead time from Plant to various DCs. For example in the Hundai example the plant is located at Chennai and Lead time from Chennai plant to DC at Delhi is 7 days. The planned order release date should be 7 days less of schedule date and also to ensure that that day is working day.
One can understand that DRP is effective only if there is timely data sharing between different functions. Managing time phasing manually is another cumbersome process and hence it is recommended to have proper DRP package at your disposal which should be flexible and properly designed to cater the “Distribution Network Design” changes. DRP package should be more robust and flexible so that it can compute the quantity basis UOM, FTL (Full truck load).
So far we have learnt about DRP and computation methodology with simple example. At the outset it may look easy but in reality defining time phase for each SKU at DC level is difficult part and this will keep on changing as per market dynamics. When the company is having more Products and DC then it lead to more complication and maintenance will become big issue. When the company changes its “Distribution Network Design” by opting for more plant or DC then the DRP module has to realigned accordingly.
In the next session we will learn more about DRP.