What is the problem? Huge distributor of pharmaceutical goods serves more than 10 thousands retail stores and hospitals as well as 300 their own retail drug stores is implementing TOC Supply Chain Solution. It required from the company to shift for pull replenishment. In its turn it required the ability of the Company’s Distribution Center (DC) to pick up 3 times lines more than ever daily. DC keeps 8500 SKU. The easiest solution which lies on top is: 1) to increase DC squire and its equipment, 2) increase of personnel, 3) increase the number of shifts per day. But such an “easy” solution immediately requires increase in investment and operational costs. At the start it looks quite difficult taking into account also the fact that ТОС Supply Chain Solution was initiated exactly for net profit increase which looks poor at the start.
The direction of the solution. We’ve assumed that current operational processes at the DC can contain local efficiency policies which are “eating” its capacity. So the task was to be able to change the DC processes in a way that will increase capacity significantly without additional investment and with minimal increase in operational costs. DC of a huge distribution company by itself reminds operational environment with alike characteristics and UDE’s like: 1) huge investment into capacity and equipment, 2) tendency to increase efficiency per resource (in this case – per person), 3) interdependencies of operations and high uncertainty inside. That’s why we decided as possible to apply some approaches and solutions from ТОС МТА in order to get more capacity.
What was our thinking and approach to the analyses? At the start we’ve considered our own drug store chain cause we earn there more. Traditional replenishment in the company generated approximately 100 lines per day. It was the number which was generated by drug store daily orders. TOC Replenishment requires to replenish what was sold yesterday. Thus we get approximately 400 lines per drug store per day. Such difference (from 100 lines to 400 lines per drug store per day) has shown us such capacity requirements if we are going to replenish what was sold yesterday: not 150*100=15000 pick up lines at DC but 150*400=60000 pick up lines at DC. Here we consider only 150 drug stores as a separate geographical part just for easiest illustration of the logic and calculations.
The new solution mechanics. We decided to consider DC as the system’s CCR. DC consists of 2 zones: pallet storage and conveyor. Pallet storage is designed for pallet stock pick up and keeping of manufacturers boxes. The conveyor is designed for orders pick up which consists of many SKUs with relatively low number of items for each SKU line. For instance: one manufacturing box consists of 100 items of a Product X. meanwhile for each line this is not more than 1-5 items.
Considering the conveyor more precisely it’s occurred that the equipment there is rather expensive. It’s hard and more expensive to expand in comparison to pallet stock keeping. There are 2 conveyor parameters: how many SKUs can be kept there and how many pick up lines it can ensure.
The reasons under which the conveyor capacity was “abused” by the goods that are not needed right now:
- The conveyor holds currently the particular SKU with particular serial number (it’s specific of pharmaceutical goods) but the headquarter requires to pick up another serial number for some other clients. This is analogy with manufacture when in current manufacturing process the urgent change is inputted and you need to stop manufacture of one goods and to switch to the other);
- There are 2 stock keeping zones at the DC – pallet and conveyor. If the conveyor holds overstock but additional small portion of goods has arrived than again we are putting it into conveyor zone.
- The conveyor is replenished due to forecast.
What factors influence the number of pick up lines? The storage of particular SKUs at the conveyor. The more situation of a “right” SKU location we will have the less time the employee has to reach the particular cell, pick up particular SKU, put it into the tray. This tray in its turn comes by conveyor to another employee in order to be filled in by another SKU. Only after the tray will reach the control point and packaging..
So like this we’ve considered the Gap in current way of cells utilization as a reason of the Gap in low number of pick up lines. The conveyor is designed to keep stock for 2 days. However some SKUs have stock close to zero and we are forced to replenish them urgently or / and not in a right place. Meanwhile the significant number of SKU has stock for more than 5, 10, 20 and even 30 days. So the Gap in pick up capacity was as a result of a Gap in availability that in its turn was the result of the keeping policy. The keeping policy was that SKU with often reference are kept in more “slowly” locations (less available) and at the same time SKU with less often reference are kept in “locations - high runners”. Thus we get a UDE and the next task is to catch the policies which brings us the them.
It’s quite obvious that under our suspicion the replenishment algorithms but besides we’ve got the following. If we get SKUs in manufacturer’s boxes they are located in conveyor besides the fact that the stock of them is already enough. Also in a current rules which are left from distribution mentality and practice the headquarter was defining from which series of the same SKU which orders of drug stores should be picked up. As a result if SKU/series which is kept at conveyor is not the same with SKU/series which was defined for pick up than selected SKU/series should be located in conveyor. As a result – one more cell is occupied.
What was implemented and what is the result. We’ve eliminated the firs policy – no more manual administration of series of particular SKUs. Decreased the number of small good arrivals to DC. Elimination of only these 2 reasons has increased the number of pick up lines to 70 thousands lines per day. The changes are continued.
Unique insight. At the moment the company got such a result at DC which was never expected the company at once got the temptation to increase lines sold into wholesale. It’s the same as if increase capacity of a very expensive resource which is CCR we are selling at the lowest price. We’ve already shown this problem to the company and fixed the case. Its truly profitable to convert this additional capacities into additional Throughput in our Retail.