Wednesday, May 28, 2008

Optimization: Transportation versus Inventory

In talking to a senior executive from a supply chain solutions company I heard an interesting comment last week – that more and more companies are looking at transportation optimization in the face of rising fuel costs. Of course there is a direct link between rising costs (see picture), and the desire to do something about it, but it also got me thinking about what other factors may be driving the interest in transportation optimization.

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Inventory

Traditionally the inventory has been the biggest focal point for supply chain managers. That makes sense as inventory consumes a substantial amount of operating cash flow for retailers. Assuming an inventory turns value of 7 for example, a retailer with $10B in revenues would have locked almost $1.5B of operating cash flow in the inventory. Therefore any reduction in the inventory results in more money available to other functions. However that is a double edged sword: achieve overly enthusiastic reduction in inventory and you will lose sales (and hence revenues) due to stock-outs, but under achievement results in bloated inventory that will eventually require clearance and pull down the margins.

Finding that golden “optimal” level that balances the two sides (service and excess) is hard to establish and harder to maintain as demand patterns evolve and change. Inventory joins the demand with supply – and it is this inherent position that makes it dependent on the supply and demand planning processes. In fact this dependence is very critical. The accuracy, stability and consistency of demand and supply planning processes affects the efficacy of the inventory planning. And that directly impacts the inventory levels and ability to service demand. Inventory planning typically uses demand, supply and lead-time for determining the optimal inventory levels to maintain a specific service level.

All the above makes it almost necessary to review these processes together to have any appreciable impact on the inventories. The combined impact of demand planning, inventory optimization, and supply planning processes can result in huge savings through reduced inventory in the system, lower clearance costs and better financial efficiencies. However it is a large effort and it impacts a large number of users in an enterprise. It also requires good clean master data and large amounts of historical transactional data, both of which need additional effort to obtain. This generally makes it a little more complex and requires a clear consistent strategy to successfully deploy. The rewards are bigger, but so is the effort leading up to it.

Let us also examine how the savings in inventory affect the company financials.

Inventories exist as assets (current assets to be specific) on the balance sheet. Any reduction in inventories therefore reduces the total assets and impacts the asset turnover ratio (see picture). A higher asset turnover ratio basically means that the corporation is able to generate the same revenue by deploying fewer assets than before. Assuming all else remains same, it results into higher ROA (return on assets) that can do wonderful things for a corporation like raise its share price, enable it to pay higher dividends, ability to expand or do any of the other things that spare change can do. Reduced inventories also reduce the inventory carrying costs (hence COGS), but the impact is relatively small because the fixed costs remain the same and only variable costs are reduced.

The financial impact largely makes the corporation more efficient in using the available resources.

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Transportation

Compared to the inventory optimization, transportation is a different story. It is almost an opportunity for the taking. No matter how the replenishment was decided, eventually what has been ordered needs to be moved from the suppliers to the retailer’s warehouses, and from then on to the stores. The transportation optimization just does not depend on other processes like the inventory optimization does. And almost all the data that this solution needs such as routes, rates, lanes, carriers, purchase orders, and weights/volumes of items is deterministic and largely available in the enterprise already. The only exception to this required data may be the volumetric and weights for the items but that too can be obtained in collaboration with suppliers. For an average retailer, shipping costs used to add up to 1.5 to 3% of the revenues (that is, when the oil was still not trading in the stratosphere, it would reasonably be higher now). Assuming a 2% rate, it is still a cool $200M for a $10B retailer. And unlike the inventory savings that indirectly improves ROA, any savings in transportation are immediately visible to the bottom line.

Here is the financial side of the story.

Shipping costs reduce the cost (hence COGS, cost of goods sold). With all else remaining same, it directly impacts the profitability or margin. First and foremost, profitability directly shows up in the bottom line, and provides extra cash for any other priorities. Then improved margin also improves the ROA (see picture) and allows the companies to do all the wonderful things we mentioned above that can be done with spare change.

Finally it looks like addressing inventory improves overall health but requires a broader approach to reviewing the business processes involved in supply and demand planning, but addressing freight costs is a quick solution to a specific problem of runaway fuel costs. And just as fortifying your diet with vitamins will make you stronger and healthier; an impending infection can only be cured with a strong dose of antibiotics. For now, inventory looks more like the vitamins while transportation is the strong dose of antibiotics. Take your pick!

Friday, May 16, 2008

Replenishment Policies and Inventory Planning

The two processes of replenishment and inventory are closely related. The inventory planning process establishes the optimal inventory levels that must be maintained to meet expected service levels for demand fulfillment. What does that exactly mean? To understand we need to explore the replenishment (or re-ordering) process. In doing so, we will also establish the decision parameters an inventory planning process provides for the replenishment to work at its most optimal levels.

Replenishment or Reordering

Reordering or replenishment process needs to define review period for reordering, and an ordering quantity. Then it needs the inventory parameters to determine whether an order for replenishment should be placed at the time of review or not. Based on how the review period and order quantities are defined, there are a few options to drive the reordering.

Continuous Review and Periodic Review

These terms refer to the frequency of review to determine when orders must be placed for replenishment.

In the continuous review process, the inventory levels are continuously reviewed, and as soon as the stocks fall below a pre-determined level (usually called, reorder point, or reorder level), replenishment order is placed. As more and more companies start using sophisticated IT systems to track their inventories in real-time, the continuous review method becomes a viable and optimal way to plan for replenishment.

Under periodic review, the inventory levels are reviewed at a set frequency. At the time of review, if the stock levels are below the pre-determined level, then an order for replenishment is placed, otherwise it is ignored till the next cycle. This method provides a viable process alternative to the continuous review by segmenting the merchandise into review buckets. This makes it easier to manage when the process is manual, or the number of items involved is extremely large, or when constraints on ordering-day exist.

Order Quantity and Order up-to Level

These terms refer to the process that is used to determine how much is ordered when a replenishment order is placed.

In the first process, the “order quantity” is fixed. If the review determines that an order should be placed, then the order for a pre-defined quantity for that item-location combination is placed for replenishment. The order quantity for all replenishment orders is fixed in this method, though order day may vary or may be fixed depending on the review method.

The second process defines a pre-determined “order up-to level” instead. The actual order quantity is determined as the difference between the on-hand stock on the review day, and the pre-determined “order up-to level”. The order quantity in this process will differ from one order to another depending on the on-hand quantity on the day of the review.

Between these two sets of parameters, four basic reordering process options become available.

Options for Re-ordering Process

Based on the above two parameters, the reordering process can be deployed in the four basic ways. The diagrams below depict these variations of the process.

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Inventory Planning

The two key inputs to optimally run the reordering processes above are the inventory safety stock and reorder levels. These parameters control two of the most critical factors in a supply chain, the amount of inventory, and the ability to maintain favorable service levels.

And both of these are defined by the inventory planning process. As the demand and supply patterns change, the optimal inventory levels required to guarantee imagedesirable service levels also change.

Due to inherent variability in the demand and supply streams at any supply chain node, the ability to service demand directly depends on the safety stock. The relationship between the two is exponential that means that a 100% guarantee to fulfill demand will, in theory, require an infinite amount of safety stock to be maintained.

A good inventory planning process helps define these levels, discriminating between products that require higher service levels versus those that don’t. It helps in maintaining user defined service levels that guarantee desirable fill-rates to fulfill the demand. It also reviews them frequently to make changes to the safety stock recommendations to adjust to the new demand/supply picture.

Here is a quick synopsis of the inventory planning or optimization process that determines the optimal inventory levels to meet a desired service level.

Inputs to Inventory Optimization

As shown in the picture, the inventory planning process takes the following inputs.

  • Desired Service Level -- this is normally a user provided input. The desired service level depends on the item in question, its sales attributes, demand, profitability and associative relationship to the other items. Users normally define groups of items that have similar attributes to define and manage the service levels.
  • Demand -- this is the historical and projected demand for the item at the location. Note that the demand at a location like store will be the POS (point of sale) history, while demand at a distribution center is simply the requests that stores placed on the DC. If the store requests on the DC are not available, one could use the outbound shipments as an approximation of such demand.
  • Supply -- this is the historical and projected supply of the item at the location. The supply at a location like store will be the shipments history from DC, and/or vendors; and supply at a distribution center is generally the inbound shipments from vendors.
  • Supply Lead-time -- this is the historical lead-time of the supplies. The lead-time may vary for every PO/transfer order that is fulfilled even for the same item/vendor/distribution center combinations. This time-series data provides the variability of such lead-time and helps the inventory optimization engine to determine the probability that a specific projected supply will be realized on the need date. image
Process of Inventory Optimization

The inventory planning process determines the variability of the historic data to determine the optimal inventory levels. Most algorithms uses statistical methods, and are therefore computationally intensive.

  • The process pre-processes the time-series data for demand, supplies, and supply lead-time to compute the mean and standard deviation of these series.
  • It then computes the optimal inventory levels (safety stocks) that will be enough to guarantee the target service levels.
Outputs of the Inventory Optimization

The process can recommend the following decision parameters that are then the inputs to the reordering process itself.

  • Recommended safety stock levels.
  • Reorder levels,
  • OUTL (order up-to levels), and
  • Order quantities for the fixed order quantity scenarios above.

Saturday, May 3, 2008

Distribution Options for Retailers

When it comes to distribution, Retailers have many options. These are Direct to Store, conventional Warehouse based “stock and distribute”, or Cross-dock (or flow-through) models. Each of these options affects the supply chain efficiencies and costs. In a previous article on cross-docking, we discussed the process, benefits, and some of readiness issues for cross-docking. The current discussion is targeted to review the costs associated with each of the three options, and a decision support methodology to select the optimal model for distribution.

Distribution Models for Retail

Understanding the costs and having processes to measure these costs provides an objective way to evaluate the impact of selecting these options. Most real-life situations will be complex enough to demand simultaneous deployment of all the three options for differing set of products and locations. But the cost analysis still helps to know what these sets should ideally be.

Following cost elements exist at various nodes and the arcs in the diagram.

Cost Elements Relevant to Distribution

The table below shows the cost elements related to each of the above distribution models. Not all elements exist at all the nodes or supply chain arcs. The table shows where these elements exist, and should be considered in costing the above options.

Some of these costs are harder to measure than others, but almost all of them can be objectively estimated for a good comparison among the available options for the selected set of products.

Cost Element

Direct-to-store

Warehouse (stock & distribute)

Cross-dock (flow-through)

Demand Planning

At the store

At the store

At the Warehouse

At the store

Replenishment Planning

At the store

At the store

At the Warehouse

At the store

Demand Consolidation

NA

NA

Aggregate at cross-dock

Ordering

At the store

At the Warehouse

At the cross-dock

Receiving

At the store

At the Warehouse

At the store

At the cross-dock

At the store

Disposition (after receiving)

NA

At the Warehouse

At the cross-dock

Put-away

NA

At the Warehouse

NA

Storage

NA

At the Warehouse

NA

Transfer Orders or Allocations

NA

At the store (pull based)

At the cross-dock for stores

Transfer Order Fulfillment Planning (waves) or Allocations

NA

At the Warehouse (order waves)

At the cross-dock (distribute using original demand, or allocate)

Picking

NA

At the Warehouse

NA

Packing

NA

At the Warehouse

At the cross-dock

Staging

NA

At the Warehouse

At the cross-dock

Shipping

Supplier to Store

Supplier to Warehouse

Warehouse to Store

Supplier to Cross-dock

Cross-dock to Store

Cost of Inventory

NA (common to all)

At the Warehouse

NA (assuming pure cross-dock, no stocking)

While the cost elements provide good data points for decision making, there is more to be considered.

We will look at the impact of these options on the twin supply chain parameters of lead-time and inventory. It is important to understand the interaction of costs with these two core parameters. For example, a shorter lead-time to replenish the store demand helps in better fulfillment decisions and specially helps when the demand is volatile. It also leads to smaller safety stocks at the stores. But it may also require more frequent and smaller shipments that affect the shipping and receiving operational costs.

Finally we will look at the supply chain processes, and how they get affected in each of the options.

Together this methodology provides a thorough decision support mechanism for selecting the optimal distribution models.

Lead-time and Inventory

Lead-time

We will assume that the lead-time in this context is the total time between the creation of demand at the store and its replenishment. From this point of view, the “warehouse” and the “cross-dock” models provide comparable lead-time efficiencies for the store.

However the “warehouse” model provides an inherent advantage. By maintaining the warehouse inventory, it helps in absorbing the variability in the demand and supply processes; and spares the stores from the effects of demand volatility.

The same is not quite true in the “cross-dock” model as there is no inventory to buffer such effects. Cross-docking models can distribute to stores using the original demand make-up, or by looking at the latest demand and re-allocating merchandise as it is received. While the latter provides a little respite by matching the latest demand against the supply, it still cannot address any system-wide demand surge, or drops.

The lead-time in “direct-to-store” delivery models gets adversely affected due to various factors. Among them are the mixed orders that suppliers need to fill to optimize transportation on a single store demand; locations of supplier warehouses; and the shipping lead-times.

Inventory

In each of the flow-paths above, inventories are required to be maintained either at the store, or at the warehouse, or at both the places.

In the “direct-to-store” delivery models, the inventories are required only at the stores. However the longer lead-time in this mode of replenishment requires that higher inventories be maintained at the stores for maintaining the desired service level.

In the “warehouse” model, the inventory is required largely at the warehouse with a small safety stock at the store. Low lead-times and guaranteed service levels (along the supply chain arc from warehouse to the store) almost take out the need to maintain sizable safety stock in the stores. This is especially suitable for items with low or intermittent demand as centralized inventory in the warehouse provides optimal inventory deployment scenario.

In the “cross-dock” model, the inventories are likely to be lowest. There are no inventories at the cross-docking facility; and stores need to maintain just enough till the next delivery from the warehouse. The demand planning ordering cycles can be tuned to optimize the inventory requirements.

Supply Chain Processes

Demand Planning

We will define demand planning in this context as demand forecasting, inventory planning, and replenishment planning to produce the final need quantities.

In a “direct-to-store” model, the demand planning process is relatively straightforward. The historical sales at the stores are the clear demand stream that can be directly used for future projections. Also this is a single echelon supply chain model with no requirements for demand propagation, or time-phased planning.

The “warehouse” model primarily targets the replenishment at the warehouses. To calculate the demand at the warehouse, one can use the historical shipments to stores, transfer order requests from stores, or the actual store sales propagated and time-phased at the warehouse echelon of the supply chain. The last one is the most desirable, but also most expensive to model and compute.

The “cross-dock” model can actually combine the best of both worlds for demand planning. It allows the demand to be planned at the store level, but consolidates this demand at the warehouse level so that consolidated orders to the suppliers can be created. This adds some complexity to the process; and may also require that the original store demand be maintained for final disbursement of merchandise at the flow-through center. Alternately dynamic allocations can be carried out at the time of receipt at the cross-docking facility.

Ordering

The process of ordering itself does not change much in the three scenarios. However the number of orders in the system varies widely. As each order incurs a processing cost, the higher number of orders to be processed can become overwhelming.

In a “direct-to-store” model, the purchase orders are created at the store level. This naturally results in a larger number of the purchase orders to be processed. In addition, the ordering constraints like order minimums can further make the process inefficient as the stores have to wait till they have enough demand to reach the order minimum, or artificially inflate the demand that may result into unwanted inventory. The upside though, is that there are no internal transfer orders to plan and execute as the orders are directly delivered at the store.

The “warehouse” model consolidates the store demand at the warehouse. As each warehouse may be fulfilling demand for several stores, it substantially reduces the number of orders to be managed. However there are internal transfer orders to be fulfilled that add to the costs.

The “cross-dock” model also consolidates the individual store demand to create aggregated orders for the suppliers. However this model requires that either the original store demand is retained for distributing the receipts, or an additional process of allocation is deployed to disburse the merchandise at the flow-through center.

Logistics

There are considerable differences in the logistics processes in all the above scenarios.

The “direct-to-store” model can result in a large number of LTL shipments. As orders are created for direct delivery to stores, the opportunity to consolidate orders to create TL shipments gets reduced pushing up the transportation costs. However there are warehouse tasks of receiving, putting-away and fulfillment that get eliminated in this approach.

In the “warehouse” model, the inbound transportation can be greatly optimized through consolidation of orders, and shipments bound for the warehouse. However the warehouse adds its own layer of activities and costs, before the merchandise reaches its final destination at the store. These activities consist of receiving, disposition, put-away, storage, order-wave, picking, packing, staging, and shipping at the warehouse.

The “cross-dock” model provides the same inbound transportation optimization opportunities as above. However it does add some of the warehouse activities and costs. The flow-through requires the merchandise to be received, sometimes broken-up, staged, re-palletized and shipped. However it does save on put-away, storage, order-wave and picking activities at the warehouse.