Inventory Drivers August 30, 2008
Posted by Lawrence Loucka in : Supply Chain , 1 comment so far 
• Supply Chain Organization: Is there an integrated approach to the supply chain and inventory decisions, or functional silos? The less integrated, the more inventory problems (shortages or overages) are likely to occur.
• Supply Chain Network Design: The greater the number of stocking points, all things being equal, the higher the level of inventory. The longer the supply chain (e.g., goods produced offshore), the higher the level of inventory.
• Customer Service Policies: A company’s strategies and goals related to customer service, both generally and at an A, B, C category level, will greatly impact inventories.
• Safety Stock Policies: Relatedly, how aggressive or not a company wants to be with safety levels, and how frequently a company revisits safety stock assumptions and SKU-level targets, are key variables.
• Degrees of Freedom for Inventory Decisions: The more individuals that have the ability to add inventory into the supply chain, the higher the levels are likely to be.
• Management of Trade-Offs: Company specific decisions about the traditional inventory, transportation, and unit cost trade-offs. The lowest total cost will usually have higher inventories than the lowest inventory cost option.
• Forecast Accuracy: The greater the level of forecast inaccuracy, generally the lower levels of total inventory.
• Demand Variability: Highly dynamic demand in general leads to greater inventory levels to maintain customer service targets.
• Supply Variability: The more variable the supply, the more buffer inventory that needs to be held. Obviously, this is a potential issue with offshoring. In general, variability of supply is worse than a long supply chain in terms of the impact on inventory.
• SKU Counts: The higher the number of SKUs, the higher the level of inventory will generally be for the same dollars in sales.
• Total Cycle Times: The faster the cycle times, the lower levels of inventory required. Procter & Gamble, for instance, is trying to make its factory more flexible, with much quicker set-up times, in part to reduce inventory levels.
• Level of Supply Chain Collaboration: The more integrated a company is with suppliers and customers to jointly manage inventories, the lower inventories are likely to be.
• Vendor Relationships: Companies that have supplier-owned inventory programs, or just-in-time supplier logistics centers, will have lower total inventories on the raw materials/components side.
• Level of Supply Chain Visibility: The better visibility a company has to its network-wide inventory, the lower its total inventory should be. This is part of the promised potential of RFID.
• Inventory Accuracy: The more accurate a company maintains its levels of raw materials and finished goods inventories, the lower the level of inventory, as planners have better trust in the numbers upon which they are planning.
• Order Patterns (Seasonality): Less consistent demand patterns can lead to higher inventory levels. As an extreme example, some wrapping paper manufacturers build inventory all year to ship only in the couple of months before Christmas.
• Metrics: What gets rewarded? Metrics drive behavior, and it is no different with inventory. Have a plant that is driven primarily by yield and cost per unit metrics? Expect more inventory, for example.
* from Supply Chain Digest Letter July 2008
Five Frogs March 5, 2008
Posted by Lawrence Loucka in : Consulting, Reviews, Supply Chain , add a comment
Five Frogs are sitting on a log. Four decide to hop off. How many frogs are left?*
It doesn’t take much for good intentions to end up in disaster. It’s been my recent fate to be involved in two failed mergers, one a postmortem, the next a trainwreck-in-progress. Integrating distribution, logistics, information, management and financial systems; oh, and the people is a tough tough thing. The deal makers fall in love with the potential synergies and then all too often with out a plan or a process hope that magic will happen once the deal is done.
"Five Frogs on a Log: A CEO’s Field Guide to Accelerating the Transition in Mergers, Acquisitions, and Gut Wrenching Change” by Mark Feldman and Michael Spratt is a great guide, and not just for mergers and CEO’s but for any organizational change event and those who are caught up in the maelstrom of clashing cultures. A little light on methodology, this book will let you know what to expect from the merger/acquisition, encourage focusing on execution, the importance of communicating even when in the fog, it’s a virtual project plan for you and your leadership team.
Read it! Hopefully before, not after the chaos starts.
*Five. Because there’s a difference between deciding and doing. "Execution," the authors tell us, "is always more difficult than it seems."
oops! January 2, 2008
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Demand Segmentation November 8, 2007
Posted by Lawrence Loucka in : Definitions, Lean, Lean Sigma, Logistics, Supply Chain , 1 comment so far
Traditional Product Quantity (PQ) or ABC analysis fails to recognize that high volume may not be predictable and that low volume can be. So when trying to determine which products may lend themselves readily to pull techniques we can run into trouble if we don’t understand demand variation. Get some demand data - build a spreadsheet or table listing products in rows and demand in columns, calculate average demand, Cv (the standard deviation divided by demand average), and plot it as here. Here are some considerations:
- Altitude - this analysis typically starts with customer demand but can be done by market, customer, finished goods, in-process, raw materials, suppliers i.e. anywhere along the supply chain where there is consumption.
- Time Bucket - depending on the ‘clock speed’ of the enterprise the demand data can be aggregated by month, week, day, or hour. When gathering data start with the smallest time period possible. It’s easy to convert daily demand to week or month but impossible to take monthly and say anything about daily demand.
- Unit of Measure - the units of volume may be straight forward, for example ‘pieces’ or may be complicated due to different value streams or product lines having a mix of units. You may need to convert your data to a common unit. Dollars can be a common unit.
- Demand - sometimes not easy to get. Shipments may not represent true customer demand, especially if on-time delivery and order fill aren’t very high. Getting original customer demand can be difficult if the customer order entry system forces ship complete or when back orders lose original request dates (and quantities).
- Geography - like altitude, this analysis can be done by production cell, value stream, plant or DC, business unit, or enterprise.
- Horizon - use forecast to determine volume, especially if product life cycles are short. Using history to predict future volume is like driving by looking in the rear view mirror - it can be done, but reaction time is a little slow, and its hard to see the ‘cliff event’ until it’s too late. Sometime forecast is crap or isn’t available, so then use very recent history.
- Timeline - usually want at least 25 data points to calculate a meaningful standard deviation of the demand history.
- Scrub - other than filtering out abnormal orders consider weekend transactions, huge one-time orders, and zeros. Excel and Access treat blanks and zeros differently. As you take the transaction log and build a pivot table of part number vs. date you’ll have cells with no data because no transactions occur on that day for that item. Use search/replace to replace blank with zero. But for new products coming to life during the study period you might leave cells blank prior to the launch date. Similarly if a product has regular demand, say Monday, Wednesday, Friday you might want to leave Tuesday and Thursday blank.
- Plot - volume vs. Cv
- Interpret - Cv’s less than 1.0 lend themselves to flow and pull techniques. Cv’s less than 0.5 can often be handled with rate-based replenishment methods. Remember a Cv of 1.0 means the demand variation is a great as the demand average. Say a part has an average daily demand of 100 with a Cv of 1.0 the demand one day could be zero and the next 200 or more - not very predictable. High Cv items are usually low volume, but not always. Take a look at the three data points in the top center of the graph above. Must be a story here - why are the highest volume parts so unpredictable?
Muda in the Warehouse September 25, 2007
Posted by Lawrence Loucka in : Consulting, Definitions, Lean, Lean Sigma, Logistics, Supply Chain , add a comment
Although created in the manufacturing environment of Toyota by Taiichi Ohno, the Seven Wastes can be found almost everywhere, if you learn how to see them. Here’s some lean thinking for the warehouse:
Overproduction - Think about the consequences when consumers, retailers, wholesalers, distributors, and manufacturers justify "just in case" or Murphy stock as a hedge against unplanned demand. Money, time, people, physical assets, the environment have all been tied up for something that isn’t needed.
Waiting - the ‘hurry up and wait’ of trucks sitting idle or drivers killing time awaiting their turn at the dock, or DC workers or lifts standing by waiting for tools, instructions, materials to arrive or to be taken away. Waiting comes from poor layout, lumpy demand, system batching. Then once the blockage is cleared we hustle.
Defective Product or Service - from picking errors, incorrect order quantities, misplaced stock to shipping on the wrong carrier or the wrong mode these errors consume resources of time, people and materials to no useful end. Worse yet, additional resources, often 2 or 3 times the original, are usually needed to correct the error.
Overprocessing - how about dock audits, redundant approvals, pick/pack/ship audits, cycle counting? Another example of overprocessing the the warehouse is the failure to rationalize the supply base and concentrate relationship management on a few top-tier suppliers. What about rationalizing the carriers? Both result in inefficient duplication of resources, decisions, and communications.
Moving Product - like overproduction, the unnecessary movement of product can occure both within the warehouse and throughout the entire supply chain. Too many steps, too many stops, unnecessary movement from suppliers though master DC’s to regional DC’s for further deployment to customers can be deadly drivers of cost and time, labor, and space.
Moving People - in the warehouse an enormous percentage of people’s time is devoted to movement, such as picking, put-away, and replenishment. If a facility isn’t well laidout with easy access to "A" items an enormous amount of time can be wasted in traveling empty. When good aren’t where they’re supposed to be the movement to the wrong location is both a defect and a waste of human motion.
Ineffective Inventory Control - creates waste a several levels. Excess inventory based on bad inventory data diverts limited capital into creation and maintenance of waste. Excess inventory results in consuming valuable storage space to hold unnecessary goods. A scarcity of items, on the other hand, results in stock outs, expediting, or lost orders.