The Opinion Page
News and comments about the issues facing today's SCM and Inventory Management professionals.
I have been corresponding recently with a colleague who is striving to improve inventory management practices in his business. We had been discussing the importance of inventory record accuracy, which led us to two separate but related issues: stocks-outs and inventory turnover. Here was my friend's question:
So I've been tracking my inventory record accuracy (for the end of month counts and cycle counts) and my suppliers delivery accuracy % with the method you outlined. I was thinking about another one and wondered about your feedback.
I think it would be worthwhile to track "Out of Stocks". For example, I'm out of [Product X] until Friday because I didn't keep enough inventory and my supplier short shipped me. I know I'm out of stock because our Shipping Manager sends a report anytime it happens - but nothing is ever tracked.
Wouldn't it be worthwhile to track, by vendor, the # of times I ran out of stock on a sku every month and possible how long it lasted? If so, what is a common method to track it?
Let me know if you have any ideas. It just got my brain stirring and I think it would fall nicely as a "Customer Service KPI" on my KPI Board.
Here was my initial response:
I have often used % Out-of-Stock as a KPI. Often, you can use this to communicate good news, as well as to identify area(s) that need improvement. (Sales guys are always complaining, "we ain't got nuttin' to sell." Well, if you whack them with a preponderance of evidence over time, they'll stop complaining and start selling.)
I have usually taken the statistic one step further. I categorize the sku's A,B, and C using Pareto analysis. I also filter out any items that are in out-of-season or discontinued that might pollute the findings.
It is usually easy to run a stock status report daily, and pull it into Excel - maybe using vlookup.
Others might criticize this effort, saying that "service level" measurements or other indicators are better...fair comment, I guess, but out-of-stock stats are easy for others to understand. And it is a simple, easy to compute tool.
I like the process of having your shipping manager flag stock-outs when they happen. I am not familiar enough with your processes to properly comment, but when I worked in wholesale, we would run any customer orders through a predisposition file before the orders hit the warehouse floor - if the computer system identified an item as "out-of-stock" the system would pull that line item order aside and hold it in the order bank. The order would never be released to the warehouse until the goods became available. So, the shipping manager would only be identifying errors in inventory record accuracy (i.e. the system thinks you have 10 on hand, but the order pickers could not find the product.) If this is the case with you, then you would need to run the stock status report to capture all of the stock-outs.
I recommend that you publish the stats over time. Publish the stats daily, and you can even graph the results. Once you gather a few months of data, you can reveal some really cool trends.
It is important to go beyond just reporting the stats - I know that you know this - to identify root causes. You could do a little brainstorming with a fishbone diagram to identify what the root causes might be - then tarcj the actual causes. You might be able to show that 90% of your stock-outs are caused by vendor compliance problems, and another 5% are caused by forecast error...bla bla bla...
Hope this helps. Any more questions, give me a shout.
To which my colleague responded:
Looks good. Just to keep it simple (I can look into sorting by ABC etc once I get it all figured out) how do you measure % Out of Stock? For example. Let's say in October I only had 2 things run out of stock. [Product X] and [Product Y]. Out of the 40 items I order from that supplier, those 2 items were out of stock for 2 days once during the month.
How do I measure that? Is that the right example?
To which I responded:
My view is that your total potential stock outs for a month is 40 items x (31 days minus 5 Saturdays minus 5 Sundays = 21 "working days") = 840. In other words, there are 840 potential working item-day combination where you could suffer a stock out in that month.
Your daily % in stock for October 1 is (40-2)/40 = 95%
You were stocked out for 2 days, so:
Your daily % in stock for October 2 is (40-2)/40 = 95%
Your month-to-date % in stock as at October 2 = (38+38)/(40+40) = 95%
Assuming that you were back in stock on October 3 (obviously, your daily % in stock = 100%),
Your month-to-date % in stock as at October 3 = (38+38+40)/(40+40+40) = 96.7%
Your month-to-date % in stock as at October 4 = (38+38+40+40)/(40+40+40+40) = 97.5%
and so on. At the end of the month,
Your month-to-date % in stock as at October 31 = (838)/(840) = 99.8%
As I mentioned, someone with a PhD in Statistics will poke holes in this approach as it fails to account for other issues such as sales missed, ability to recoup lost sales, service levels, and so forth. If, for example, you were running a very important and time-sensitive promotion on October 1st and you stocked out at that time, you should punch yourself in the face for making the mistake. The approach that I have shown is simple, but I think it is effective. Using this method, you can approach your boss with hand-on-heart and say, "Yes, our % in stock in October was not perfect, but it was pretty damn good - "world class," in fact - and when a mistake was made we identified it, found out what caused it, and recovered fast."
One last hint - I like using "% in stock" rather than "% out-of-stock" as it tends to impart a more positive perspective on things.
And I was pleased when my colleague responded:
Ok - let me work on this for a bit and stew over it. I think I'll get back to you but it makes PERFECT sense. BTW - our shipping supervisor does this report based on what his people tell him. "Were out of this!". That's how I'll know. We can often get something down from our warehouse to fix it. So I need to setup something in Excel and track it daily by the sounds of it because I can't assume I'll be out of stock until the vendor arrives.
Making KPI's too technical and running your business solely off "the numbers" is a poor mistake to make. "Profit is the inevitable conclusion of work well done", as Mr. Ford said - not metrics well done!
I love this one. It's easy to understand and easy to improve on. I'll get back to you in a bit after I try getting it setup!
Our conversation later led to the topic of computing inventory turnover. More on that later.
Recently on Linkedin, the following question was asked:
Team, any suggestions on how to error proof the pick / ship process manually or with RF. To ensure the customers always gets what he has ordered.
This was my response this morning, for your interest and amusement:
An appropriate answer depends very much upon the nature of the product(s) being distributed, as well as outbound shipment volumes and frequency. This submission will talk about a process that has a heavy manual component.
I agree that verification of outbound shipments is a very important step.
I used to manage (as Operations Manager) a small (40,000 sq foot) warehouse that stored and distributed finished goods of very high per unit value. The goods were fragile as well. We had a high sku-count (about 7,500 sku's), large customer data base, and our WMS was a combination of manual pick/pack/ship with a bespoke computerized customer service system that generated the picking documents. It was very "1980's", but we succeeded in achieving over 99.5% inventory record accuracy, high labour productivity, and virtually no customer complaints regarding mis-shipped sku's.
One of my warehouse manager's key responsibilities was performing a visual verification of case contents before the cases were sealed and manifested for shipping. Two of our best full-time staff assisted him in this process, when required. He was on the floor a lot (over 75% of his day, typically - no hiding in his office) and he was obsessed with accuracy.
But, inspection does not ensure Total Quality, and Dr. Deming's Point #3 of his Fourteen Points is "Cease Dependence on Mass Inspection." I agree with Dr. Deming wholeheartedly, and even he granted that some exceptions do exist to this rule. In the spirit of Point #3 we succeeded in building quality of processes upsteam. If we had failed to do this, my warehouse manager would have been overwhelmed with mistakes at the verification stage.
I believe that it is important to have a clear and unambiguous product numbering hierarchy. We dealt with all manner of colours, shapes, and sizes. The product's UPC code, or other numerical identifiers, had to describe the item precisely. It was not good enough to describe a product as being "blue". Was it "sky blue" or "turquoise" or "teal" or "royal blue" or "midnight blue"? We had a code for each. Everyone from customer service to order entry to warehouse operative had to understand the importance of the product codes.
Our order entry staff were well-trained, so that errors at this stage were minimal. If an error did occur, we could easily trace it back to the order-entry operative and take corrective action in that area (was it human error? Did the customer make a mistake? Is some re-training required?).
Warehouse picking staff were well-trained and cross-trained in other areas (e.g. packing and shipping). We favoured full-time employees, and literacy (read, write, speak) in English was a prerequisite. We found it difficult to train part-time and temporary employees to a sufficiently high state of knowledge to ensure quality. If any ambiguity existed, the order pickers were unafraid to ask questions.
While we did not embrace a formal cycle counting routine in our warehouse (I very much recommend it, though) we did use some of the corrective actions suggested by cycle counting. We investigated, for example, any instance where a customer order had passed through the order entry predisposition stage onto the warehouse floor, but the picker could not locate any stock. This would trigger a root cause investigation.
So, I suggest that verification in combination with sound upstream processes will lead to success in shipping accuracy.
The New York Times reported this week that NY Attorney General Andrew Cuomo sued Ernst and Young on Tuesday, accusing the accounting firm of helping its client, Lehman Brothers, to "engage in a massive accounting fraud" by misleading investors regarding the financial health of the investment bank.
It seems that Ernst and Young approved a controversial accounting maneuver known inside Lehman Bros. as "Repo 105", which involved the "surreptitious removal of tens of billions of dollars of securities [debt] from Lehman's balance sheet to create a false impression of Lehman's liquidity, thereby defauding the investing public". The NY Times reported that this tactic temporarily removed as much as $50 billion from Lehman's balance sheet to give the appearance that Lehman had reduced its debt levels.
Cuomo referred to the practice as a "House of Cards business model, designed to hide billions in liabilities before Lehman collapsed." The shock waves were felt with great pain around the world.
The "repo" transactions, variations of which are employed ubiquitously on Wall Street, occur when an investment bank raises cash by selling assets, then buying them back a few days later. These transactions would typically occur just before the close of the books at the end of financial quarters.
Ernst and Young argue, of course, that such transactions are allowed under GAAP (Generally Accepted Accounting Principles). I am not an Accountant, and as such cannot express an opinion one way or the other. But this certainly fails to pass my ethical "sniff test": is management interfering in the normal patterns of business in an extraordinary way in an attempt to distort reality and otherwise mislead stakeholders?
There is an analagous practice which occurs frequently in the Canadian retail, wholesale, and manufacturing supply chains. From the point of views of the industrial customer, this is called "forward buying." It works something like this:
As a manufacturer or wholesaler approaches its fiscal period end (month, quarter, or year), management realizes that it is about to fall short of its sales targets. It creates incentives for its customers to buy product in quantities that the customer would not normally need. These incentives are frequently expressed as reduced cost prices or discounts from contracted prices, if the customer will buy quantities prescribed by the seller. The customer, let's assume that in this case it is a retailer, performs a quick analysis of the "deal" (comparing the reduced prices to the related inventory carrying costs, for example) and arrives at a decision to buy or not buy the incremental quantities.
Incentives need not necessarily come in the form of reduced prices. Occasionally, they can come in the form of an "exchange of favours" by individuals in senior management, extended payment terms, and a variety of other arrangements.
As a professional inventory manager, I have always argued strenuously against this technique. Not only does it open the seller/customer relationship to unethical practices, but the true costs of such transactions are frequently overlooked. From the seller's perspective, I call it "mortgaging the future" to relieve current pain.
It often takes a long time for conditions to develop which lead to offering such deals, but once the firm is on the merry-go-round it is very difficult to get off. It is like a heroine addict who receives great pleasure and results from the first hit, then spends a lifetime trying to replicate that first feeling.
Pretend that Wholesaler ABC has enjoyed 50 years of relatively stable growth, with sales averaging +5% growth annually. Senior management at ABC sign on to a +5% budgeted sales increase for 2010. Shipments in 2009 were 100,000 cases of widgets. ABC must therefore ship 105,000 cases in 2010 to meet their sales target. The average price of a case is $1,000, so annual sales in 2009 were about $100,000,000.
Significant unexpected changes happen in the marketplace in 2010. Such changes might include the entry of new competitors, a softening of the macroeconomy, a change in consumer tastes, or government legislation. Whatever the negative issue, sales for ABC start to trend downward, at a rate of 95% of the prior year's volume. Management at ABC either ignore the slide, or dismiss it as a temporary "blip", or are completely unaware of it due to flaws in their sales analysis system.
On Dec. 1, 2010, the sales trends hit management at ABC like a shovel in the face. Not only are sales down relative to last year, they will never make budget! In fact, the gap between actual and budgeted sales looks like it will be 10%! (5% vs.LY + 5% growth). After 11 months, they realize that their shipments will be about 95,000 cases, versus a target of 105,000 cases and the shortfall is therefore about 10,000 cases ($10,000,000).
Management panics. It's "Let's Make a Deal" time at ABC. They approach their top two customers, Customer 123 and Customer 456. If each of these two customers buy an extra 6,250 cases, to be shipped before December 31, 2010, ABC will extend a 20% cost discount on the incremental purchase. (6,250 x 2 x $800 per case = $10,000,000 = sales shortfall).
On Dec. 15, 2010, both 123 and 456 agree. The incremental purchases represent about 3 months' worth of stock at each of Customer 123 and Customer 456. Ultimately, ABC achieves their 2010 sales target.
What are the costs of this deal to ABC?
One might answer, correctly, that ABC has lost potential gross margin dollars of 12,500 x $200 / case = $2,500,000. Incidentally, ABC had to ship 12,500 cases, and not just the "gap" of 10,000 cases, because the selling price has been reduced to $800 per case rather than the contracted $1,000 per case. So, 12,500 x $800 is enough extra volume to make up the shortfall in dollars.
But, there are other costs to ABC. Since they are shipping an extra 12,500 cases, which is about 4 weeks of normal stock, in the last two weeks of December, they are cramming 6 weeks of work into 2 weeks. This means extreme pressure on operations.
- overtime might have to be paid to warehouse workers
- inbound product (e.g. subcomponents or raw materials) might have to be expedited. ABC have to incur air freight and premium routing costs in order to ensure backorders are not accumulated?.
- standard manufacturing or assembly maintenance procedures might be foregone, as lines are dedicated to increased production or assembly.
- standard Health & Safety considerations might be overlooked in the month-end rush. Might there be a higher risk of accident, injury or burn-out?
- this is Christmas Break time, and the extra work could effect employee morale.
- integrity of inventory record accuracy and inventory control measures might be compromised in the rush to finish paperwork.
At the end of the day, is ABC any farther ahead? In many cases, the answer to this is "no." Their Big Customers, 123 and 456, have simply "bought forward" 3 months' of supply. They now have surplus. They will simply shut down their purchasing for 3 months, until the surplus is reduced to normal levels. At the end of the First Quarter, therefore, Supplier ABC is in even worse shape than they were in December! The gap between actual sales and budgeted sales widens further.
Besides, ABC has now misled their investors, by overstating their sales potential, and the financial health of their company.
Unless ABC is willing to tackle the underlying causes of the 2010 sales erosion (competition, style, or legislation) ABC's financial condition will continue to worsen.
Customers become perturbed as well! Customers 123 and 456 now have surplus. Their careful management of inventories for the past 11 months has now been eradicated. Their warehouses are strained to find homes for the extra inventory. They are exposed to shelf-life issues, increased risk if shrink, and increased risk already associated with forecast accuracy.
I have see situations where Customers 123 and 456 end up returning the surplus stock! What a disaster for everyone!
There are too many reasons not to jump on merry-go-rounds of this nature. Do the right thing: address the underlying problems and take your lumps when you have to do so. But do not matrgage the future with schemes such as these.
I am taking a little break from my theme about "Deming's 14 Points" to direct your attention to a fascinating little article in the Monday, July 19, 2010 edition of The Globe and Mail. Here is the link:
Auren Hoffman's (via Harvey Schachter) brief submission is particularly relevant to the Inventory Manager. He argues that in many facets of a growing business, there is a time when one must kill things off that are no longer helpful.
Accumulation of discontinued, out-of-season, out-of-fashion, and otherwise obsolete inventory is frequently one of the most pressing inventory problems faced by retailers, wholesalers and manufacturers today. And it has been that way for a long time. Sometimes it exists, lurking in the weeds, unidentified by the business for years. Sometimes it stares us in the face on a daily basis - we trip over it when we visit the warehouse, and it is on all of our slow-moving inventory reports. Sometimes the CFO says that it is too expensive to write down, or write off. And sometimes we simply fall in love with our product, and enter a period of denial while sales drop off and the goods are simply not as glamorous, attractive, and sexy as they used to be. Divorce, frequently, is a fact of life.
It is my observation that companies need to be far more brutal about killing off unproductive sku's than they have been over the past 30 or more years.
Products that are at risk of becoming out-of-season require special treatment. The project of managing seasonal product inventories is a little too complex to address in this blog. But it is possible with today's POS technology, some diligence, budgeting for reality, and some planning. The simple fact, and prime motivator is that one day after the seasonal event (for example, Valentine's Day, Christmas, Easter, or Halloween) seasonal products are worth a lot less than they were 24 hours before. Valentine-related products are worth a minimum of 50% less on February 15th than they were on February 13th. The trick is to follow each sku's sales (or depletions) closely relative to your pre-season sales profile, and take pricing or transfer action before it is too late. Re-project, re-project, and re-project, daily if you have to do so. Identify and kill off the non-producers - sell them before the end of the season, and do not relist them next year (or purchase more conservative quantities).
Non-seasonal products have a life cycle as well. The trick here is to avoid making that "one last big purchase" in anticipation of sales that will never transpire. Take the care to know where you are on each product's life cycle profile, and take clearance action when it won't break the bank. A 25% markdown taken now might clear up potential problems, that would cost a 75% markdown six months from now.
Above all, the Inventory Manager needs to be objective and cool-headed. Every Marketing Manager in the world will try to tell you that every product he has ever introduced has been a smash success. Marketeers are lovely people, but if you listen to them too frequently, you will soon be swamped with sku's, awash with inventory, and stumbling over dusty "product enhancement" materials (such as wrapping paper, bows, baskets, and signage) that have grown to take over your warehouse. On new assignments, I have walked into some of the biggest inventory messes known to mankind - and frequently I was there because the warehouse was bursting at the seams with old marketing collateral and obsolete items that Marketeers thought would sell to some idiot some day. That "some day" never came. Cull the herd of skus before they breed themsleves into an uncontrollable mess. Be vigilant. Kill the old geezers now.
Hoffman goes on to highlight problems with meetings, reports, processes, and people. We've all been in meetings where we wonder "why am I here?" and the only answer is "because we've always held this meeting." Kill it. Kill the reports that no one reads. Kill the processes that are no longer value-added. And, sadly, review the people who are not making a contribution. First, discover whether barriers are preventing performance. But Reed Hastings of Netflix is quoted as saying "Adequate performance deserves a nice severance package."
Dr. Deming's Point #4 was "End the practice of awarding business on price tag alone."
In her thought-provoking editorial titled "One Single Point of Failure" (Purchasing b2b Magazine, May 2010), Deborah Aarts discusses the April 2010 eruption of volcano Eyjafjallajokull in Iceland, and the impact suffered by supply chains worldwide caused by the subsequent ash and dust clouds. This natural disaster "caused chaos in supply chains the world over. As air traffic to and from northern Europe ceased, many companies sourcing from the region scrambled to make alternate arrangements." She cites the example of Nissan, who sources pneumatic tire pressure sensors out of Ireland that are sent to plants around the world by air in a JIT environment: "When the airspace closed, planes could no longer service the Irish plant, and Nissan's quick supply of the sensors was cut off. The company was reportedly forced to temporarily suspend production at its plants in Fukuoka and Kanagawa, Japan." BMW operations in South Carolina were similarly disrupted as it could no longer obtain seat covers from South Africa.
Ms. Aarts (along with risk advisor Marsh Inc. in a follow-up contribution within that same magazine) search for solutions. The key, it is argued, is to analyze the supply chain of each item and look for single points of failure: those critical items and points of contact that, if disrupted, would cause serious problems downstream. But what specific evasive action could be forward-planned? Searching for alternative suppliers is a possibility, but having an alternate local supplier sit idle in anticipation of a similar disaster could be impractical and cost-prohibitive. Carrying some protective safety stock might be a prudent plan: I discussed this option with a colleague of mine in the health care industry at a recent APICS Professional Development Meeting - in an industry that makes life-or-death decisions on a daily basis, they have concluded that a 4-week safety stock is affordable and comfortable. While I have never personally embraced an arbitrary "weeks coverage" objective (as it flies in the face of the spirit of continuous improvement) I had difficulty arguing with my colleague. Lives are at stake. I decided to take a "Total Cost" view which worked to support his conclusion. Whatever the optimal solution, it is important to identify those single points of contact that present the greatest risk.
How is all this relevant to Dr. Deming's Point #4? Well, Deming argues that the practice of awarding business based on price tag alone, which was, and continues to be ubiquitous in American business and public service procurement policies, leads to a proliferation of suppliers. Moreover, if the purchasing agent plays one supplier against another, he or she may succeed in driving the rice to a point where the suppliers having difficulty staying alive!
It is critically important for companies' procurement policies to put quality first. Sourcing from a multitude of suppliers will make evaluation of quality of inbound materials virtually impossible. Too much variation lot-to-lot and within lots will necessarily occur, and variation impairs quality. Jumping from vendor to vendor will further produce reliance upon specifications, the practice of which impairs pursuit of the quality initiative and continuous improvement.
Deming strongly advocates building long term relationships built on trust with single suppliers. There are enormous advantages. Long term quality initiatives can be cemented. The supplier is more likely to assume the risk of innovation and the cost of modification of production processes that benefit the customer. Administrative processes and transactions between the two partners are likely to be streamlined. Engineering, supply chain, and marketing departments, among others, in both companies should work together to build quality and reduce costs. He argues that robust quality arrangements cannot be adequately arranged across a multitude of suppliers.
Dr. Deming further questions the worth of contracts, especially short term (annual) ones. A supplier who enters in to a series of short term contracts cannot, typically, afford to tailor the product to the needs of the buyer.
Does Dr. Deming's advocacy of single source long-term relationships conflict with the "Single Point of Failure" analysis as discussed by Ms. Aarts? I do not think so. Dr. Deming was enough of a realist to understand that catastrophes such as fires, strikes, and yes, even volcanoes happen, sometimes with devastating consequences. The outcomes are magnified in a JIT environment. Alternatives need to be planned, with intelligence.
The point is that the myopic view of awarding business based on price tag alone is a quality catastrophe waiting to happen. Take the Quality and Total Cost view. "Defects beget defects. Good quality begets good quality."
Many operations management practitioners are familiar with the concept of cycle counting. It is an important procedure in the OM practitioner's tool box to help improve inventory record accuracy.
To avoid any ambiguity, the APICS Dictionary defines Cycle Counting as follows:
"An inventory accuracy audit technique where inventory is counted on a cyclic schedule rather than once per year. A cycle inventory count is usually taken on a regular, defined basis (often more frequently for high-value or fast=moving items, and less frquently for low-value or slow-moving items). Most effective cycle counting systems require the counting of a certian number of items every workday with each item counted on a prescribed frequency. The key purpose of cycle counting is to identify items in error, thus triggering research, identification, and elimination of the cause of error."
It is the last sentence where many firms fail to properly execute the spirit of cycle counting. More on this later.
The importance of inventory record accuracy ought to be self-evident. Without accurate inventory records, customer service and sales lose visibility of what is available for sale. Inventory Managers will order either insufficient stock, or will unknowingly order surplus. Confidence interally and exterally becomes shaken. Customers become disappointed. Finance gets angry. Warehouse personnel get frustrated. The list goes on.
A mentor of mine years ago, for whom I have great respect, used to express her fear that the more one counted an item, the worse inventory record accuracy became. There is more than a grain of truth to that assertion.
Cycle counting must respect similar cut-off rules as are observed in an annual physical inventory that has been well done. Pending inbound shipments need to be identified and accounted for in the counts, Pending outgoing customer orders need to be identified and accounted for in the count. Stock needs to be located properly in the warehouse. And samples need to have been listed and included in any counts, if they are saleable inventory. Broken and otherwise unusable inventory needs to be written off and excluded from the count.
Adjustment of the inventory record to the physical count needs to be done. But too many firms stop there. It is critical, as per the last sentence in the definition above, that the cycle count team investigate and identify the root cause of the error, and ensure that it does not happen again,. This might mean adjusting internal business processes or make demands of external partners that would require the assistance of Senior Management. But until the root cause is addressed, the problem will continue to pose problems.
What other issues might cause a cycle count program to fail? A few land mines to avoid:
- inexperienced staff, who are not familiar with the product(s) have difficulty counting properly
- failure to devote sufficient resource to the program
- kicking off the program during a period of peak activity (sales, outbound or inbound shipments).
- poor stock locator systems
- a messy warehouse
- failure to promptly write off and dispose of unsaleable inventory- staff who have been insulated from business processes outside of the warehouse's four walls. Staff need to appreciate the impact of poor inventory record accuracy and need to have some basic understanding of business processes outside of the warehouse.
- lack of support and follow-up by senior management.
It can be done!
Contribution Analysis (reference my most recent two postings below) can also be used effectively in Quality Assurance, including Vendor Quality Certification initiatives.
Let's say that your firm's QA (and Operations) team has determined that one of the major reasons for suboptimal customer service levels and stock-outs is unpredictable fluctuations in lead time. "Lead time", in this example, is defined as the length of time it takes to fill your stock from the moment you initiate a requisition. This allowance includes the time it takes to prepare the Purchase Order through to physical receipt of goods in your warehouse, and placing (posting) goods into available inventory. Naturally, if you place a PO with a supplier, the quantity in part is determined by the amount that you expect to sell within the lead time. If goods arrive three weeks late, and you do not have enough safety stock to compensate, you will likely run out of stock.
Now, your QA/Operations team might have come to this conclusion by using a variety of tools, such as the "Fishbone" (or Ishikawa) diagram, or even Pareto Analysis. But now we want to dig deeper into the problem of lead time variability.
Take a statistically significant sampling of inbound shipments that are arriving "late" (that is, beyond lead times that have been negotiated in procurement contracts). Determine what issue, or combination of issues, have led to the shipment arriving late. Such issues might include:
- supplier/vendor out of stock
- equipment breakdown in supplier's manufacturing process
- shipments delayed at point of consolidation at port of exit (for overseas suppliers)
- unreliable trucking company
- goods stuck in customs due to paperwork problems
- delays in rail yards
- and so on
Count the frequency of each issue within the sampling.
Rank the issues top-to-bottom.
Apply Pareto's Law and assign A, B, and C classifications.
This will allow your QA team to focus upon those few issues that are contributing the most to your lead time variability problem (80%), and fix them first. This is the low-hanging fruit
It can be done!
In my last posting, I wrote about Pareto's Law and ABC Analysis (also called "Contribution Analysis".) Once the Inventory Manager understands the ABC's of his or her product portfolio, there are many practical applications.
One such practical application is with regard to Service Levels. Service Levels can be defined in myriad ways, but one of the most common is fill rate vis-a-vis customer orders. Another is a simple % in-stock calculation. In its simplest form, if customers, for example, order 100 widgets, and we are able to fulfill quantity 98 on time, our fill rate is said to be 98%. Now, there are a number of variants to this simple example that are designed to make the service level statistic more meaningful, but for the sake of illustration I have chosen the simplest example that I could conjour up.
Much to the chagrin of the Marketing and Sales Departments, it is statistically impossible to reach and maintain 100% service levels. The graphical relationship between service levels (on the horizontal axis) and inventory investment (on the vertical axis) is hyperbolic. It shows that as the firm approaches 100% service levels, the inventory investment required to achieve an extra 1% in service levels increases exponentially. The curve never reaches 100%. So, the firm that is obsessed with chasing the 100% service level Pot of Gold at the end of the rainbow can ruin its cash flow through over-investment in inventory.
The idea behind ABC (Contribution) Analysis is to stratify service level goals by contribution code. Typically, the goal structure looks something like this:
"A" items =>Service Level Goal = 98%
"B" items => Service Level Goal = 95%
"C" items => Service Level Goal = 90%
This says, in essence, that the firm is willing to live with a 90% fill rate on "C" items as they are of little relative importance to the business as a whole. The firm will strive for high service levels for "A" items, due to thier importance to the business.
Firms employing this recognize the very real tradeoff that exists between financial needs and sales or customer service needs. It makes no sense to increase inventory investment by 50% in order to realize a 4% increase in sales. And believe me, I have sat in my fair share of Senior Management meetings where this arguement was made repeatedly. As the guardian of the inventory asset, the Inventory Manager cannot allow himself or herself to get talked in to this high-risk approach.
Firms ought to do some benchmarking, to try to determine what the competition is able to do. If best practice in the industry is that "A" items typically see a 99% service level, then you must judge whether or not that is achievable given current pricing structures and profitability scenarios. On the other hand, if you can achieve 98% due to superior inventory management expertise when the competition achieves 95%, and you can still beat or meet the competition on price, you have achieved a significant competitive advantage.
Moreover, the spirit of continous imprvement is that you can, and should improve service levels overall incrementally. But be careful not to blow your brains out in the process.
It can be done!
I cannot imagine a planner who manages tangible inventory who does not invoke Pareto's Law as a central tool in his or her analysis. Sadly, I know it happens.
Most will be familiar with Pareto's Law, which has also been known as the 80/20 Rule. It involves ranking the items within a product portfolio based on sales, value, or dollar value of usage. It is also used frequently in Quality Control to determine those issues that are most problematic. Once the ranking has been completed, a percent contribution is computed for each sku within the portfolio. Then, a "contribution code" such as A,B,C is assigned to each item. A items are those roughly 20% of items that contribute roughly 80% to overall sales, while B items are those 30% of items that contribute 15% to sales, then C items are, as Dr. Juran would say, "the trivial many"...50% of the items that contribute only 5% to sales.
The objective is to manage the A items with much more care and attention than the C items. In many cases, the inventory status of A items are reviewed daily or at a minimum weekly. Service level targets for A items are set much higher than C items. A items are cycle-counted in the warehouse more frequently than C items, to attain a very high level of inventory record accuracy. A items turn faster than C items. Expediting A items tends to be worth the effort.
I have worked for firms that insist on treating all items in a large product portfolio with equal reverance. The result was that, given limited time and resource, attention to the A items, the most important items, became diluted, and the lowly C item that contributes 0.1% to annual sales got far more attention than it deserved.
So, let's incorporate Pareto's Law into every planner's tool kit. Use it, and work it.
(A little trivia....Vilfredo Pareto (1848-1923) actually received more credit than he deserved for Pareto's Law. It was really quality pioneer Dr. Joseph M. Juran who coined the term "Pareto's Principle", probably because it sounded better than "Juran's Principle"! While Paerto planted the seed, Juran popularized the notion!)
No matter what technique, or combination of techniques are used by the firm to forecast demand, it is of critical importance that future marketing plans be incorporated into the forecast.
Most retailers, many wholesalers, and some manufactures promote certain sku's and in doing so spin demand away from past trends and absolute values. History is the planner's best friend. When the value of historical data is reduced, the planner is faced with a difficult challenge.
It is necessary that a formal process, such as Sales and Operations Planning (S&OP) be established to allow marketeers to articulate their expectations of demand. This demand forecast becomes a shared responsibility, as the planner will execute procurement decisions based on these promotional sales forecasts.
Further, it is necessary that the forecasts be "rolled up" and a sanity check versus budget be performed.
It can be done!
John Skelton is the Principal Consultant and founder of Strategic Inventory Management.