Category Archives: Inventory

Organizational Damnation 59: Warehouse Management

This warehouse frightens me.
Has me tied up in knots …
   Dave Matthews Band

And if your warehouse doesn’t frighten you, obviously you haven’t taken a good look at it.

The warehouse is responsible for inventory, and inventory is very costly even when it’s well managed. Some studies of inventory (carrying) costs have estimated inventory costs to be 25% of the value of the average inventory level. Having your inventory cost you up to 25% of its value is a damnation in itself! That’s why many organizations have been migrating to JiT (Just in Time) inventory strategies. But this brings its own problems — and is another source of warehouse damnation (but we’ll get to that).

If an organization aggressively pursues a JiT inventory strategy, even a slight delay can result in a stockout which can result in production line downtime if the product was needed internally or a loss of sales if the product was for sale and needed on the shelf.

Now, besides costing a small fortune, why is the warehouse a damnation?

They control product availability.

If they take their time unloading product, temporarily misplace product, damage product, miscount product, or store it in the least efficient location, the product won’t be available when you need it.

They are the final product quality check.

If they don’t carefully check deliveries for apparent damage, don’t return defective units (and accidentally restock them), and don’t perform any quality checks they are supposed to perform on delivery, defective (or tainted) product can get in the system, get shipped to customers, and give you a black eye.

They control product delivery.

If they take their time loading product, or get behind in orders, customers won’t get their product on time and you will be blamed even if the order arrived on time.

They have a huge impact on inventory cost.

You can move to JiT and optimize inventory levels, but inventory cost is the overhead costs and the depreciation costs, and the overhead costs are the space utilized, the manpower employed, and the operational overhead. If poor planning requires 50% more manpower, on average, than is needed, that bumps up cost. If poor organization means each product retrieval or shipment takes 50% longer than it should (because the warehouse is not lean), that bumps up cost. If poor operational policies or systems means that it is heated 24 hours a day, even though only staffed 10 hours, that bumps up cost. Warehouse controls all of this, not Procurement.

Even a warehouse staff with the best of intentions can cause Procurement the worst of nightmares. It’s yet another organizational damnation that you need to deal with on a daily basis.

Procurement Trend #26: Increased Accuracy in Demand Planning

Twenty-three lacklustre, backwater, trends from yester-year still remain, so let’s get back to it. The sooner we get through these, the sooner we get back to modern times.

So why do so many historians keep pegging increased accuracy as a future trend, and helping poor LOLCat regress to past lives? There are a number of reasons, but among the top three today are:

    • Hyper-competitive markets make demand planning difficult
      because a one week’s difference in release date due to an unexpected delay can result in a competitor beating you to market and siphoning off a significant portion of your expected market share for the product
  • lack of long-term data in short lifecycle product categories makes trending hard
    which makes it even harder to predict not only when a product instance is going to reach end of useful (sales) life but when the next iteration is going to bomb because the product has reached end of life and needs to be retired
  • most tools are still using outdated inventory models
    because the initial versions were created twenty, thirty, and even forty years ago and it’s just not possible to force fit new, complex, innovative inventory costing and projection models into them

So what do you do?

Hyper-Competitive Markets

As per above, Procurement not only needs to identify suppliers who can add value at little or no incremental cost but needs to identify suppliers who can help it get an edge in these markets. It needs to move to JIT (Just in Time) production and distribution to the extent possible, track product and consumer trends carefully, and adapt as needed.

Lack of Long-Term Data in Short Lifecycle Product Categories

It needs to collect as much market data as it can from analyst and trade bureaus to identify global trends, and analyze all of the data it has on past and current products to predict life-cycle trends that are in-line with current market conditions.

Outdated Inventory & Forecasting Models

It needs to update its inventory management and demand planning tools ASAP to not only plan with more data, more resolution, and more options, but support forecasting under different conditions.

Is MRO Inventory Bogging You Down? Maybe You Need a Bit of Xtivity? Part II

Yesterday, we finished Part I by asking What is Xtivity?

Simply put, Xtivity is a solution for your MRO Inventory Optimization Needs and only your MRO Inventory Optimization Needs. If your organization is regularly managing tens of millions of dollars of inventory, or more, you probably know that MRO Inventory is costing you Millions and your current ERP/MRP/CPG Inventory Management systems aren’t helping you curb these costs while making sure that the part is always there when you need it. (Because, in the MRO world, unlike the CPG world or back-office world, availability always trumps cost savings. If you’re a retailer and you are out of stock on 2% of your catalog, no big deal, especially when the average stockout rate is 8%, and if your supply cabinet runs out of toner when the CFO wants to print out 500 pages of financial reports, you can just send a low-wage employee to the local office supply store to pick up a replacement. It’s annoying, but the most it’s going to cost the organization is an hour of someone’s time and maybe a 20% markup on a $50 cartridge. Big whopping deal, NOT! But if it costs 1 Million a day to run the production line and the company’s entire factory workforce sits idle for three days while your repair technician waits for a part to be express shipped to the Brazil factory from a supplier in China, a single stock-out can be the difference between the organization turning a big profit and suffering a big loss for the quarter.)

Accepting this reality and realizing that traditional ERP/MRP/CPG Inventory Management systems weren’t going to solve this problem (which is typically solved by the average company by significantly overstocking a critical replacement part in multiple locations), ten years ago, Xtivity formed to do something about it and nine years ago launched one of the first SaaS solutions to address the issue.

The xIO Software-as-a-Service platform is a 100% web-based MRO Inventory Optimization Solution that can plug into your current inventory management and procurement solutions, suck in your inventory (related) data, pass it through a number of proprietary and statistical models and algorithms, developed by Dr. Stephen Pearce (formerly of Texas A&M and author of Strategic MRO: A Roadmap for Transforming Assets into Competitive Advantage) and refined over the last decade for optimal performance across all of the major MRO industries (including Pharmaceutical, Oil & Gas, Automotive, Power Generation, Pulp & Paper, Automotive, Food Manufacturing, and Transportation), and output, on a monthly basis (or any other regular interval that makes sense from an operational perspective) the optimal order point, order quantity, and average lead time required for each MRO inventory item (by location) — taking the client’s business rules into account. The net result is increased part and material availability and fill rate, accurate lead time calculations, and cash-flow savings from reduced inventory across the board. Based on this information, the xIO solution then generates reports that recommend the suggested changes to future orders and calculates the expected savings both in inventory carrying costs and year-over-year cash outlays for MRO inventory.

But it doesn’t stop there. For each individual item it creates a detailed inventory report that shows the trend over the last 36 months, the projected trend, the expected savings from the initial change to the order frequency, and the expected MRO inventory savings over time. All of the data that go into the summary reports and report by inventory category (defined by inventory velocity) can be drilled into and all of the data (and reports) can be exported to Excel (if desired). And once the suggested changes are accepted, the Xtivity solution can push the new order points, order quantities, and lead times back into your inventory management solution which will take over the ordering, tracking, and classic inventory management functions.

Xtivity, which is well known in the reliability, maintenance improvement, and big MRO space, if not in the broader supply chain management space as a whole, has become so good in its niche that they are at the point where their average client sees a ROI in 90 days or less and 10x ROI over time. Plus, 99.99% of clients can use their solution out of the box. They support so many inventory systems and data formats (in addition to being SAP and Maximo certified) that they only had to do a custom data conversion project for 2 out of the last 1,000 global companies (of a solution that supports, and supports users in, 6 languages) that have tried their platform.

When Xtivity says xIO is a true SaaS solution with no hardware, software, or integration requirements that plugs the MRO optimization hole with virtually no effort (beyond an inventory manager reviewing the order point, order frequency, and lead time recommendations and approving them for push-back into the inventory management system), Xtivity means it. The entire application has been streamlined to not only optimize MRO inventory management and free up as much cash as possible without increasing operational risk, but to minimize the amount of effort required to get results. This is important because you generally don’t generate business value by wasting time on software support, you generate value by implementing and maintaining better (MRO) inventory management policies. And the Xtivity solution allows you to focus on operations, not software, and thus get a quick return. It fills its niche very well. So if you are looking to improve your MRO inventory management, and potentially free up Millions of dollars in cash-flow, check out the Xtivity xIO solution, it’s easy to try and very easy to use.  (For more information on Xtivity, they can be contacted at

Is MRO Inventory Bogging You Down? Maybe You Need a Bit of Xtivity? Part I

Inventory optimization is tough, but maintenance, repair, and operations inventory management is even tougher because the parts just sit there until they are needed — and sometimes, either due to proper maintenance or just good luck, the critical part you are stockpiling for your production line sits on the shelf three times longer than expected while other times the critical part has to be replaced twice as often as the vendor who sold you the machine told you it would have to be.

The last thing you want to do is get the stock levels wrong because inventory is expensive. In addition to the capital that is tied up in the inventory, there are the facility storage costs (which include rent, overhead expenses for services like security, and property taxes) and the possession costs that include, but are not limited to, clerical costs (to track the inventory), insurance (to insure the inventory as a whole), theft (as the insurance policy will have a deductible and a maximum claim), taxes (when the organization takes possession), deterioration (as some inventory will get damaged or spoil), depreciation (as most components decrease in value over time), and obsolescence (if the inventory cannot be used in time). Having inventory sit idle is very costly.

To make matters worse, many of these parts are very expensive and often have no residual value if unused. Whereas unpopular consumer packaged goods can often be sold at fire-sale prices which will allow you to recover some of their cost, this is not always so with MRO. This is because the parts are typically only useable within a particular machine on your production line and by the time you shut it down, chances are that the supplier is no longer selling the machine and most of the suppliers’ other customers are no longer using the machine as well. In addition, many MRO parts and supplies, especially in the chemical, pharmaceutical, and high-tech industries, have specific storage requirements (cool, dry, etc.) and this makes the storage cost even pricier than for regular (consumer) goods.

With typical inventory carrying cost eating up approximately 25% to 40% of a company’s annual inventory investment, the last thing you want is too much inventory, especially since certain MRO categories with special storage requirements and a high risk of obsolescence can have amortized inventory carrying costs that are close to the total value of the inventory! Unless you like having millions tied up in inventory, you need to make sure that you optimize your MRO inventory to the best of your ability. If you can’t do that, don’t rely on creativity — that won’t be enough because just one wrong JIT (Just in Time) decision can bring your entire production line down for days and cost you Millions of dollars. If you don’t have a suitable platform and the expertise in house, don’t rely on creativity. Apply a little Xtivity instead.

Anticipatory Demand Planning is Good, but Anticipatory Shipping?

SI can believe that Amazon patented a Method and System for Anticipatory Package Shipping (US Patent 8615473) but can’t believe it would use this for more than a small number of items. Nor does it believe the system would be implemented as outlined in the patent as filed, at least in the short term.

It took Amazon 7 years to turn its first profit, and while Prime is currently very profitable to Amazon (which makes $78 more in profit per year per Prime customer, on average, than non-prime customer according to CIRP’s market research – Source), those margins would drop substantially if Amazon started shipping tens, or hundreds, of thousands of packages a year that no one wanted. Amazon does have an efficient distribution network and probably has the absolute best deals with postal and courier services that can be papered, but every shipment costs money and every unnecessary shipment eats into profit. Returns cut into profit margins enough, how much are returned shipments to nowhere going to cost?

Thanks to big data, predictive analytics is getting better by the day, but it’s still hit and miss at a granular level. While it’s pretty easy to use correlation data across a large customer base to predict that you are likely to desire an item, it’s harder to predict whether or not you’d actually buy it, and if you would, at what price point, assuming you don’t already own the product in question. (It’s always telling the doctor he wants books and media he already owns.)

As a result, any predictive analytics at the individual consumer level are going to be hit-and-miss at best. Predictive analytics work best across a large consumer base with a lot of data where one can predict that, on average, 5 in 100 people who match a profile will buy the product from Amazon.

And, from Amazon’s viewpoint, the best use of the predictive analytics is on new releases, as the bulk of sales in many of its categories, and books and media in particular, are in the weeks immediately following a new product release. With the right data and the right algorithms, it can not only predict how many units it is likely to sell against its current customer base, but if the demand is enough, how many in each region that is associated with each distribution center and how the orders will likely track over time on a daily basis.

In this, and only this situation, would anticipatory shipping, and in particular, anticipatory packaging, make sense in the short term. For example, if Scott Adams were to release a new Dilbert book and Amazon predicted 200,000 copies would be sold in the first 3 weeks, and expected that it would get 50,000 of those sales, pre-packaging 40,000 for shipment and then distributing those across it’s DCs such that each DC received a number of books proportionate to the expected sales in the serviced area would be a good idea. All Amazon would have to do to speed up shipment would be to slap the delivery address on the boxes as the orders came in and have them ready to go in the next pickup for local delivery.

In the future, once the system is fine-tuned and its delivery partners have the technology to replace a unique delivery address identifier with a specific delivery address on-the-fly, Amazon can pre-ship a set number of these pre-packaged items to the local post office or delivery company every day, which can, in turn, load those packages onto the appropriate courier truck each morning as the addresses in the system are updated with consumer delivery addresses sent over by Amazon upon each purchase.

But not everyone would get faster shipping service. In order to prevent too many unnecessary shipments and loss, Amazon would have to err on the side of caution and pre-package (and pre-ship) less unit of an item than it expected to sell, and restrict the anticipatory shipping and packaging to only those items expected to have a large sales volume. In most cases, the best Amazon will do is optimize the distribution of inventory across its warehouses. However, this can still take a day (or two) off of average delivery time, so this is still a good start.

Any differing opinions?