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How does your warehouse stack up?

Logistics Management has a new article titled – How does your warehouse stack up? by Maida Napolitano. The survey was conducted jointly by Logistics Management and Gross & Associates, a consulting firm specializing in materials handling and logistics – First Annual Warehousing Trends Survey.

The survey was designed to help today’s warehouse managers get a clearer picture of the challenges they face today and give them an opportunity to see how their warehouse operations compare with the industry average.

The composition of the survey involved:

The results of the Warehouse & DC Trends Study are based on the responses of 485 participants involved in making warehouse-operations decisions at North American companies.

The key findings of the survey are broken down along the following lines:

  • Typical Characteristics
  • Goals
  • Need for speed
  • Operations
  • Finding a solution
  • Technology

Typical Characteristics of an American Warehouse

A typical North American warehouse
is privately owned (77 percent) with either an end consumer (32 percent) or a manufacturer (26 percent) as its primary customer.

  1. is less than 250,000 square feet
  2. receives and ships a wide variety of products, such as electronics, computers and software (25 percent); paper, packaging, and office supplies (24 percent); and chemicals and raw materials (21 percent).
  3. the most common units handled are pallets (87 percent) and cartons (79 percent), with rack storage (86 percent) as the primary storage module, followed by floor storage (62 percent).
  4. Over 90 percent of warehouses still pick orders manually using carts and pallet jacks, while 20 percent have evolved to some form of mechanized picking to a conveyor.
  5. 3 percent of warehouses have fully automated picking requiring no human intervention. The typical warehouse uses some form of warehouse management system (WMS).
  6. Thirty six percent of respondents developed their WMS in-house, 22 percent purchased a stand-alone package, and another 22 percent purchased their WMS as part of an ERP module.
  7. Surprisingly, 23 percent of all warehouses still have no WMS, relying mostly on spreadsheets and order-pick sheets.
  8. 35 percent of respondents have annual budgets of less than $25,000 for continuous improvement programs and 8 percent don’t even have such a budget.
  9. Of the warehouse managers who have a budget of less than $100,000 (59 percent of all respondents), 37 percent said they would spend some of it on materials handling equipment, while 23 percent planned to invest in information management systems.
  10. Warehouse managers with budgets of $1 million or more (7 percent of total respondents) focused more of their spending on IT. Of the respondents in this category, 41 percent reported that they would spend on information management systems, while only 21 percent planned to buy materials handling equipment.

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Its alive, its alive, its alive… (to be read along with suitable music)

SC Digest has an article by Dan Gilmore, editor, on Creating a “Living Supply Chain”, a concept put out by Dr. John Gattorna of the Sydney Business School (Australia) and Cranfield School of Management (UK).
So what is a living supply chain?

In part, because in the end, it isn’t driven by networks and assets and technology, but by people. Somehow, too many of us tend to lose sight of that. “The reality is that it is people who drive the supply chain, both inside and outside your business, not hard assets or technology,” Gattorna writes. “They are in fact living systems, propelled by humans and human behavior.”

Ok. This is also why management is an art and not a science, its why management consultants are paid mega bucks whether or not the strategies that they recommend are finally put into action or fall by the wayside. So what’s new about that?
Most of my recent posts about supply chain collaboration namely, REA, a semantic model for Internet supply chain collaboration and Using Prediction Markets for Collaboration deal with essentially how to structure one’s supply chain around people and ideas around this particular subject.
One of John’s key observations about a dimension of competitive advantage that is begging for exploitation is recounted below,

It is the failure to understand that human element, or indeed the lack any real body of knowledge in this area of supply chain, that is a major force in why some many strategies go unrealized, and many efforts at collaboration produce little value. Harnessing that dimension is the next and only real source of competitive advantage. “If you can understand and correctly apply a more enlightened approach to managing this ‘human factor’ in the supply chain, you’ll discover a primary source of performance improvement. It’s all there for the taking.”

While harnessing the power of people within the supply chain is not the only real source of competitive advantage but it is one of the important sources and should be tapped. Well, then the automatic question is – HOW?

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Cardinal Health Releases RFID Pilot Results

Cardinal Health Releases RFID Pilot Results in a recent news release. They report,

Test data shows promise and gaps of the technology that will affect widespread adoption across pharmaceutical industry

The aims of the RFID pilot program were as follows:

The pilot program tested whether ultra-high frequency (UHF) radio frequency identification (RFID) tags could be applied, encoded and read at normal production speeds during packaging and distribution of pharmaceuticals. Verifying the authenticity of medications along each step of the distribution process adds an additional layer of security to lessen the chance of counterfeit pharmaceuticals entering the supply chain. It is also hoped that RFID data could improve efficiencies in the supply chain.

The results of the pilot program:

Overall data collected by Cardinal Health supports the theory that RFID technology using UHF as a single frequency at the unit, case and pallet levels is feasible for track and trace. However, several challenges remain before it can be adopted industry-wide. Some of those challenges include:

  • Technology and process improvements to achieve:
  • Case-level reads in excess of 99 percent at all case reading stations;
  • Unit-level read rates in excess of 99 percent when reading from tote containers at the distribution center and pharmacy locations;
  • Allowing unit-level “inference” to become acceptable practice in the normal distribution process at stages where unit-level read rates are unreliable, but case level reads approach 100 percent (*Three stages marked in chart above);
  • Barcode technology to be used as complementary and redundant technology to RFID;
  • Management of the cost impact to implement and sustain the technology;
  • Improved collaboration across the industry to identify opportunities to significantly improve efficiency.

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REA, a semantic model for Internet supply chain collaboration

REA (Resource-Event-Agent) is a semantic model for internet based Supply Chain collaboration developed by Dr. William McCarthy of Michigan State University. In this presentation for the ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2000), Dr. McCarthy and Robert Haugen, Logistical Software LLC outline a web-based semantic model for collaboration.
Before I dived into this thing – I asked myself what do these good people mean by using the word semantic in a semantic model for internet based supply chain collaboration? You can look up the definition here

se.man.tic: Spelled Pronunciation[si-man-tik]
– adjective
of, pertaining to, or arising from the different meanings of words or other symbols
Eg: semantic change; semantic confusion.

So in other words, a semantic model is really a language meaning based model. So, what do the authors mean by using the term sematic model?

By “semantic model” we mean a computer software model of real-world supply chain activities. Another term for semantic model from the field of knowledge representation is “ontology”: the set of classes, relationships, and functions in a universe of discourse.

The authors also try to differentiate it from XML in the following way:

We use the term “semantic model” to differentiate from something like XML, the eXtensible Markup Language, which is often touted as the language of the semantic Web. XML is just a format; it has no content. A semantic model describes the content of the semantic Web: that is, what classes of objects, relationships, and functions are involved in supply chain collaboration. The REA semantic model can be expressed in many formats: XML, UML (the Universal Modeling Language), a relational database, and/or an object-oriented programming language. Using XML as the lingua franca, any REA-based system should be able to interoperate with any other REA-based system, because they understand business objects and events in the same way.

The authors also supply an outline of the aims of using the REA semantic model:

  1. supply chain collaboration requires a standard semantic model that all trading partners can use;
  2. to achieve Tim Berners-Lee’s vision (in other words, so that anybody can do business with anybody anywhere), the model must be a generally-recognized, non-proprietary Internet standard;
  3. the model must be broad (covering the whole supply chain) and deep (covering all relevant business activities);
  4. REA is the broadest and deepest currently available semantic model for supply chain collaboration;
  5. and REA is non-proprietary, in the public domain, open for developing into an Internet standard.

So what should the REA semantic model achieve in practical operational terms?

As a semantic Web, REA can link economic events together across different companies, industries, and nations. The links are activity-to-activity or agent-to-agent or person-to-person, not just company-to-company. This means each individual in a REA supply chain can be linked directly to each other individual.

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Oh, the emails you’ll get…

This is one blog post that you’ve got to read… by Joel Spolsky.
Joel writes about an email he recently received,

A management consultant at Bain wrote me a nice email, that included the following sentence:

“Our team is conducting a benchmarking effort to gather an outside-in view on development performance metrics and best practice approaches to issues of process and organization from companies involved in a variety of software development (and systems integration).”

And notes Joel wryly,

I didn’t understand a thing he wrote. The email contained a lot of words (“benchmarking,” “outside in,” “performance metrics,” “best practice,” “process and organization”) each of which set off a loud buzzing alarm-like sound in my head. The noise from the buzzing was so loud and so distracting that I found myself completely unable to parse the email.

And all I can say is : Bwahahahhahah!!
Don’t forget to read the productivity shell game whether it is true or not.

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Using Prediction Markets for Collaboration

Prediction Markets Blog talks about Using Prediction Markets for Collaboration the use of collaborative tools and lists a few applications of such technology.
The post lists three particular directions for collaborative products namely:
New Lines of Communication

Prediction markets have the ability to open up new lines of communication within the organization. In a lot of companies, especially large ones, the executives don’t get to hear what the “normal” employees on the ground are thinking because the two groups are insulated by multiple layers of management hierarchy.

This is precisely what is called “Going to the Gemba” in Lean thinking and that’s really what this sort of collaboration technology opens up. However, there is more than merely creating a common place/market where people can interact but actually going down to the floor and physically interacting with people is the way to go. Perhaps, collaboration takes us part of the way there but I don’t think that it can or should be a substitute for taking the time and effort of going to the gemba.
Collaborative Brainstorming

GE and many other firms utilize markets because they are trying to figure out how to devote their time and resources to the best ideas. By allowing individual traders to create new “stocks” in the market, many more ideas are brought to the table than if the process were to remain centralized.

I think this is a great idea and a space that could use more advertising as well.
Collaboration within the Supply Chain

One of the most compelling aspects of prediction markets is that they don’t have to be limited to just the employees. Since the market itself is web-based, you can cast a wide net of participation that includes vendors, retailers, and others along the supply chain. If you are a manufacturer of DVD players and are interested in forecasting what the consumer demand is going to be in two years, wouldn’t it be wise to allow your wholesale partners to weigh-in with their unique perspective on the situation? What more effective way to coordinate actions like this than with a prediction market?

There has been talk for ages about Supply Chain collaboration but the talk has not been followed by the walk, at least not as much as it should be. But things are changing now, slowly but changing. The arrival of new technology such as the one highlighted above might give it a boost and for good reasons. RFID is also entering this fray in a big way and will provide the data component of what is collaborated upon.

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SCM Newz roundup

EPCglobal initiates RFID container tracking pilot between Hong Kong and Japan reports eLogistics Trendwatch.

GS1 EPCglobal has announced that the Transportation & Logistics (TLS) Industry Action Group has initiated an RFID pilot program to enable visibility of containers transported by sea between Hong Kong and Japan.
The Japanese Ministry of Economics, Trade & Industry (METI) is an active participant in the TLS Action Group, and is providing extensive support for the pilot project. The first phase of the pilot, which is scheduled to be completed in February 2007, will assess the use of both passive and active UHF EPC/RFID tags for cartons and containers shipped by sea between Hong Kong and Japan. Associated data will also be exchanged through EPC Information Services (EPCIS).

And further more a second phase,

A second phase, scheduled for completion in September 2007, will be handled between Shanghai and Los Angeles.

DC Velocity reports on a “new” service from non-asset-based third-party logistics service provider – 4 Way Logistics. The service is new in the sense that these search option are now online rather than on the phone or through a routine (paid) RFP process that one ususally conducts for such services.

A new freight portal takes the tedium out of comparing rates, transit times and service area options for LTL transportation. The 4 Way Logistics Online LTL Marketplace allows clients to find an LTL solution in minutes with just a few clicks of a mouse. 4 Way Logistics is a non-asset-based third-party logistics service provider offering multimodal transportation services across the country and around the world. The company’s new online service takes the time and guesswork out of the LTL search process.

DC Velocity reports on a a new fuel optimization service that integrates with its IntelliRoute mileage and routing system from Rand McNally.

The IntelliRoute Fuel module allows motor carriers and shippers to estimate and plan truck routes based on current fuel prices and locations. The downloadable module provides fuel location pricing information, optimal fuel trip planning, and fuel query services that help fleet owners minimize fuel costs. IntelliRoute Fuel is powered in part by technology from FuelAdvice.com, an online resource for truckload carriers.

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About me

I am Chris Jacob Abraham and I live, work and blog from Newburgh, New York. I work for IBM as a Senior consultant in the Fab PowerOps group that works around the issue of detailed Fab (semiconductor fab) level scheduling on a continual basis. My erstwhile company ILOG was recently acquired by IBM and I've joined the Industry Solutions Group there.

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