Monthly Archives: November 2006

10 Things I Learned at INFORMS 2006

I attended as many talks as I could manage in the three and a half days that I spent at the worlds largest Operations Research / Management Science conference (separated by meetings with some local companies), and as a result I learned the following:

  1. Under the right model:
    • centralized models of production, decentralized make-to-stock models of production, and decentralized make-to-stock models of production can all be highly profitable
    • sole sourcing is not always the right option
    • but sometimes sole sourcing is the right option
    • when supply chain participants collaborate and share processes, higher customer satisfaction can result
    • better information leads to lower costs
    • shifting inventory to the right supply chain participant can save everyone money
    • large distribution networks are often bloated and inefficient
    • increased flexibility often leads to increased cost and profit loss
    • lean supply chains can be very profitable
    • but sometimes modular supply chains with more inventory are more profitable
    • a complete characterization of potential supply chain risk is challenging
  2. Abstract, strategic, “big picture” thinkers often solve problems faster and better than concrete, tactical, “current crisis” thinkers.
  3. Decreasing customer returns increases profit.
  4. OEMS can profit greatly from secondary markets and those that try to shut them down might be severely jeopardizing their business.
  5. Good supply chain planning is key to good disaster readiness planning.
  6. 1 in 5 outsourcing relationships are doomed to failure because they favor the client at the expense of the vendor from the outset
  7. Highly skilled individuals prefer solutions with moderate amounts of complexity.
  8. The benefits of centralization realized depend on commitment levels.
  9. If you want to sell your solution, focus on the benefits, not the features.
  10. Manufacturers benefit from innovative customers.

Well, as you probably guessed, I did not actually learn the above, but I did learn that academics now have solid mathematical models that explain why us practitioners have observed each of the above “teachings” offered by various talks that I attended. Don’t worry, I’m not going to bore or confuse you with the models, but simply point out why each of these is true from a “common sense” viewpoint.

    • different production models can be highly profitable
      it really depends on how lean your supply chain is
    • sole sourcing is not always the right option
      it is often a risky proposition
    • sometimes sole sourcing is the right option
      since dual sourcing can often be costly
    • higher customer satisfaction results from collaboration
      do you pick out your wardrobe with your eyes closed?
    • better information needs to lower costs
      better forecasting alone saves you money
    • properly placed inventory saves money
      it costs money to move improperly placed inventory around
    • large distribution networks are often bloated and inefficient
      if JC Penney needs less than 10 DCs in the US, how many do you need
    • increased flexibility often leads to increased costs and profit loss
      the more versions of a product you have, the less likely you are to sell a large quantity of any particular unit, and profits, like economy, come with scale (and each different variation has its own setup and teardown production costs)
    • lean supply chains can be very profitable
      in fact, they can be more profitable than you think
    • sometimes modular supply chains with more inventory are more profitable
      if you have to shut part of your supply chain down waiting on inventory, you’re losing money – the right amount of safety stock at each location can prevent this
    • complete characterization of potential supply chain risk is challenging
      you can never come up with and plan for more than a finite number of possibilities but in real life, an infinite number of things can go wrong
  2. abstract, strategic, “big picture” thinkers are better problem solvers
    a “big picture” thinker is less likely to sacrifice better opportunities tomorrow for good opportunities today
  3. decreasing customer returns increases profit
    customer returns decrease profits, so reducing them increases profit
  4. OEMS can profit greatly from secondary markets
    considering how much today’s high-tech equipment costs, a company is a lot more likely to invest in a solution that has a decent resale value
  5. good supply chain planning is key to good disaster readiness planning
    if you do not know what is critical to your operations, then you do not know what to prepare for
  6. 1 in 5 outsource relationships is doomed to failure from the outset
    considering the less than stellar returns from many outsourcing projects, this should not be a surprise
  7. highly skilled individuals prefer solutions with moderate amounts of complexity
    after all, using a simple solution does nothing to demonstrate your capabilities
  8. benefits of centralization realized depends on commitment levels
    an unsupported initiative never works (and center-led is probably more effective anyway)
  9. focus on the benefits, not the features, in solution selling
    with the exception of those few individuals who have to use the solution significantly in their daily tasks (who are usually not the decision makers), no one really cares how cool it is to use – they care about how effective it is at solving their business problem and saving money
  10. manufacturers benefit from innovative customers
    innovation helps everyone

Are we defined by our markets? – or – Smart Procurement Uses Yahoo!

One of the most interesting sessions I attended at INFORMS was the Online Auctions I session in the Auctions and e-Commerce cluster which consisted of the following talks:

  • How Can You Price a Phrase? Search Engine Auctions as Evolving Practices by Charles W. Smith
  • The Geography of Trade on eBay and MercadoLibre.com by Asis Martinez-Jerez
  • How Much is a Dollar Worth? Tipping versus Equilibrium Coexistence on Competing Online Auction Sites by John Morgan

Each of these talks fundamentally tackled a different aspect of a challenging sociological question whose answer may define us much more than we define it. Do we shape the market or does the market shape us? Although neither of these talks directly answered this question, the insights offered by the speakers are definitely worth due consideration.

In the first talk, Charles told us that real auctions are a discovery process – they define the value of a commodity for which we do not know the true value. This tells us that eBay is not a true auction, since the items traded on it have a well defined value (range). On the other hand, search engine auctions are true auctions since they are defining how much our basic terminology is worth as a means of indexing information. This also tells us that not only is procuring advertising online no easier than procuring advertising offline – but it is fraught with challenge as we have no idea how to accurately price a phrase – whereas a century of advertising has assisted us in pricing a service (if not its return).

This is all based on the theory of markets accepted by the speaker – that markets are definitional practices that generate meanings as interactive and mutual role-taking social practices that evolve over time. Furthermore, their generated meanings are not only subject to external factors, but they affect non market practices and our daily lives. For example, we don’t look something up on the internet, we google it. We don’t auction it on the internet, we eBay it.

In the second talk, Asis explored whether or not the internet has altered the geographies of trade as it crosses international borders and sites like eBay allow you to buy and sell worldwide. After all, with 34B in sales in 2004, eBay can essentially be used as a proxy for eCommerce. What Asis found was that the same location effect is more persistent in online trade than offline trade. Commerce is abnormally high within city and state (provincial) borders and abnormally low across borders. Asis theorizes that trust and cultural factors are the driving reasons, but this is hard to prove from pure numeric data. This tells us that if you’re going to buy something online, you should probably only consider local vendors since the odds are that you are going to end up buying local anyway.

In the third talk, John ran an experiment to determine whether or not eBay and Yahoo are in equilibrium coexistence or if the US auction market is tipping to one side or the other. In the experiment, which used a large number of identical coins offered for sale on both markets using the different types of auctions offered (reserve vs. no reserve, soft vs. hard close, etc.), John determined that revenues on eBay are consistently 20 to 70 percent higher than those on Yahoo and that eBay auctions attract approximately two additional buyers per seller than equivalent Yahoo auctions. This tells us that you should sell on eBay, but buy on Yahoo for smart procurement – and that the market is most likely slowly tipping towards eBay and that, as they have in most of Europe, Yahoo auctions in the US will most likely eventually disappear. (As a contrast point, Yahoo essentially owns Japan, and eBay and Yahoo are essentially equal in popularity in China and other parts of Asia.)

CombineNet IV: BoB’s Unique Talents

Disclaimer: This blog, including this post, is not sponsored by CombineNet. The author is not employed by, contractually engaged with, or affiliated with CombineNet. Any and all opinions expressed herein are solely those of the author. Furthermore, the opinions expressed herein should be contrasted with the opinions of other educated professionals before the reader forms his or her own opinion. Finally, the author is neither endorsing nor dissenting the use of CombineNet’s products or services – merely trying to spread awareness on the importance of optimization and the relative uniqueness of an offering like that of CombineNet. This disclaimer holds true for each post in this multi-part series and will be repeated.

Warning: This is a lengthy post.

In my last post, I outlined in some detail a problem that I felt not only required BoB (Best of Breed) but required CombineNet in particular for an optimal solution. What I did not convey is that not only are there other problems out there that I could have chosen, but there are a significant number of supply-chain related problems that often require BoB.

Today I am going to discuss six problems that generally require a BoB solution. This does not mean that you would necessarily require CombineNet (there are some other optimization vendors that can tackle a few of these), but that you would require a best of breed optimization solution (similar to that offered by CombineNet) to tackle these problems and be assured that the solution you achieved was optimal.

The problems I am going to discuss are:

  1. Distribution Network Design
  2. Large Combinatorial Problems
  3. Large Non-Homogenous Logistics Problems
  4. Non-Traditional Sourcing Problems
  5. Very Large (Traditional) Sourcing Problems
  6. Regret Minimization Problems

Distribution Network Design

Most large retailers or distributors have large distribution networks – often dozens of locations throughout a single country or region. However, this is generally not optimal. For example, in a talk at INFORMS given by a practitioner at APL Logistics, they described how they analyzed the distribution network used by JC Penney that had almost 60 DCS (and cost over 330M / yr to operate) and using in house proprietary meta-heuristic optimization algorithms, they deduced an optimal distribution network that had only 8 DCs, saved over 30M dollars, and, on average, shaved over a day off of standard delivery times! What the presentation did not dwell on (since INFORMS is an OR conference) is that these problems are usually humongous and insanely difficult to model, yet alone solve with your average off the shelf optimization problem (as bad as the multi-level make vs. buy problem discussed in my last post) and without a best of breed solution, your chances of finding the truly optimal solution are often slim.

Large Combinatorial Problems

Large pure combinatorial problems are much, much harder than large pure linear problems (which optimizer’s like iLog’s CPlex can often cut through like a hot knife through butter on today’s high end machines) and significantly harder than general MIP problems. The reason is that these problems contain very large numbers of binary variables, and the best generic domain-independent techniques available are generally no better than greedy branch and bound, and for even a thousand binary variables, that could be 21000, or over a trillion evaluations. An example of a large combinatorial problem is a large marketplace auction where all the participants bid on fixed size lots which are non-decomposable. In other words, CombineNet’s (original) definition of an exchange.

How much better are best of breed solvers on large combinatorial problems? Let’s consider CombineNet’s best of breed solution customized for exchanges. According to CombineNet: “The resulting optimal tree search algorithms are often 10,000 times faster than the state-of-the-art general-purpose MIP solvers on the hard instances of real-world market clearing.” As I have expressed to CombineNet personnel directly, I doubt that this is the average case, but I know beyond a doubt that well defined algorithms can easily shave a factor of 100 or more off of solution time, and that this can be scaled up to almost 1000 on a multi-core machine with a smart parallel implementation. In other words, don’t always expect the best case, but the average case performance of BoB on these problems will demonstrate significant improvements.

Large Non-Homogeneous Logistics Problems

This is similar to a variation of the multi-level make vs. buy problem discussed in the last post. However, in this situation you are trying to optimally bundle your deliveries across product, and sourcing categories and choose the optimal carriers and distribution network independent of your suppliers. Given the non-uniform quotes (weight, volume, LTL, FTL), lot sizes, and various charges and surcharges often imposed by freight carriers, forwarders, loaders, unloaders, warehousers, etc., this problem can become really surly really fast on a large buy. Moreover, unlike the sourcing case where it often makes up a low percentage of your spend and a high order approximation is more than sufficient, when you aggregate your logistics across multiple categories, even a fraction of a percentage point can become significant.

Non-Traditional Sourcing Problems

Most Platform Optimization Engines are optimized for traditional sourcing problems – this means that they are generally not optimized for non-traditional sourcing problems. (Why should they be? Most of the problems you face are traditional everyday sourcing problems.) But every now and again you might have a non-traditional sourcing problem. One example – cell phone plan optimization. Cell phone plans are expertly crafted to be as confusing as possible to make sure the carrier maximizes profit at your expense. If you’re a small company, it probably isn’t worth the hassle trying to figure it out and standardize on a common carrier plan – the costs of manpower and resulting therapy costs will probably outweigh the savings, but if you are a large company, you can save hundreds of thousands of dollars, if not millions, with the right company wide plan (which will probably consist of different sub-plans for different groups and individuals, but all on the same corporate contract). That’s why Soligence has a solution just centered around cell phone plan optimization.

Another example, as conveyed to me by Paul Martyn himself (CombineNet’s Chief Marketing Officer and premiere evangelist on the CombineNotes blog) is energy utilization optimization. If you are a large corporation that produces energy for your production operations and consumes it from the grid, whether you realize it or not, you have a sophisticated form of an energy trading problem. If you can produce enough extra energy to add to the grid, should you, and when? If you have the potential to store energy, then adding energy to the grid at peak hours and only siphoning off extra energy at non-peak hours could slash digits off of your energy bill. Furthermore, shifting your operations so that your maximum energy utilization only occurs at non-peak hours could also save you bags of money. Considering this isn’t a traditional energy trading model, traditional production model, or traditional operations research planning model, its easy to see why you might have to call on BoB.

Very Large (Traditional) Sourcing Problems

POE, especially a well designed and implemented POE that uses real optimization technology as its underpinnings, excels at traditional sourcing problems. It’s what POE was built for. That being said, POE is built on off-the-shelf optimizers, and off-the-shelf optimizers are designed for general purpose needs. That means that they will hit their breaking points before a custom designed best of breed solution, even though they improve every year. For example, leading solvers can easily crunch MIP problems with hundreds of thousands of variables and pure LP problems with millions of variables, but once your MIP problems contain millions of variables and your LP problems tens of millions of variables, you’ll start to notice a performance degradation, which could be rapid and considerable when you get close to the underlying solver’s breaking point. When your encounter the odd problem that is this large, a best of breed solution that also integrates domain intelligence can save you a lot of time and rapidly increase your chance of finding the optimal business solution in the finite timeframe that you have to make a decision.

Regret Minimization Problems

Most of the time you know the problem you need to solve, the associated constraints, and the associated costs. But every now and again you don’t. For example, you need to rationalize your supply base but do not know the optimal number of suppliers. In most products, you have to choose a number or run multiple scenarios with different numbers and then take the best one. Although this approach can be effective, it doesn’t help you understand why a certain solution is best or guide you to the best solution. A best of breed solution that manages the search algorithm can not only guide you to a potentially optimal solution but inform you of nearby solutions that are invalidated by your soft or uncertain constraints. This is very difficult for a platform optimization engine – since it generally cannot guide the search. The best it can do is run different scenario formulations, show you nearby answers, and identify constraint conflict sets. It’s a good approach, but for a strategic problem, the more you know, and the faster you know it, the better you are.

By now, you’re probably asking does BoB have the upper hand? Well, even though BoB can solve a slew of problems that POE cannot and it’s always theoretically possible to tone down a solution, whereas it’s not always theoretically possible to built up a solution, the reality is that, as I’ve said before, when it comes to optimization, one size does not fit all and using a sledgehammer on a finishing nail is not always effective. Furthermore, these are not your everyday problems. It often takes years to realize the savings from distribution network redesign, reverse auctions and sealed bid negotiations are generally not combinatorial exchanges, you do not redesign your transportation network after every sourcing event, most of your sourcing problems are traditional, most of your sourcing problems are of a manageable size with proper strategic sourcing, and if you don’t know what your constraints should be on a regular basis, you have deeper problems you need to solve first. That’s why an upcoming post will focus on POE, the everyday hero, in more detail. When combined with this post, you should have a better understanding of where each technology can be helpful to you.

Disclaimer II: Although this blog, including this post, is not sponsored by CombineNet and the author is not employed by, contractually engaged with, or affiliated with CombineNet, the author is going to report, in full disclosure, that CombineNet did allow the author to use one of their free registrations at INFORMS (of which they were a sponsor), as well as buying the author lunch.

Supply Chain Education is Important

As with any professional field, the appropriate education is often a critical sucess factor. And, as with any professional field that is constantly changing, continual education is often key to continued success. Moreover, although the academics will often tell you this continued education should be delivered by them either through more advanced degrees, specialist degrees, or appropriately designed continuing education courses, the reality is that it is what you learn that is important, not who delivers it. In other words, we are no longer in a world where the medium is the message, we are in a world where the message transcends the medium and we are the message – and the message that we convey is what is important.

This means that professional development courses and certification programs, if appropriately designed and delivered, can be just as effective as academic programs, if not more so – especially if they are tailored to the challenges we address in our daily routines and convey to us the knowledge we need to do our jobs, and do them better.

To this end, I’d like to formally point out that if you are a traditional purchasing manager looking to update your capabilities from those of a twentieth century purchaser to a twenty-first century strategic sourcing professional, you have a professional option through Next Level Purchasing – the first (and only?) organization to offer training, and certification, over the internet at your pace.

Observant readers may remember that I’ve referenced Next Level Purchasing a few times before and wonder why I’m drawing extra attention to them now – and the answer is simple. First of all, until recently, there were very few academic programs with supply chain components, and most of these programs do not have extensive modules on today’s eSourcing enabled strategic sourcing best practices, as most of this technology is quite new. Therefore, this program provides a great way for you to update your skill set very quickly. Secondly, after a great discussion with Charles Dominick, the founder of Next Level Purchasing about current and future course offerings, I’ve decided to review a course or two* to help you understand the benefit of their unique offering and how you can use their offering to jump start your advancement to a Next Level Purchaser.

* I may not get to it until after the Supply Chain Directions Summit hosted by eyefortransport in San Francisco at the end of the month.

Riding the Rails with Coupa

As you may recall, Sourcing Innovation was one of the first blogs to bring you a detailed preview of Coupa, the revolutionary new enterprise open-source e-Procurement application from Silicon Valley. One of the most interesting aspects of this technology is that it is being built on Ruby on Rails (RoR), as discussed by co-founder Dave Stephens in this post on his blog Procurement Central.

This is a bold move considering that RoR is still a relatively new technology that is essentially unproven in the enterprise application market beyond the corporate website, but one that could pay off big time for Coupa when you consider the rapid development time enabled by RoR as compared to other enterprise platforms such as Java and .NET (where WORA* does not apply). Personally, I’m still a big Java fan, but I can see RoR becoming the platform of choice in a couple of years for a number of reasons:

  • faster development time
    following the mantra of “convention over configuration”, RoR sacrifices flexibility for convenience, allowing developers to do more, quicker, and better within the framework provided which makes basic assumptions that significantly decrease the amount of configuration required
  • MVC architecture
    unlike most enterprise frameworks that have preceded it, RoR was built on the MVC architecture from the ground up and has built in object-relational mapping capabilities
  • full stack framework
    whereas some platforms require extensions from multiple vendors, Rails provides all of the components commonly needed by most web-based systems
  • designed for reusability
    RoR adheres to the DRY (Don’t Repeat Yourself) philosophy and its framework was designed to allow every piece of knowledge in the system to be expressed in just one place
  • preconfigured application structure
    RoR automates the creation of project structure and automatically creates all files and components needed by default (no need for a fancy IDE to automate these tasks for you)
  • simplicity
    rails wasn’t designed to do everything, and its focus on the common features used by a majority of programmers a majority of the time removed much of the complexity inherent in many application frameworks; note that this does not limit its capability, as it includes a robust extension mechanism to allow development teams to add (only) the capabilities they need
  • strong community uptake
    a large number of developers, especially in the open source community, are latching onto RoR as their development environment of choice as it overcomes the shortcomings of web scripting languages such as PhP and the impracticality of J2EE for (rapid) web-based development
  • XML compliant
    so if you need to integrate with a non RoR app, no problem!
  • rapidly maturing environment
    just like Java, RoR is rapidly maturing from a neat language for cool web page development to a full fledged enterprise application development platform – I’d say it’s pretty close to Java 1.2 in terms of lifecycle, which is where Java truly became a solid language for application development

In other words, instead of jumping onto someone else’s bandwagon, Coupa has decided to jump into the driver’s seat and lead the charge in the development of eProcurement applications.

And if you want to join the RoR movement early, but don’t know where to begin, consider checking out www.daveastels.com, especially if you are in the NorthEast, for courses, resources, and best practices consulting.

*WORA: Write Once Run Anywhere