A recent article in Strategy+Business on Cut Costs, Grow Stronger had the following graph which I think is just great:
Any guesses as to what most of the companies on the line (and, specifically, those closer to the upper right of the line) have in common? Anyone?
These companies were all early adopters of strategic sourcing decision optimization. Think about it.
This series discusses the recent report from CAPS Research on “the role of optimization in strategic sourcing”. The primary goal is to highlight, clarify, and, in some cases, correct parts of the report that are important, confusing, or incorrect to insure that you have the best introduction to strategic sourcing decision optimization that one can have.
In this chapter, the optimization enhanced sourcing cycle is enhanced. The first issue is cycle time. According to the report “at one company, the time from first exposure to the optimization concept to completion of the first pilot run was one year … this is probably fairly typical“. While this is likely true at larger companies, it needs to be clarified that while it takes some companies a while to first buy into the concept and then acquire a solution, a good provider can take you through a pilot on a moderately sophisticated category in under 6 weeks.
The typical cycle times for each activity in the bid cycle given for the example company are worth noting:
This says that cycles varied from two weeks and three days to over eight months, which demonstrates that simpler events will not take very long while you should plan for up to six months for very complicated events like rebidding all of your global freight lanes in a single project. (And yes, modern solutions are powerful enough to do just this. A customer of Trade Extensions recently conducted a self-service Billion Dollar event that consisted of 65,000 items, 60,000 transport destinations, and 400,000 bids from over 100 suppliers.)
Finally, as the report states, the total time to complete the sourcing process will be directly related to the number of scenarios tested and the number of rebidding cycles and solving the model with constraints can take from a few minutes for smaller, less complex buys to several hours for large, complex buys. Thus, the more scenarios you want to analyze, the longer it will take. However, you can still run through more scenarios in a day than a spreadsheet would allow you to do in a week, or a month, for more complex models. So while it can take a week or two to analyze all of the meaningful scenarios for a larger project, it’s a drop in the bucket compared to the analysis time if you were still using unmanageable spreadsheets.
This series discusses the recent report from CAPS Research on “the role of optimization in strategic sourcing”. The primary goal is to highlight, clarify, and, in some cases, correct parts of the report that are important, confusing, or incorrect to insure that you have the best introduction to strategic sourcing decision optimization that one can have.
The chapter starts out with a list of ten questions designed to help organizations evaluate the appropriateness of optimization for their sourcing event. And while I still contend that every event can benefit, the question list will help you determine how beneficial optimization could be. In short, the questions were:
Next it goes on to discuss the resources required. While you will need each of the resources identified in your organization, you won’t necessarily need all of the resources on each team. For small projects, all you will need is a category expert with an intermediate level of optimization knowledge and a support person who can assist the suppliers in entering their bids. For reference, in addition to support personnel from your optimization solution provider who should be available as needed, the resources that need to be available to you in your organization if you are to make full use of sourcing optimization include:
Then it goes on to discuss the different types of solution models you have to choose from, which basically fall into three categories:
It concludes by discussing a number of awareness and training issues and process requirements. Some of the more critical awareness issues include:
Finally, the following implementation tips should be heeded:
Next Part V: The Optimization Sourcing Cycle
This series discusses the recent report from CAPS Research on “the role of optimization in strategic sourcing”. The primary goal is to highlight, clarify, and, in some cases, correct parts of the report that are important, confusing, or incorrect to insure that you have the best introduction to strategic sourcing decision optimization that one can have.
This chapter starts off by explaining the buyer and supplier data requirements for decision optimization and it does a good job. The five data requirements it lists for a buyer are spot on:
Next it goes on to discuss a number of optimization model issues including those of model size, complex sourcing events, small and standard buys, and the optimization sweet spot. The report did a good job on these issues, but three points need to be clarified.
While it is true that many moderately sized problems will still be challenging for a desktop or laptop, moderately sized problems can easily be solved in a matter of minutes (and sometimes even seconds) on average mid-end servers. Furthermore, today’s high-end servers can handle problems that are quite large indeed. And while it may still be the case that no single provider can handle all of your strategic sourcing decision optimization needs, the 80% solution is still a great one — license a solution that gives you 80% coverage and then utilize a second provider for large, custom, high-dollar events where the ROI will dwarf the additional cost.
The report correctly states that while it is quite possible that the software will not find ‘provable’ optimal solutions for the model, the software can nearly always find good solutions that will be ‘near optimal’. However, it does not state that those ‘near optimal’ solutions will be ‘provably’ near optimal, which is always the case with MILP optimization (that is the foundation of the majority of strategic sourcing decision optimization products on the market today). Since MILP solvers start by finding the optimal solution to the relaxed linear model, the distance of each successive solution from the absolute lower bound (which can be increased every time a solution sub-space is fully explored) is always known. So even though there may not be enough time to fully explore the potential solution space and find the provably optimal solution, the solution returned is provably near optimal within a certain tolerance.
Finally, the statement that most e-purchasing suites have an optimization module that can address the large number of bidding opportunities in this area is laughable. There are dozens (and dozens) of providers who offer e-sourcing and / or e-procurement suites (just check the resource site), but only a handful that offer (true) strategic sourcing decision optimization. When it comes to strategic sourcing decision optimization, you’re pretty much limited to Algorhythm, Bravo Solution (Vertical Net), CombineNet, Emptoris, Iasta, or Trade Extensions … only four of these can be considered suites … and only four are self-service. While I expect that we will see more providers with true optimization offerings as part of their suites in the future, until the utilization of strategic sourcing decision optimization becomes mainstream, I don’t expect any new providers will emerge.
Next Part IV: Implementation Issues
This series discusses the recent report from CAPS Research on “the role of optimization in strategic sourcing”. The primary goal is to highlight, clarify, and, in some cases, correct parts of the report that are important, confusing, or incorrect to insure that you have the best introduction to strategic sourcing decision optimization that one can have.
The second chapter did a great job of highlighting the many benefits of optimization from a productivity, cost/price, and decision visibility perspective. In brief, they are:
Productivity
Cost/Price
Decision Visibility
It also did a good job pointing out that good strategic sourcing decision optimization models also allow qualitative criteria to be analyzed. For example, you can exclude all suppliers with a service level of less than 95% or a product quality less than 8 (on a scale of 1 to 10). The ability to consider non-price decision criteria, used creatively, allows you to model and calculate a wide range of cost vs. value trade-offs and make better overall sourcing decisions. A great example of the power is the user who ran two scenarios where one scenario forced all rubber-based parts against a baseline that allowed the user to gain insight into how the cost of rubber was impacting her costs.
Next Part III: Preparing for Optimization