Category Archives: Decision Optimization

Questions to Ask your Optimization Vendor

Not all optimization vendors are equal … and more importantly, not all vendors that claim to have decision optimization even have it (as their systems barely qualify as decision support). Thus, since Emptoris [acquired by IBM, sunset in 2017] just released a new version of their offering, since Iasta [acquired by Selectica, merged with b-Pack, rebranded Determine, acquired by Corcentric] is coming out with their first heavy-hitting release in the next month, and since CombineNet [acquired by Jaggaer] is always working on something new, it’s important that you be able to distinguish between the relative strengths and weaknesses of the different products, as well as how much strength you really need, if good decision optimization is one of your driving reasons for selecting a (new) e-Sourcing solution. (And, by the way, it should be!)

Now, as I indicated in a comment over on Spend Matters (in “Emptoris 7 Pushing the Sourcing Envelope”), I’m not going to devote a post analyzing the new Emptoris announcement at this time, as I don’t yet have enough data points to even make a half-assed*0 attempt (although I do feel I have a pretty good idea precisely what they did based upon their choice of wording, the amount of time they’ve been working on it, and my perception of their in-house skill level), but I really think you should analyze it, just as you should analyze any other vendor’s solution, before buying it. (Not necessarily because I don’t think it will do the job, but because the key with optimization is buying just what you need in the majority of your sourcing events. Optimization is expensive. Buying too much power could severely impact your potential ROI, and buying too little power will be equivalent of flushing that investment down the drain as it won’t solve the majority of your problems. I’m using the word “majority” because there is no general purpose decision optimization product for sourcing that will handle all of your events and solve all your problems. As with just about everything else in business, it’s the 80-20 rule. The best solution is the one that solves as close to 80% as possible at a cost of ownership that maximizes your ROI multiple. You can always do one-time projects with best-of-breed providers or specialist outsource providers for those projects in the remaining 20% where there is enough of a savings opportunity.)

Before I get to the question list, I should point out that it’s almost impossible to cover every question, as many of the questions you should be asking depend on the answers you receive to your first few questions, but I think the question list below is a good starting point. If I get some good feedback, and some more free time, I’ll consider doing a part II at a later date. So, without further ado, here’s the starting list!

  1. Does your product meet the four critera for strategic sourcing decision optimization as outlined in the Strategic Sourcing Decision Optimization wiki-paper on the e-Sourcing Wiki [WayBackMachine]  (initially authored by the doctor, the all-knowing optimization guru*1)? Specifically, does it support the following:
    • Sound & Complete Solid Mathematical Foundations
      such as simplex algorithms and branch-and-bound;
      many simulation and heuristic algorithms do not guarantee analysis of every possible solution (sub)space given enough time, and, thus, are not complete in mathematical terms
    • True Cost Modeling
      many bidders bid tiered bids, discounts, and fixed cost components – the model must be capable of supporting each of these bid types
    • Sophisticated Constraint Analysis
      At a minimum, the model must be able to support reasonably generic and flexible constraints in each of the following four categories

      • Capacity / Limit
        allowing an award of 200K units to a supplier who can only supplier 100K units does not make for a valid model
      • Basic Allocation
        you should be able to specify that a supplier receinves a certain amount of the business, and that business is split between two or more suppliers in feasible percentage ranges
      • Risk Mitigation
        let’s face it – supply chains today are all about risk management, and you should be able to force multiple suppliers, geographies, lanes, etc. to mitigate those risks without specifying specific suppliers, geographies, lanes, etc. to take advantage of the full power of decision optimization
      • Qualitative
        A good model considers quality, defect rates, waste, on-time delivery, etc.
    • What-if Capability
      The strength of decision optimization lies in what-if analysis. Keep reading.
  2. Does it support the creation of multiple what-if scenarios and does it simplify the creation of these scenarios?
    The true power of decision optimization does not lie in the model solution, but the ability to create different models that represent different eventualities (as this will allow you to hone in on a robust and realistic solution), to create different models off a base model plus or minus one or more constraints (as this will help you figure out how much a business rule or network design constraint costs you), and to create models under different pricing scenarios (to find out what would happen if preferred suppliers decreased prices or increased supply availability).
  3. How fast is it for different average model sizes and can performance be tweaked?
    Optimization takes what it takes. That being said, if one solution takes an average of 1 hour for an average scenario, and another solution takes 10 minutes, all things being equal, if you have compressed sourcing cycles, the 10 minute solution might be better. Emphasis on “might”. This is only true if the faster solution is of the same quality – some models, and some solvers, sacrifice quality and accuracy for speed. The best solution will let you trade off “tolerance” and accuracy for speed. Sometimes it’s easy to get within 1% or 2% in a few minutes, even though that last 1% or 2% could take hours. On a model with low total savings potential, getting within 1% may be enough. And when trying to hone in on the right what-if scenario, it’s nice to get within 1% quickly and then allow the right scenario to run to completion over night after you’ve quickly analyzed half-a-dozen scenarios and settled on your preferred scenario. Thus, tweaking ability is very important.
  4. If it supports “real-time” is it “true” real-time or “near” real-time.
    Thanks to significant advances in processor and hardware performance as well as off-the-shelf optimizer technology (like ILog’s CPlex), it’s now possible to rapidly re-build and re-solve moderately sized models using off-the-shelf modeling languages in seconds, allowing for e-auction tools that keep the model relatively small and simple to incorporate decision optimization in near-real-time by simply re-building and re-solving the model every 30-60 seconds (depending on model-size) on a high-powered dual or quad core server with an appropriately configured and optimized CPlex 10. However, this is NOT true real-time optimization and could rapidly break down if the model gets too big or too complex. (For example, real-time optimization requires the ability to merge model construction and model solution in such a way that a new bid can be introduced as a parameter change that does not require the optimizer to rebuild the sparse model matrix and start the solution process over from scratch.)
  5. Describe two or three scenarios you have encountered where you could not model the situation exactly for companies in our vertical, how you worked around the issue, and how accurate the result was.
    No optimization model can handle every real-world scenario 100% accurately. If a vendor representative says so, he’s either lying through his teeth or not competent enough to be selling the product. (Note that: I’ll have our support expert get back to you on that is a good answer from an average sales representative.) This is about the only way to get a decent idea of how appropriate the tool is for you. If the scenarios were complex and the constraints based on business rules you hardly ever, or never, use, then the solution is probably okay for you. If the scenarios were simple and the constraints based on business rules you use all the time, it’s probably not the tool for you.
  6. Can we do a pilot project before committing to a long term license?
    If you like what you hear, but are still unsure, or are having problems getting the budget approved, a pilot is often the way to go! (Note that I did not use the word “free”. You should be willing to pay for services at a rate that is sufficient to cover the provider’s cost for this pilot – especially considering that many of the companies that offer affordable optimization offerings are only able to do so because they keep their costs and overheads down – and if they gave free services away to everyone who requested a free pilot, they would have to increase their costs, and that would be a detriment to everyone, including you, in the long run.)
  7. We’re having problems understanding how this fits into our business or what the best solution for us is. Would you be willing to demo your solution to, and answer questions from, our consultant who understands both our needs and decision optimization technology?
    Let’s face it – just like the right decision optimization tool can deliver huge savings multiples on your investment (10X or more), the wrong tool will simply represent a six (or seven) figure cost that yields little return. If you can’t tell the difference, and there’s no shame in admitting you can’t if you’ve never used this type of technology before, then you should bring in a consultant*2 who can to help you select the right technology, and ensure you are appropriately trained on it, until you are self sufficient and saving an average of 10% to 12% per project put through the tool.

*0 And we all know that any decent attempt should be full-assed!
*1 You should feel free to proclaim my greatness whenever you are not in my presence! I don’t mind.
*2 Just remember that, unfortunately, this consultant may not be able to help you if you want Emptoris evaluated. (And I’m sure that some of you should definitely be evaluating the Emptoris solution.)

The 2nd Sourcing Innovation Series – Let’s Get Analytical!

Spend Analysis. Decision Optimization. Cost Modeling. Almost since the beginning, these have been the six dirty words of strategic sourcing. Study after study has found that these techniques easily save 8% to 15% for just about any organization that spends more than 500M a year, but yet, on average less than one fifth of companies out there have tried these technologies, and less than one tenth are using them. It’s like they’re taboo. Well, in the not too far off future, the tables are going to turn, and instead of being the six dirty words, Spend Analysis Based Cost Modeling Decision Optimization are going to be the seven words of saving grace for tomorrow’s sourcing organization that wants to survive beyond the next decade. But the technology of tomorrow is not going to be the technology of today. But first …

Why? There are numerous reasons that this will happen, including negative returns from reverse auctions from early adopters, the forthcoming fall-out of the majority of first-generation supplier networks and marketplaces that still remain, and the eventual realization that contract management is not the holy grail if you don’t have a good contract in the first place, but the primary reason this will happen is the G-Word. Globalization. The effects we’re starting to see now are nothing like what’s going to come, especially since the majority of companies are unprepared!

Tactical job loss to outsourcing, rampant inflation in raw materials due to skyrocketing demand from developing countries, quality issues, and CSR (Corporate Social Responsibility), or should I say CSI (Corporate Social Irresponsibility), issues are only going to compound in the coming years. And, without recourse, this is only going to push costs, as they say, through the roof of the nearest skyscraper!

The only way companies are going to be able to maintain costs, yet alone achieve savings, is by getting a firm handle on costs and, more importantly, by identifying and achieving savings opportunities not previously explored. This is going to require an improved understanding of the cost drivers of what you are buying (cost modeling), and understanding of where variability exists, either within past buys or against market indices (spend analysis), and what the best award scenarios are (optimization).

But it won’t be three applications at three different stages of the sourcing process, it will be one, and it will be at the beginning, center, and end of the sourcing process. Think about what CoExprise is doing for the management of contract manufacturing – integrating the important PLM, Sourcing, and Procurement aspects of complex assembly sourcing – it will be something like that. But instead of an Aravo-Iasta*1-Ketera*2 union for a specific domain, it will be an Apriori–CombineNet–BIQ–Akoya union for the generic product domain. And it will look like nothing you’ve seen before. Sourcing tomorrow will be quite different than sourcing today. The only question is, who are the brave souls that are going to lead the way?

*1 Iasta was acquired by Selectica, merged with b-Pack, rebranded Determine, acquired by Corcentric
*2 Ketere was acquired by Deem

The future’s coming hard and fast … and I’m gonna be on the freight train that meets it head on!

Two Great New Optimization Resources

For those of you looking for a good introductory overview of decision optimization for strategic sourcing, two new resources hit the bit-stream today.

First of all, there’s the 2-Part “What is Supply Chain Optimization?” podcast, part of the Next Level Purchasing’s (now the Certitrek NLPA) podcast series that features Charles Dominick (a Supply And Demand Chain Executive Pro to Know), President of Next Level Purchasing (a Supply & Demand Chain Executive 100 Company) and yours truly. (For more details, see today’s edition of the Next Level Purchasing newsletter.) Clocking in at just under an hour, we try our best to convey the basics of strategic sourcing decision optimization and why it’s important to you as a sourcing / procurement / supply mananagement professional. For those of you who find the podcast quite dense (it is!), and wish to review one or more sections, you’ll be pleased to know that a free transcript (basic or with editorial notes) is available, sponsored by Sourcing Innovation.

Secondly, over on the eSourcing Wiki [WayBackMachine] (which, as of today, has 18 wiki-papers on various topics relevant to you as a sourcing professional with more on the way), the Strategic Sourcing Decision Optimization wiki-paper is now available, sponsored by Iasta (acquired by Selectica, merged with b-Pack, rebranded Determine, acquired by Corcentric). Along with an introduction to optimization, including strategic sourcing decision optimization, it also overviews the benefits and ten strategies for success.

When you add both of these resources to the ever increasing archive of decision optimization blog posts here on Sourcing Innovation, I believe (or at least I hope that) you finally have the resources you need to start understanding what strategic sourcing decision optimization is, is not, and why it’s important. Especially when you consider that Emptoris (acquired by IBM, sunset in 2017) gives you nothing and CombineNet (acquired by Jaggaer) primarily gives you academic papers in their learning center, which, although great, are too advanced for those of you looking for an introduction that you can understand as a non-academic and non-optimization researcher.

What’s Involved in SCNO (Supply Chain Network Optimization)? Part III

In Part I, we defined Supply (Chain) Network Optimization as the optimization of your global distribution network to minimize costs while controlling risk to an acceptable level, discussed the various costs involved in a supply chain network, outlined some of the questions you should be asking, and outlined some of the complexities associated with Supply Chain Network Optimization.

In Part II, we reminded you that supply network optimization, of which freight / transportation cost optimization is a significant part, does not belong as part of a standard sourcing project (since only freight rates, and not total costs, can be fixed and freight costs will always be an approximation anyway) and that if you are considering an award where freight dominates the cost, then you should be optimizing your transportation cost and estimating your unit cost (based upon quoted rates and expected discounts from pre-qualified suppliers in the region), since the largest savings are generally achieved from optimizing the component of spend that makes up the majority of spend, not the minority.

Today, we going to discuss some of the challenges of global distribution, as highlighted in the ESYNC white-paper, “Strategic Assessments” (registration required) that prompted me to white this series of posts. Even though the white paper itself did not live up to the promises implied by its title (it’s sorely lacking on the distribution network front and the strategy front), the Operation’s Analysis & Opportunity Assessment table on page 2 and 3 did a good job summarizing the challenges with (global) distribution and outlining why you need appropriate supply chain information technology to help you manage your global supply network.

Challenge Root Causes
Short Shipments Inadequate Inventory Management, Missing Stock and Poor Warehouse Management,

Picking, Packing, and Staging Errors
Shipping Errors Loading and Carrier Errors, Poor Product / Packing Identification Processes
Operator Productivity Facility Layout, Material Flow, Processes, Procedures & Systems
Late Deliveries Weak Scheduling and/or Carrier Selection
Tracking Data Integrity Disconnect between shipper and carrier information systems
Customer Service Responsiveness Weak / No Link between call center & fulfillment systems
Returns Processing Ill-defined processes and procedures; incomplete/non-existant interface between

call center & fulmillment system
Costs Facility & Equipment; Labor; Shipping; Outsourcing

The table also included an “ESYNC Approach” column which, predictably, revolved around AIDC, WMS (Warehouse Management Systems), TMS (Transportation Management Systems), and RFID – technologies that ESYNC sells or integrates with. These are good suggestions, but they don’t completely address the problem. You need IMS (Inventory Management Systems) that go beyond the warehouse and integrate with forecasting systems; GDM/GTM (Global Data Management / Global Trade Management) systems that help you comply with all of the regulatory requirements of the countries you operate in, all of the import and export customs requirements, and all of the taxation laws (including those that allow you to claim refunds under certain conditions); and proper modeling and optimization tools to make sure you have the right network in the first place.

What’s Involved in SCNO (Supply Chain Network Optimization)? Part II

Yesterday, I said that Supply (Chain) Network Optimization (SCNO, or SNO, but not snow), which is not easy, is the optimization of your global distribution network to minimize costs while controlling risk to an acceptable level. Furthermore, it’s not something you should tackle as part of your everyday sourcing project.

Yes, I’m saying it again. And the next person who dares to suggest otherwise gets an e-coupon for a free smack upside the head, redeemable the next time we meet. The nature of distribution network optimization is that it cannot be optimized within a single sourcing scenario, and any attempt to do so is likely to do more harm than good. To truly optimize your network, you have to optimize across all of your buys, and even in any given year, you’re likely renegotiating less than a third of your major contracts and a quarter of your buys, and you don’t expand into new countries overnight.

Furthermore, since you are contracting for fixed rates, not fixed costs, and your total costs depend on actual volumes, which are forecasted and variable, your freight costs at the time of award are approximations. If you’ve done your homework, and are revisiting your freight contracts semi-annually or annually, like you should be, you should be within a few percentage points, at most, with these estimates. Let’s say worst case scenario where you’re off by 5% because you didn’t quite meet demand to get that rebate you were hoping for (since your estimate demand was only 1% above the cutoff). In an average strategic sourcing scenario, you’re looking at freight in the 5% to 15% range, so you’re off by at most 5% of 15% or 0.75%. Worst case, you’re off by 0.75% – but since you have an equal chance of being off either way if you’re estimating properly, it’s going to average out over all your awards and you’ll be within a fraction of a percent of optimal (unless oil spikes again and huge surcharges come into play, but since all your competitors will be paying the same surcharge that every carrier will be levying above the board, you’ll still be ahead compared to your peers, relatively speaking, if you have the right lanes at the right volumes for the right rates with the right carriers).

The proper way to optimize distribution network costs is to semi-annually or annually analyze all of your projected transportation needs over the next 6 to 12 months using all of your projected shipments (based upon current contracts, forecasts, and current patterns), aggregate volumes across lane groups (defined as the set of lanes that take a product from region A (such as a set of posts on the southwest coast) to region B (your major re-distribution center outside Chicago), bid out the appropriate lanes or lane groups to one or more carriers, and optimize a transportation award to these carriers who quote rates based upon minimum volume guarantees (such as 75% of expected volume across the lane). This gives you highly accurate freight rates to use in your award allocations.

On top of this, every one to three years you should be re-optimizing the flexible aspects of your distribution network. By this I mean, re-evaluating warehousing space that you are leasing or that is highly liquid and could be easily sold, re-evaluating the air and ocean freight options to you, re-evaluating the ports you are using, and re-evaluating your shipment consolidation strategy (should you always wait for shipments from multiple suppliers to fill the container or should you use a third party that can consolidate shipments for multiple buyers to fill the container).

For example, maybe sales on the west-coast are high and the east-coast are low, maybe you’ve experienced three major delays at your current port of choice, and maybe part of your cargo is always depreciating by waiting for enough cargo to fill a container. In this case, you would model the expected costs of retaining your current distribution network versus the costs of different network designs that cancelled the lease of one of your east coast distribution facilities, used a different port, and / or used a third party logistics provider to determine whether or not a redesigned network could offer you a lower operating cost (taking into account the one-time fixed costs associated with any restructuring you had to do, amortized over appropriate minimum contract periods).

Then, every three to five years, you should be re-optimizing the distribution network as a whole, including the fixed aspects of your distribution network. By this I mean every single warehouse and facility, every single warehouse and distribution facility, every single port of exit and entry, and every single carrier is considered to be floating and the cost of the current network is compared against a fully optimized solution (that takes into account all of the one-time fixed costs that will be associated with any and all restructuring) optimized over different, appropriate, minimum contract periods (from three to seven years, as the optimal model may change from year to year as volume projections will change year over year and existing contracts will expire, decreasing the fixed costs associated with a restructuring). Then, each of the optimal network model solutions that represent a significant cost savings should be compared against the current network model and those that represent the minimal deviations from the current model analyzed in depth. (Even if a totally redesigned network could offer lower cost savings, it’s a bad idea to re-design your whole network at once. Most big-bang efforts end in failure. Furthermore, it usually only takes a few major changes to produce significant savings, if done, right, and the longer it takes to redesign your network, the more you are relying on the accuracy of your long term forecasts to realize these savings, increasing the risks associated with redesign.

Finally, at least the first few times you do this, be sure to bring in an expert and make sure the appropriate tools are available. Even though these resources may be expensive, partly due to the relative lack of expertise in this area and partly due to the significant education and experience required to do these projects properly, (since you need expertise in Operations Research (OR), optimization, modeling, supply chain, analysis, and consulting), as another resident guru of the blog-sphere would be quick to point out, it’s not what you pay, but what you get out of it. You might think that 3K to 5K a day is expensive, but if that person, with access to the right tools, saves you millions of dollars, a hundred grand or two in professional services, (on-demand) software costs, and project costs is paltry in comparison. It’s the net value of the ROI, not the cost, that’s important, as it is in any business project.