Category Archives: Decision Optimization

Safety Stock or Service Levels?

The answer is easy. Both!

A recent article in Industry Week on “The MRO Dilemma” asked if you should focus on safety stock or service levels. The answer is both.

The article, which notes that waste is generated every time a piece of equipment breaks down or runs at less than optimal speed because of needed repairs, and that these repairs are delayed if there is not enough spares on hand, notes that more MRO inventory translates to higher inventory carrying costs but also likely higher service levels while less inventory will reduce the carrying costs [while putting] service levels in jeopardy. This is obvious.

It is also obvious that trying to maintain 100% service levels is likely not an option for most companies because that would mean you just about built a duplicate plant in your store room.

But what might not be so obvious is that the 95% service level recommended as a good target is not good advice at all. The target service level does not, as the article indicates, depend on what your company can afford, but depends on what is optimal for your company. And it is often production line / product specific. A production line producing your most profitable product line should never be down, and if that dictates a costly 98% service level, so be it. However, the turn around time on replacing a printer in the admin offices is not nearly as critical and you can accept a service level of 90%, or less, from your internal IT support, especially if they have outsourced the function to a vendor and a higher service level would increase costs 20%.

Just like you optimize your buy, you optimize your service levels. If downtime on a production line costs you $1,000,000 per hour, you spend $100,000 to make sure you have spares for every moving part that can break. If downtime on a secondary machine that is only required for custom orders, which account for less than 10% of profits, only costs you $10,000 an hour, and stocking the same level of spares would cost you $50,000, you opt for a lower service level. It’s all about optimization.

And, there are companies like Servigistics and MCA Solutions, just to name a couple, that can help you optimize this trade-off so that you’re not improving inventory carrying costs at the expense of service levels and vice versa. With optimization, you can have both … at the right levels that are the most profitable for your organization. Be smart.

Six Secrets of Successful Freight Tenders

A recent article over on Canadian Transportation and Logistics on “the five secrets of successful freight tenders” had some really great tips for getting the best bang for your buck that makes the article a must read. However, it missed one very important tip, which is probably why it claims that Freight RFPs are analytically challenging. (This used to be true, but it’s not anymore. If it’s still true in your organization, then your organization is stuck in the middle ages and it’s time to at least step up to the industrial age.)

Before we get to the tip it missed, let’s start with the tips it provided because at least one of these is overlooked on many a project.

  • Sell your freight.
    Provide as much information as possible about your freight requirements. For each product, include transport, storage, volume, and frequency requirements. The more accurate and complete the RFx, the better quote the carrier can give you. Without detailed information, carriers will build in a “risk premium” so they don’t end up with “bad freight” and both parties lose.
  • Provide enough time.
    Without enough time to analyze your requirements and consider the fit, you’ll get a rough bid that won’t be the carrier’s best proposal. Remember that, depending on the time of year, it will likely sit on someone’s desk for a week, then in pricing for another week, before someone gets to it in the third week. If detailed analysis is required by the “number cruncher”, it could take a month to get the best bid.
  • Standardize the accessorial program.
    Variety and complexity of programs can make the analysis of bid responses unnecessarily complex, as you will be trying to compare apples to oranges to potatoes. And while maybe you can force fit compare the first two, the third poses quite a challenge. Create one program with one uniform set of charges that applies to all carriers.
  • Fully analyze rate proposals across the board.
    Typically carriers will give you aggressive discounts on major lanes to lure your business, but keep discounts to minor lanes minimal, or non-existent. As a result, you may pay more for freight overall if you end up shipping more on secondary lanes.
  • Benchmark results
    Freight patterns can change, and the net result is that a new freight schedule expected to save you money costs you more in the end. “Shadow rate” your current shipments using at least your last rates (if not your last two rates) to get a feel for what freight profiles give you the best deal overall.

But most importantly:

  • Use a sourcing package that can handle freight optimization and multi-level freight bids.
    A good strategic sourcing decision optimization platform (as provided by Algorhythm, BravoSolution, CombineNet, Emptoris, Iasta, or Trade Extensions) will not only allow for full analysis of the entire freight bid, but allow for the easy import of multi-level freight bids from excel spreadsheets. More specifically, these modern packages allow a carrier to define (inter)national rates by weight, volume, or distance, and then override these by region, and then by lane. This will allow a carrier to quickly define standard bids for low-volume lanes or lanes that they are not interested in and focus in on the lanes that fit their network and that they want to aggressively bid on. A carrier can bid on a 10,000 lane global sourcing project in a couple of hours. This decreases response time and increases bid quality.

Innovation in Sourcing

Today’s guest post is from Chetan Raniga, who is General Manager, Americas at Trade Extensions.

As someone who’s been in the strategic sourcing field for over ten years as a consultant and product manager, it’s been interesting to see the rapid evolution of sourcing solutions over the past few years. Leading solution companies now realize that users need solutions that feel familiar; that’s why Excel integration is common among leaders in the supply management arena. It’s the same reason Coupa has screens that almost mirror Amazon.com — providing an interface and workflow that’s both familiar and intuitive. Another example is the use of dashboards — the charts and alerts in Trade Extensions remind users of Mint.com, a popular personal finance site, though they show vastly different types of data!

Here are some other changes for the better:

Collaboration and Workflow:
The sourcing solutions of the past were extremely tactical (e.g., automating the process of running an RFQ or auction for a specific category), and therefore, didn’t give buyers the ability to share ideas, exchange documents, and view the real-time status of their sourcing initiatives. Now, platforms provide robust project management capabilities with Gantt charting, custom workflows (e.g., only have new suppliers go through the qualification step), document sharing, and Skype-like chat features. A buyer can see exactly which suppliers, team members, and stakeholders are online, and instantly communicate with them. Audit trail and logging capabilities have also gotten stronger, which is important for the confidence of both buyers and suppliers in using these platforms. Multiple teams are now using these platforms to share data. For example, a Direct Materials sourcing group can incorporate freight pricing from a tender conducted by the Logistics team. The group can use the platform to determine which items will use the suppliers’ freight (delivered pricing) and which will use the 3rd party carriers’ freight (FOB plus freight).

Flexibility:
Systems of the past didn’t provide the flexibility that we have today in collecting inputs. Labels such as ‘Price per Unit’ would be hard-coded or the cost formula would only support a limited number of operators and functions. Data entry was also cumbersome and error-prone since it involved either manually entering or copying-and-pasting vast amounts of data. Today’s solutions integrate with Excel, so that existing data and formulas can be easily leveraged. For example, item, demand, and cost component data stored on separate Excel spreadsheets can be uploaded with one click. Even better, some solutions allow users the ability to customize the supplier’s bid form. This is critical to change management since companies can continue to use their existing bid forms in the bid gathering phase but obtain the decision support and reporting benefits in the analysis phase. These improvements have led to even shorter RFQ/P creation times.

It’s also now possible to run auctions with optimization (a step forward in utility from the original concept of reverse auctions), and to run RFQ/Ps with feedback — blurring the line between RFQs and auctions but also going further by providing custom feedback (e.g., a custom message of “Not Competitive” is shown when the bid is x% greater than the median price).

Usability in the Analysis Stage:
The one sourcing area that has lagged in adoption has been the use of optimization (which the doctor has defined as the application of one or more rigorous analytical techniques to a well-defined model to generate the absolute best decision from a multitude of possible alternatives in a rigorous, repeatable, and provable fashion). It sounds complicated, and in the past it really was. For example, if a customer wanted to see what the result would be if all the business went to incumbents at their current proportions, then she’d have to create a rule limiting allocation for each item and affected supplier. That’s painstaking when you have a couple of hundred items — but most projects had thousands of items! Nowadays, in a modern optimization solution (which include the solutions by Trade Extensions and BravoSolution), the buyer just selects one rule, written in plain English (as shown below).


Even better, new platforms allow buyers the ability to create rules in Excel and then upload them. In the example below, the buyer is setting limits by plant and supplier simply by completing a table.


Reporting:
The solutions of the past didn’t offer much in terms of reporting. Most had a couple of pre-defined reports that exported to Excel. Buyers had to spend additional time modifying the reports — even changing labels and creating pivot tables — before they could present the results to their peers and managers.

Solutions today have made major strides in this area. Leading spend analysis tools (which include BIQ as well as Trade Extensions) allow users to create custom reports that can be saved as templates and re-used. The ability to choose specific dimensions (rows), columns (facts), and other information means that users no longer have to go outside the system for further manipulation. Some tools even allow the ability to drill-down/up on data (e.g., view allocation data by country first, then by region, then by state, and finally by city/plant).

We have heard buyers comment that their analysis time is shortened by three-and-a-half (3.5) weeks on average by using the new decision support and reporting capabilities mentioned above.

Thanks, Chetan!

How can we minimize our costs while maximizing the use of our current assets?

Modelling, Simulation, and, most importantly, Decision Optimization … and I’m very glad to see that the ISM recently ran an article in Inside Supply Management on “Improving with M&S”. Because, as the article points out, once the behaviour of a system is understood, supply managers can realign assets with the intent of finding the arrangement that will yield the most optimal measures of performance.

Furthermore, as the article points out, modelling, in its most basic form, is the creation and arrangement of representational elements that approximate reality. Simulation is the potential interaction, or playing out, of these elements over time. And optimization is the application of rigorous analytical techniques to a well-defined scenario to arrive at the absolute best decision out of a multitude of possible alternatives in a rigorous, repeatable, and provable fashion. Together, the technologies can be used to determine how to balance costs and resources.

The article gives some great tips for novices in MOS (Modelling, Optimization, and Simulation). Specifically, it notes that:

  • the goal is not to mirror the real-world system in all its detail but to represent those aspects that are expected to meaningfully affect the performance variables of most interest
    as it is impossible to model everything, there is a need to focus on what is relevant; for example, there may be 50 different cost elements in a breakdown of a component down to raw materials, but if 10 of them represent 80% of the cost, and only 5 of them are variable, focus on those 5 and wrap the other 46 into one
  • if the model and simulation are producing behaviour similar to the known real world, then the model most likely is an appropriate, or valid, reflection of that real-world system
    if the model works well, don’t second guess it; unknown is unknown and trying to guess the unknown doesn’t make it known
  • we learn through experimentation
    but experimenting with the real system is costly, counterproductive, and could meet organizational resistance
  • the process of modelling and simulating a real-world system assists in identifying major system strengths and weaknesses
    strengths which can be leveraged through targeted interventions and weaknesses which can be overcome through appropriate system redesign; the process of identifying strengths and weaknesses and virtually experimenting with changes to the system allows analysts and supply managers to see unintended second- or third-order consequences that might not have been readily apparent otherwise
  • selecting and analyzing various supply management activities and processes can be crucial in improving efficiencies and performance
    if the organization doesn’t know where its performance can be improved, then it will not be able to improve its performance

All great tips and all reasons why modelling, simulation, and optimization should be used by each and every Global 3000 organization.

What to Look for in a Strategic Sourcing Decision Optimization Solution

Once it is understood that Strategic Sourcing Decision Optimization is the application of rigorous analytical techniques to a well-defined sourcing scenario to arrive at the absolute best decision out of a multitude of possible alternatives in a rigorous, repeatable, and provable fashion, one can define some core capabilities of a strategic sourcing decision optimization platform. Then, when one is looking for a sourcing platform that includes decision optimization, one can determine whether or not the platform includes true strategic sourcing decision optimization foundations.

The following are core capabilities that should be present in any platform that claims to be based on strategic sourcing decision optimization:

  • Solid Mathematical Foundations
    LP, MILP, QP, and Convex optimization are good foundations. Random sampling, Monte Carlo simulation, and evolutionary / genetic programming are, on their own, not sufficient.
  • True Cost Modelling
    The models must be accurate and complete. Not “close” approximations.
  • Sophisticated Constraint Analysis
    At a minimum, capacity, allocation, (risk) mitigation, and qualitative constraints must be supported.
  • What If? Capability
    The “holy grail”, the tool must be able to generate, analyze, and compare multiple “what if?” scenarios in order to truly be useful to the organization.

In addition, the following capabilities are nice to have:

  • Constraint Impact Analysis
    Why is this solution “optimal”? Which constraints are driving the allocation?
  • Network Modelling
    for the analysis of demand across multiple categories and network (re)design
  • Automatic Scenario Generation
    that automatically creates “what if?” variants of a given scenario to jump-start analysis

For more information, see our recent article on What to Look For in a Strategic Sourcing Decision Optimization Solution over on the new Next Level Supply site. This article, that summarizes and updates some of SI’s best writings on Decision Optimization, including the Next Level Purchasing Optimization Interview and the e-Sourcing WikiPaper, is a good refresher for those of you looking to (re) acquire a sourcing platform based on strategic sourcing decision optimization.