Category Archives: Decision Optimization

The Role of Optimization in Strategic Sourcing – The Future of Optimization

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.

What will the future hold? The authors predict development in the following two directions:

  1. more self-serve applications that require no third-party involvement
  2. more powerful services that handle even larger, more complex problems

In other words, the same-old same-old for the foreseeable future. I’m sad to say I have to agree. Until strategic sourcing decision optimization catches on, most of the current providers are not going to make significant investments exploring new vistas for a solution that the majority of their customers aren’t even coming close to stressing out today. You see, current applications are just “scratching the surface” of potential uses. Optimization is very powerful and could ultimately be used to optimize the entire supply chain.

However, the applications will continue to get more user-friendly and easier on the self-service front as providers get exposed to even wider ranges of models and uses and refine their interfaces to support even more possibilities (while simplifying the definition of the average model). So this is something to look forward to.

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Rudimentary Heuristics to Support the Concept of Optimization in Negotiations

Today’s post is from Dr. Lloyd M. Rinehart, an Associate Professor of Marketing and Logistics in the College of Business Administration at the University of Tennessee and author of numerous publications including “Creating Reality Based Relationships Through Effective Negotiation: Academic Concepts and Research Support”, “Creating Reality Based Relationships Through Effective Negotiation: Understanding the Negotiation Process”, and “Effective Negotiation: Understanding the Negotiation Process – A “Road Map” to Successful Sales and Purchasing Negotiation Performance in the Value System”. Lloyd can be reached at Rinehart <at> utk <dot> edu.

This post is based on my presentation at the 2009 MPower BPX roundtable and subsequent thoughts that arose out of my resulting discussions. The concepts that I introduced in the session included the definitional parameters of seven relationships that evolve out of negotiations. These seven relationships, which were covered in the doctor‘s review of my presentation in What Relationships Do You Have With Your Suppliers, include:

  • Non-Strategic Transactions,
  • Administered Relationships,
  • Contractual Relationships,
  • Joint Ventures,
  • Specialty Contract Relationships,
  • Partnerships, and
  • Alliances.

I am going to expand on the concept of definitional parameters of relationships in one form, but in order to do so, I am going to consolidate the seven relationships into three relationship categories:

  • Transactionally Driven (Non-Strategic Transactions and Administered Relationships),
  • Contractual / Investment Driven (Contractual Relationships and Joint Ventures), and
  • Relationally Driven (Specialty Contract Relationships, Partnerships and Alliances).

Generally, whether or not it is actually the case, managers perceive that between 30% and 40% of their relationships fall into each of these general categories. Before we continue, Let me define the characteristics of these relationships. They are built on the three dimensions of trust, interaction frequency, and commitment to the relationship. In other words:

  • Does the party trust the other party?
  • How much does the party interact and exchange with the other party?
  • How committed is the party to the other in terms of dependence and investment?

Transactionally Driven Relationships are low on trust, low on commitment, but can have a range of interaction and exchange.

Contractual / Investment Driven Relationships are “slightly” higher on the trust, interaction frequency, and commitment dimensions than the Transactionally Driven Relationships.

However, those that are Relationally Driven are significantly higher on the trust dimension, while that other dimensions have a range of values.

That brings the discussion to one of today’s hottest terms in business — “collaboration”! Unfortunately, that term, like many others, means about whatever the author would like it to mean (and, consequently, that leaves the readers to interpret the concept as they desire as well!). Herein, I am going to constrain “collaboration” to be situations in which trust in the other party is HIGH. That means that of the relationships listed above, “collaboration” occurs about 30% to 40% of the time.

Now wait a minute! I said that this post is the result of my thoughts and subsequent discussions, which included a discussion with Michael. My understanding is that some of Michael’s contributions to the space deal with the concept of “optimization” in sourcing and procurement. My definition of “optimization” includes the attempt to minimize or maximize inputs that capitalize on the best outcomes across the integration of the inputs. My first exposure to the concept of “optimization” was in mathematics and micro-economics. The micro-economics applications focused on how companies could optimize the characteristics of their operational inputs and outputs.

However, here we are talking about negotiation, which means that at least two parties, rather than one entity, need be optimized. Here is the problem with the percentages given in this post. Those relationship assessments were originally generated from the perceptions of only one of the parties to the relationship. Therefore, the original data does not actually represent the “dyads” (perceptions of both parties on the relationship.) While most managers view negotiations as being too sensitive to allow external researchers to become involved, we can successfully simulate similar relationship perceptions in contrived environments. The contrived environment allows the opportunity to pair up the parties into “dyads” for dyadic assessments.

Outcomes of those assessments indicate that, in reality, only 13% of the relationships reflect situations where BOTH parties perceive high trust in the other party. In this situation, both parties feel comfortable enough in the negotiation to share information with the other party and work together for the purpose of “optimizing” the joint inputs to the relationship between the “two parties”. That is how I define “collaboration”, and the data indicates that it probably does occur 13% of the time. It is also important to recognize that the process of “working together” in the negotiation process involves a “collaborative” strategy in which the parties are attempting to “optimize” the outcome in a “Win – Win” sense.

However, there is another situation, that constitutes 1% of relationships, where balance in the negotiation occurs. That is when both parties approach the negotiation and relationship from a “competitive” strategy perspective. In this case, both parties are very skilled and effective negotiators and collectively drive each other to outcomes that are similar to the “collaborative” outcomes, but instead reach that position by pushing the other party “hard” to achieve a mutually beneficial outcome. In other words, both parties are approaching the relationship from a Transactionally Driven perspective. Therefore, I believe two diametrically opposite relationship perspectives can lead to similar outcomes, even though the negotiation strategies are very different. However, regardless of the strategy implemented, the parties must thoroughly understand the negotiation process.

Before concluding, one other problem must be identified with this discussion. The 13% of the original 30% to 40% of relationships that were perceived to be “high trust” and the 1% of the relationships that were perceived to be low trust leaves 86% of the relationships unaddressed. Those are relationships that are unbalanced in the level of trust between the parties. If one trusts the other party less, then that party will most probably implement opportunistic strategies which will be “self” beneficial and, of course, at the expense of the other party. Therefore, it is critically important that both parties in a negotiation fully understand the negotiation process and know how various strategies can contribute or detract from the desired outcomes of the negotiation.

I hope these thoughts stimulate discussion (both pro and con) that may advance the quality of decision making in your organization.

Thanks, Lloyd!.

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Asset-Oriented Supply Chains Need Supply Chain Network Optimization

I couldn’t agree more with this recent headline from Supply Chain News that notes that Asset-Oriented Supply Chains Need Supply Chain Network Optimization More Than Ever because, like just about every other type of supply chains, they do. This is because, as IDC Manufacturing puts forward in a recent research report,

  • profitability is closely linked to the cost, and efficient use, of raw materials which are steadily increasing in price while market pressure is driving sales prices down,
  • high operating costs (partly due to the continual increase in the cost of energy and water) are making plant efficiency a key concern, and
  • changing demand patterns are adding additional strain to the supply chain from regional shifts and gaps between production and actual demand.

A good supply chain network optimization tool will allow a company with rising costs and shrinking revenues to understand the costs and benefits of each supply chain network option open to them and answer the following questions:

  • What is the optimal allocation of materials or customers to plants and/or distribution centers (DCs)?
  • What is the best location for new plants and/or DCs to minimize freight, inventory holding, and/or rail fleet costs while maximizing customer service levels?
  • How do we reallocate our capacity so we may close (temporarily or permanently) under-performing plants?
  • What capacity should we build into our plants, production lines, or processes, down to the requirements of specific machines or tools?
  • Based on our inventory levels and production capabilities, what is the optimal product mix, considering co- and byproducts?
  • Based on seasonal demand or production limits, what should we pre-build in inventory?
  • How do we optimize our production and distribution schedules for the desired levels of customer service and profitability?
  • What is the profitability impact of crossing borders – from currency exchange rates, tariffs, or duties?

And in this economic climate, such a tool may well make the difference between riding out the economic downturn and becoming a victim of it.

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The Role of Optimization in Strategic Sourcing – Challenges / 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.

This chapter addresses the challenges associated with optimization from a user perspective, which, unfortunately, are numerous. The good news is that they are all easily overcome if you are aware of the issues and address them early on.

User challenges fall into three categories:

  • Increased Knowledge Requirement
    • some people will be afraid of the unknown
      easily addressed with a little education
    • others think optimization is a threat to their job
      easily addressed by explaining optimization is not intelligent, users still need to formulate the models
    • many do not understand the power associated with optimization
      easily addressed by a well-defined pilot
    • utilization can require a significant cultural change
      easily addressed by helping an organization define a change management plan
    • there is a learning curve
      easily addressed through repeated use over time
    • the proper constraints need to be utilized for maximum results
      easily addressed with provider support
  • Measurement of Results
    • it can be difficult to tie cost/benefit to the tool
      but a baseline scenario always provides a good measure
    • market timing can affect the event
      but what-if scenarios can illustrate how much more could be saved/lost with price changes
    • good historical data may not be available
      which means you form a baseline by comparing the unconstrained scenario to the cost of a human-generated solution
    • overuse can lead to “analysis paralysis”
      which means you define the relevant scenarios before you start using the tool, and stop when you have analyzed all of the relevant ones
  • Software Provider Issues
    • tools are still evolving
      the provider needs to explain how current functionality will not be affected, only additional capabilities will be added
    • it’s hard for a novice buyer to select the right solution(s)
      a good provider could recommend that the buying organization engage an external, unbiased, expert for educational purposes before evaluating vendor solutions
    • internationalization — are the right languages supported
      this is tough since no tools allow users to add new languages, but there’s no reason a buying organization could not work with a solution provider to create a new translation if it was needed
    • installed vs. on-demand; supplier-driven vs. buyer driven
      this requires a good understanding of your needs
    • some providers recommend minimum event sizes
      well, this is their problem … if they don’t want your business, what can you do?
    • the provider might not understand the buyer’s business
      the provider simply has to spend some time getting to know the customer

Other points to note are the following statements which are somewhat misleading:

  • the first time you save a lot of money, then returns diminish
    while it is true that the first application on a category will see more substantial returns than subsequent applications, creativity can be used to repeatedly find savings that you might not expect through product substitutions, supplier-defined bundles, and alternative delivery requirements
  • demand collaboration, sales forecasts, and performance management … may be perceived as conflicting with optimization
    while some providers who have these solutions and do not have optimization may position these as “alternatives”, they are not the same thing and they do not conflict with optimization — in fact, they enhance optimization because better forecasts and improved performance give you more reliable data which gives you more reliable models which give you better results

Finally, the chapter summarizes some of the suppliers’ perception of adoption barriers which are worth noting.

  • organizational issues
    • leadership conviction is required for a sale
    • a long term focus is required
    • it’s a hard sell to any organization not already using other e-sourcing tools
    • organizations using other e-tools, including auctions, advanced forecasting, and performance management often see optimization as unnecessary
  • inertia
    • too many organizations are content with costs that are “good enough”
    • others “fear the unknown”
    • optimization is not a well understood term in sourcing
    • there is the fear that optimization can eliminate jobs
  • implementation issues
    • significant resources are often spent on supporting today’s customers, leaving few resources for developing better solutions
    • users rarely have clean data
    • the buyers are not always sophisticated enough to properly structure the problem

In other words, your success is in your hands — you have to see the value, acquire a solution, and get trained if you really want to see optimal results.

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The Role of Optimization in Strategic Sourcing – Optimization and Reverse Auctions

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 benefits of using optimization with reverse auctions are discussed and a number of case studies are presented. Specifically:

  • Fasteners #1
    Before the event, which was conducted as a reverse auction followed by an optimization-based analysis, the suppliers were projecting a 20%+ price increase. After the two-stage event, the end result was an increase of 11%, which was split among one new supplier and two incumbents, while two incumbents lost business.
  • Fasteners #2
    A company decided to centralize its buy across eight business units. A reverse auction followed by optimization-based analysis identified savings of over $80,000.
  • Shelving
    A shelving buy for 35 stores covering 150 items from 10 different sources realized a total savings of 10% when optimization was applied after a reverse auction.

Next, the chapter discussed the challenge of tiered and bundled bids. They are challenging in a number of respects — they are a challenge to define, they can be a challenge to explain, they are often a challenge to “normalize”, and they can be a big challenge to implement for even sophisticated developers — but not as challenging as the report would have you believe. After all, a few providers support both of these bid-types, and at least two do so in their self-service tools.

The statement that only after the model is solved can it be discovered if the business allocated to a supplier would have been sufficient to earn a discount is false! While the specific solution being used, by the company in the example, may not have supported discounts, a number of solutions on the market fully support tiered and volume discounts, which include the type described within the example. These solutions support models which dynamically update the total cost when a threshold is reached. (I have personally designed and implemented two solutions with this capability, one of which is still on the market.)

The one thing that should have been noted, but wasn’t, is that implementing these discounts usually requires a sophisticated set of binary equations. If discounts are required in bulk, the size and complexity of the model will increase significantly and this can negatively impact solve time in a big way.

In addition, not only are tiered and bundled bids the most common form of creative bidding supported by many optimization applications, but they are also the most powerful when combined with discounts and used appropriately.

Finally, there’s no reason that the optimization cannot be applied on-line, in real-time, during the auction. If you’re buying a commodity, or if you can completely specify your business rules and constraints up-front, you can run an optimization-enhanced auction and make (automated) contract offers immediately after the optimization completes. While most providers don’t yet have this capability, Trade Extensions, for example, does. Now, the model has to be of a size and complexity that can be solved in real-time during the auction, but thanks to the advances in processing power and solution algorithms that have materialized over the past five years, you’d be surprised just how big the model can get and still solve in the 15 to 30 minutes typically allocated for a mid-size real-time auction.

Next Part VIII: Challenges / Issues

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