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Nonquantifiable Data: What Other Factors Need to Be Considered?

Our discussion up to this point has focused on the quantifiable aspects of the network design solution. However, there are other factors that you want to consider when making a final decision. Some of these factors do not lend themselves to being quantified and being considered directly within the optimization runs. This does not mean that our optimization runs are meaningless, nor does it mean that we should just ignore these factors.

It is important to run the optimization with as much quantifiable information as needed. You will want to run a variety of scenarios with different input data. This will then give you a range of potential solutions. From this range, you will then want to apply the consideration of the nonquantifiable aspects. For example, if closing existing facilities and opening new ones in new locations increases your political risk, you want to know whether that new configuration saves you $500,000 or $50 million. You will then be able to judge whether the extra risk is worth it.

We will discuss how you run different scenarios and create a range of possible solutions in future chapters. Some of the nonquantifiable factors you might then want to consider include the following:

  • Firm’s Strategy—Your firm may value cost more than service or vice versa. For example, your firm may have a strategy of servicing the top customers at any expense or be committed to a local manufacturing strategy.
  • Risk—For global supply chains, you need to worry about placing sites in politically unstable locations, port closures, and the added risk of extra distance between origins and destinations. There is also a risk when you have just a single location to make a given product or you have a supply chain that is currently at capacity and is not equipped to handle any unexpected extra demand.
  • Disruption Cost—Firms realize that changes could cause significant disruption, leading to other costs like attrition, lost productivity, and unmet demand.
  • Willingness to Change—Some firms may be more willing to change than others. This can impact the range of solutions you might want to implement. For example, for a firm that is not willing to change, they may be happy to give up savings in exchange for a minimal number of changes.
  • Public Relations and Branding—This is especially important for firms with a highly visible brand. If one of these firms opens or closes a new facility (especially a manufacturing location), it can often make the news. These firms need to consider the public reaction and the impact on their brand.
  • Competitors—A firm’s supply chain can be impacted by the competition. Sometimes it makes sense to be exactly where the competition is, and in other cases it makes sense to be where they are not.
  • Union versus Non-Union—Some firms have strong policies on union affiliation or union contracts and want the locations chosen to reflect that.
  • Tax Rebates—Although taxes can be modeled directly as a cost (as product crosses borders or tax jurisdictions), there can also be rebates for locating a facility in a particular location. This can be hard to quantify during the analysis, but it can be used for negotiating with the local tax authorities.
  • Relationships with Trucking Companies, Warehousing Companies, and Other Supply Chain Partners—You may have supply chain partners (like trucking or warehouse providers) that you will not be able to work with in new locations. There is some value to keeping your existing partner relationships. You will need to consider who your new partners will be in the new configuration, or what you will need to do to get these new partners.

There are many more such factors. What is important to remember is that we are not just pushing the “run” button and coming up with the right answer. We want to run a variety of scenarios and then apply other criteria when finalizing the decision. When we finalize this decision, we can realize exactly how the quantifiable factors (cost and service) are impacted. This can help lead to discussions based on facts, data, and trade-offs (rather than gut-feel, intuition, and emotion).

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