Today, Spend Matters would like to welcome Dr. Jason Brown. Dr. Brown, a former CTO at CombineNet, will be contributing his thoughts on Spend Matters about how practitioners can best apply optimization to their overall sourcing practices.
Before getting into the nuances of how best "to-do" sourcing optimization and the specific cases where it makes the most sense to apply it, I'd like to first begin by asking the question: why do we need sourcing optimization?
I have heard this question raised many times during conversations with potential clients and partners in the past. Optimization is a confusing word, as it means different things to different people. Most people think that they think they need optimization when they have something "complex," but then how do we define complex? Sourcing optimization is applicable to all spends regardless of complexity.
Optimization in its most basic form means to find a solution to a problem that maximizes (or minimizes) some objective function. However, it is usually not that easy when applied to supply chain problems, as the objective function usually involves internal and external costs and typically needs to adhere to a myriad of business rules (or constraints).
For example, you want to minimize the total cost of sale including transition costs, but you need to use a certain set of suppliers using a specified set of raw materials, or can only produce certain goods at certain locations. Additionally, your company may have corporate policies that dictate that the sourcing of goods that need a certain "green score," to provide a certain amount of business to MWBE, and to honor existing contracts. All of these things regardless of the size and complexity of a sourcing event are excellent candidates for sourcing using optimization.
It is important to understand that optimization engines simply find an optimal answer to the problem. For example, in the sinusoid, there are an infinite number of solutions that maximize the sine function. An optimization engine will simply give you the first of the solutions that it comes to (the problem of finding how many optimal solutions are out there is a completely different type of problem to solve). What you are guaranteed is that the returned solution is one that maximizes (or minimizes) your objective.
This is where the human element comes in. It's then the job of the analyst to look at the solution and determine what they like and do not like about it, add in more constraints, and look at the new optimal answer. For example, consider a supply scenario. If there are too many suppliers, set a limit for each item in a particular set. Given this requirement, it's important to make sure that the optimization supported in your sourcing application lets you enter as many constraints (business rules) as you need, since you never actually know until you look at the solutions.
With all that said on optimization, when it comes to strategic sourcing, there are a few reasons why professionals traditionally look to use optimization:
- Analysis time savings
- Negotiation and contracting time savings
- Money savings
- Investigation of future opportunities
Check back soon as we examine these reasons in more detail and look at applying sourcing optimization to common challenges!
-- Jason Brown