This is the third part of a five part series that revises and ties together key ideas outlined last year on Sourcing Innovation across multiple posts. Regular readers will be familiar with much of the content, but the integrated perspective should help to cement the ideas in regular readers and new readers alike.
This post is largely based on It’s Not Optimization, It’s Strategic Sourcing.
In our last two posts we outlined a complex scenario that could not be accomplished with a traditional sourcing suite that was just a loosely coupled set of modules that did basic sourcing tasks and provided many reasons why the power of the suite did not even come close. Simply put, we have not only reached the point where it is impossible to define a sourcing event of any magnitude without hitting at least a few of the nine dimensions of complexity but we have also reached the point where the data collection, manipulation, and analysis requirements are so intensive that only a sourcing solution built on, and backed by, a true optimization engine is going to be able to handle the data, manipulation, and analysis required.
Now, we’re not saying that the right strategy for every event is optimization, but we are saying, as per SI’s already classic paper on Optimization, What Comes Next, that we have reached the point where you cannot determine the right strategy without optimization to at least build and solve a baseline cost model given current market prices and expected bidder increases or decreases from the last event to determine whether or not optimization might be helpful.
For example, while a 3% savings potential might be enough for a (strategic) sourcing auction or optimization-based multi-round RFX, a 3% drop in expected product cost does not necessarily imply a 3% savings potential. If that drop is from remote suppliers that ship down lanes where costs have risen 10% and shipping is 30% of the overall total cost model, there is likely no savings potential. The right strategy is likely a renegotiation with the incumbent for a contract extension or a spot market buy. Similarly a 2% drop in price combined with a 5% drop in logistics costs could equate to a 3.5% savings potential under the right circumstances, which is substantial on a 50M+ category.
Plus, with bundled discounts, volume discounts from suppliers and carriers that take effect at different price points, different import and utilization costs for each supplier, and an ever increasing plethora of capacity constraints, mandatory award splits to minimize risk, secondary goals of minimal environmental impact, and so on, it’s often impossible to determine what the lowest cost solution is and, thus, if the cost increase associated with assigning a (greater percentage of the) award to a preferred supplier seen as being more valuable in the long term is actually worth it.
In many situations, there’s just no way to do a strategic analysis and justify a strategic decision without a basic level of true mathematical optimization capability that can take all costs and constraints into account. Spreadsheets were breaking under the strain of basic sourcing requirements years ago. Now these sheets are just shards of glass — which will eventually cut you if repeatedly handled.
That’s why you have to not only graduate from a suite to an integrated sourcing platform but, when you do so, select one with integrated optimization capability. While you won’t need to use optimization in every event, you’ll always have the option and always be able to use the advanced mathematical capability to determine both the savings potential and, sometimes, even the odds of success (as you will be able to iterate through dozens of what-if scenarios based upon expected supplier and carrier bids and proposals).
But while we have clarified why traditional suites, built from a set of loosely integrated modules, are not modern sourcing platforms ready for complex sourcing, we have not clarified why many of these suites cannot be upgraded to sourcing platforms. We will address this in our next post.