As an Automotive presales professional with SAP, it’s my privilege to work with some of the world’s leading automotive companies – OEM’s and Suppliers – to extend the processes enabled by SAP. One topic that has been a consistent topic of interest, but only recently one with a clear path to resolution, is the ability to test production plans against known supplier capabilities. There are two key drivers for this requirement: planning for the impact of greater than expected attach rates for certain optional components, and the immediate need to deal with catastrophic interruptions in the supply chain. Our industry in recent years have seen examples of both.
There is general acknowledgement of the value of enabling proactive assessment of production versus supply, and a variety of approaches have been tested over time. As a result, several key learnings have emerged. The most important is to enable this process in a flexible, may I repeat, flexible, environment that does not force either utilization of the entire product structure or limit exploration to a very few pre-selected constraints.
Why? It’s simple… first, the complexity of most manufactured goods in the automotive industry precludes solving a production plan while testing capacity for all components, even with new tools such as SAP Hana. Second, this just creates noise, as most components will not pose a challenge. Third, outside of evaluating against contractual volume commitments it’s problematic to collaborate with an entire supply base to ensure accurate capabilities. The magic is to focus on the critical few.
That’s where “Flexibility” comes in – it’s not always clear up front what the critical few will be. Thus, in addition to up front modeling of known constraints, an effective solution must also be correlated to Demand Signal Management or Sales and Operations Planning to identify trends in option penetration in time to add potential constraints to the model (and engage Suppliers to ensure accurate capacity information). This addresses the first business challenge noted above. But a flexible process is even more important in the second scenario, a catastrophic interruption in supply.
Often, catastrophic events impact product well down the supply chain. Who knew how critical one specific resin was until the only plant producing it was shut down? To address this, a solution must enable a level of abstraction that is not based on a traditional product structure relationship, but instead enables application of a new constraint to a broad range of end items, perhaps even skipping intervening levels. This is not dissimilar to the process of rough cut capacity planning, but ideally is connected to a process that can not only identify impacts but provide guidance in re-prioritizing production in the short term.
So we see two different business challenges, both important, and both addressed by a robust process for modeling production, distribution, and capacity constraints on a regular basis to address trends, and adapted on an emergency basis to mitigate the impact of short term disruptions.
Comments, fellow community members?
