In a few recent sessions with industry analysts, we were surprised that we were asked if our software is in-memory computing! Given the fact that for over 20 years we designed our applications to have all the data in-memory for computation, our immediate response was: Is there any other way of doing it? The response was, yes, there are others which bring in the data from the database when they need it but now they are changing and they are getting orders of magnitude improvement in speed! This improvement in speed must have caught the attention of the analysts which brings us to the core subject of this article. There is more to speed of application than just having all the data in memory. The latter is the easy part. There are also some vendors, try to improve speed by abstraction and over-simplification. I am sure you are aware of quite few who deploy “Spread-sheet” type of capacity planning in their S&OP applications. That is forming weekly or monthly buckets with fixed lead-times! This approach typically either dumbs down how to deal with capacity, or ignores it altogether. It is the old method, with NO notion of product mix and real processing time, that has been around for decades but with a new user interface which makes it slightly more attractive. Therefore, any gain in speed is offset by a very inaccurate and unrealistic plan. In addition, it has no order level information OR any order level pegging functionality. You might as well use your spreadsheets since they give you even more control!
To gain real improvement in speed with proper representation of capacity of resources and equipment, deep modeling capability is needed and the mix of products must be taken into account. In addition, to IMC, one needs to have data representations and algorithms that provide real-time answers to very complex supply chains at order level. As an example, if one material is not available, does the system go back to search all over again for a new method of making or will it just backtrack one step to find an immediate substitute pegged to that order? If a resource is a bottleneck, will it look for a whole new routing or will it look for an alternative, process or equipment. How this data is represented and how the algorithms divide and conquer in parallel processing is what makes the application fast. Just using IMC is only the beginning, there is a lot more that goes into a comprehensive planning system that can analyze tens of millions of data points from material availability to resources and tools and skill levels, to say a few, in almost real-time.