26 Jan Face Off: IBP S&OP vs. APO Demand Planning, Part I
With all the market hoopla surrounding Integrated Business Planning (IBP) S&OP, I felt it necessary, as we were conducting our internal training on S&OP, to contrast the similarities and differences between IBP S&OP and APO Demand Planning. These two softwares provide similar process benefits around the sales and operations planning and demand planning processes in your business. Here’s how they compare.
Round 1: Forecasting:
IBP: Provides bare bones statistical forecast capability that will be sufficient for companies that are on the lower end of the sophistication scale from a forecast algorithm perspective. This limited offering will likely grow as the IBP product matures, but for now, it is focused on simplistic forecast generation.
DP: This is the process that DP was built to support. It’s able to support fairly complex forecasting algorithms while providing a user cockpit that supports forecast changes at any level (when configured properly). DP is definitely the winner of this category if your company utilizes complex statistical forecasting methods.
DP is the all-around winner of this category, but if your company does not need complex statistical algorithms (or doesn’t have anyone to manage them), then either will do.
Round 2: Disaggregation:
IBP: IBP allows for each Key Figure to have its own characteristic level at which its data is loaded, stored, and potentially utilized (termed a base planning level). And all macros must originate at this level for calculations. It is this flexibility that allows IBP to be able to run calculations at multiple aggregation levels so quickly. Essentially, the system is performing “linear” disaggregation from the user’s access level to this base planning level and back (similar to an APO DP drill down).
DP: DP uses the traditional CVC (characteristic value combination) approach to disaggregation, forcing the data to be saved at the lowest aggregation level and then using configuration rules to determine how aggregation/disaggregation to other levels is to be handled. This works fine for many situations, but tends to be a bit of an issue when performing complex currency-based data.
IBP wins this round with the ability to store and calculate each key figure at its own level.
Round 3: Data Model:
IBP: What SAP means by “unified data model” is that the forecasting, supply, and financial models are all saved to the same database set, not stored separately and then copied or released from one data model to another. This allows IBP to quickly provide calculated reporting across these three business models in real time, including the ramifications of changes in one model to the results in a different model (e.g. how will a forecast change affect the profitability of the company). This is where the real value of IBP starts to make itself known, allowing for on-the-fly changes and questions in an S&OP meeting that can be answered IN THAT MEETING and not offline at a later time.
DP: APO DP has traditionally “released” the forecast to either SNP or directly to ECC. While this allows for the forecaster to model different scenarios and then “publish” the results when they are optimal, this also prohibits the real time updates to the supply plan and capacity feedback that are vital to being able to provide a nimble SOP process.
IBP wins this category, hands down, by being able to provide real time results of one model, based on changes in any of the other models.