Effective supply chain management demands both efficiency and precision. At Valtitude, we combine SAP Integrated Business Planning (IBP) with a sophisticated segmentation algorithm to classify products and the product-customer matrix. This structured approach enhances both demand modeling and inventory strategies, helping our clients meet market demands while optimizing resources.
Strategic Segmentation for Better Planning
Our proprietary algorithm segments products and product-customer combinations into strategic clusters. This process goes well beyond traditional ABC analysis.
We examine dimensions, including demand volatility, revenue contribution, order frequency, and product lifecycle stage. By doing so, we uncover patterns and group items with similar characteristics, allowing for truly customized planning.
For example, products with steady, high-volume demand are grouped separately from those with sporadic or seasonal demand patterns. These distinctions inform specific forecasting approaches and inventory targets, ensuring ensuring every segment is managed with the most reliable techniques and policies.
In many implementations, the business process blue printing is either poorly done or not done at all. May be it is in the project plan, but this task is marked complete sheerly by a group of tech consultants mapping the old database to the new system or just the same inefficient process into a system. Although we all acknowledge that the business process need to be mapped, re-designed and documented before the system implementation begins, very rarely this is funded by corporate managers as a worthy effort. They like the tool and they want the tool……..
There is also this other possibility that the statistical knowledge is lacking from both the user representation as well as from the consulting resources. For example, I have found many implementation consultants still struggle with questions in implementations:
1. How does one manipulate the trend profiles to adjust trend?
2. What is the difference between using the ex-post forecast vs. Median?
3. Why does a moving average forecast model produces a forecast that rarely moves?
4. How much history should one need to create usable models?
5. When does one use Croston’s models?
and a host of other simple questions that can be resolved with an expert user/consultant that understands the business of demand planning and the math behind the models.
Finally, there are some short comings and challenges with the tool itself, just like any other tool. Consultants and Integrators either do NOT know what these are or just afraid to acknowledge these. It is important to recognize this, so they can help the users navigate around these pitfalls to improve usability of the tool.
Please read http://demandplanning.net/solutions.htm to understand what can be done to improve the tool. Some of the stuff is simple and perhaps will mean consulting costs in the order of 5% of your total budget to implement the tool in the first place.
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