本文是《 SAP IBP-第1篇-概述》一文关于Demand Planning模块的展开。其中Demand Sensing处理Demand Planning中的短期计划。前面章节提到的销售预测过程使用Statistical Forecasting实现了到月和周的中长期计划,而…
SAP的IBP Demand提供完整的需求感知Demand Sensing能力,同时“热数据”的源头也可以很多元,例如可以有ERP中的销售模块的订单/发货,还可以有来自于CRM中的商机/订单,甚至还可以来自于实时的POS交易数据,而这些系统间的连接与集成,IBP也都提供有相应的标准服务。 同时在配置及应用上,也是以尽量简洁的方式来进行,例如配...
经过本文和《SAP IBP-第3篇-Demand Planning(1数据清洗)》一文对Demand Planning的整体流程进行了阐述。上述的Planning View在不同的企业中都可以更具其业务的差异进行定制调整。后续的文章将阐述Demand Planning模块的最后一块内容——Demand Sensing。 ---作者阿来(WX: AlaiYC)/转载请注明出处--- 欢迎关注公众号...
SAP IBP是一款帮助企业去真正打造端到端(从需求端到供应端,从战略层到运营层)供应链计划体系的统一的计划平台,是希望赋能给客户这样的能力:虽然各个模块可以按企业所需解耦部署,但通过逐步建设最终能够将企业计划域里所涵盖的各种计划都有一个统一的集中的数据“前、中、后”平台进行集成同时进行协同。
Learn how to optimize short-term planning with Demand Sensing using SAP IBP. Many organizations, even with the best demand planning at macro level, lack the ability to respond to changing demand at operational level. Demand Sensing helps bridge the gap. It is an innovative approach where a ran...
Model Errors defined in IBP DP Definition of WMAPE, MAD, MASE, MPE, MAPE and RMSE Model Diagnostics through Forecast Error Additional Considerations Introduction to Demand Sensing Introduction to Promotion Planning Summary and Conclusion: What's next? For SAP and for your Organization!
Plan KPI进行预测准确度的检验，展示Corrected History与Published Consensus DP之间的比较。以上步骤涵盖了从基本预测到最终准确度检验的全过程，具体操作可在SAP IBP中实现。各企业可根据业务需求调整Planning View，以满足特定业务流程。后续文章将探讨Demand Planning模块的最后一部分——Demand Sensing。
We explain in detail how demand sensing helps addressing variability dampening, working capital reduction, lead time compression or introduction of late customization and illustrate the concept with the use of SAP IBP use cases.doi:10.1007/978-3-030-05381-9_7Ganesh Sankaran...
SAP Managed Tags: SAP Integrated Business Planning Hello All, I know little about Lag MDT which used for lag information within Demand sensing. Could you please explain with example? Thanks, Pravin TikarKnow the answer? Help others by sharing your knowledge. Answer Need more details? Request ...
Big remote sensing image data are collected from multiple platforms in the Arctic region on a daily basis, which poses a serious challenge of discovering the spatiotemporal patterns from this big data in a timely manner [7]. This demand is driving the development of data CI, data mining, ...