实例探究 > Procter & Gamble Implements Terra Technology's Demand Sensing for Improved Forecast Accuracy

Procter & Gamble Implements Terra Technology's Demand Sensing for Improved Forecast Accuracy

公司规模
Large Corporate
地区
  • America
  • Europe
  • Asia
国家
  • United States
  • France
  • Germany
  • Switzerland
产品
  • Terra Technology Demand Sensing (DS)
  • SAP APO
  • Terra Technology Multi-Enterprise Demand Sensing (MDS)
技术栈
  • Demand Sensing
  • SAP APO
  • Point-of-Sale (POS) Data Integration
实施规模
  • Enterprise-wide Deployment
影响指标
  • Productivity Improvements
  • Customer Satisfaction
  • Cost Savings
技术
  • 分析与建模 - 预测分析
  • 功能应用 - 企业资源规划系统 (ERP)
  • 分析与建模 - 数据即服务
适用行业
  • 消费品
  • 零售
适用功能
  • 销售与市场营销
用例
  • 需求计划与预测
  • 补货预测
  • 库存管理
  • 供应链可见性(SCV)
服务
  • 系统集成
  • 软件设计与工程服务
  • 数据科学服务
关于客户
Procter & Gamble (P&G) is a global consumer goods company known for its extensive portfolio of brands, including Always, Dash, Dreft, Duracell, Gillette, Head&Shoulders, Pantene, Pampers, Pringles, Swiffer, and Vicks. With approximately 135,000 employees working in over 80 countries, P&G's products touch the lives of people in 180 countries daily. The company's mission is to offer trusted, quality brands designed to improve the lives of consumers worldwide. P&G is committed to innovation and constantly seeks IT tools to enhance its business processes and organization. Terra Technology's Demand Sensing (DS) solution aligns with P&G's mission by providing accurate short-term demand forecasts, helping the company maintain high service levels and improve operational efficiency.
挑战
Procter & Gamble (P&G) faced significant challenges in accurately forecasting short-term demand for their consumer products. Their existing 24-month forecast provided a good overview for monthly or weekly production, but it was insufficient for the immediate needs of supply chain planning and manufacturing teams. These teams required a short-term forecast to plan production effectively and avoid 'fire-fighting' practices. P&G needed a solution that could provide accurate short-term demand forecasts to ensure agility and flexibility in manufacturing, especially for products with very short production and order lead times. The company explored various solutions but found that most big software companies lacked the agility to meet their specific demand sensing needs. Terra Technology's Real-Time Forecasting, later known as Demand Sensing (DS), emerged as a promising solution due to its specialized focus on consumer packaged goods (CPG) demand planning and forecasting.
解决方案
P&G implemented Terra Technology's Demand Sensing (DS) solution to create accurate short-term demand forecasts for finished products. The DS solution uses data from P&G's existing SAP APO system, including daily shipments and open order data, to generate a new forecast every day. This automated process eliminates the need for manual data entry and adjustments, allowing P&G to respond quickly to changes in demand. The pilot project for DS began in July 2005 with hair care products manufactured in France and sold in Germany and Switzerland. By June 2010, DS was used for 90% of P&G's product categories in Western Europe and the Americas. The success of the DS implementation led to the development of Terra Technology's Multi-Enterprise Demand Sensing (MDS) solution, which incorporates additional data sources such as Point-of-Sale (POS) data and retailer forecasts. MDS was first implemented in North America in August 2009 and is being piloted in Western Europe. P&G plans to roll out DS and MDS to Central and Eastern Europe and explore implementation in Asia, despite the region's unique challenges.
运营影响
  • The DS solution has significantly improved forecast accuracy, with a 32% improvement in Western Europe and a 40% improvement in North America.
  • Safety stock levels have been reduced by an average of 10%, minimizing the need for excess inventory.
  • The automated forecasting process has eliminated the need for manual data entry and adjustments, freeing up time for value-added tasks.
  • Collaboration between supply chain and demand planning teams has improved, fostering increased productivity and better business opportunities.
  • The implementation of DS has maintained high service levels without the need for 'fire-fighting' practices, even during periods of fluctuating demand.
数量效益
  • Forecast accuracy improved by 32% in Western Europe.
  • Forecast accuracy improved by 40% in North America.
  • Safety stock levels reduced by 10% on average.

Case Study missing?

Start adding your own!

Register with your work email and create a new case study profile for your business.

Add New Record

相关案例.

联系我们

欢迎与我们交流!
* Required
* Required
* Required
* Invalid email address
提交此表单,即表示您同意 IoT ONE 可以与您联系并分享洞察和营销信息。
不,谢谢,我不想收到来自 IoT ONE 的任何营销电子邮件。
提交

感谢您的信息!
我们会很快与你取得联系。