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Over the last several years, the pace of business has increased dramatically, forcing supply chain professionals to work harder than ever to effectively manage their daily operations. Fluctuating customer demand, unexpected resource constraints and increased management pressure have made the job of creating an optimized and profitable supply chain operating plan very difficult.

In order to survive in this chaotic environment, supply chain professionals must have accurate, up-to-date information that displays both historical performance as well as future direction. And while this information can be obtained through conventional reports and dashboard displays, it is often not enough to simply have a static summary of the data. Analysis of the data shown in these forms inevitably leads to questions and the need to drill down for more information. Several technologies do exists that offer such capabilities in limited form, however they consistently fall short of the ideal goal, which is to follow along with the thought process and decision flow of the individuals or group analyzing the data.

Supply chain professionals need accurate, up-to-date information about their supply chain performance and plan, and the ability to drill down through the data to find the answers that support their decision making processes. They need quick, nimble, flexible, customizable data analyses solutions that they can control – without the need to burden their IT departments.

WAM’s Predictive Analytics was created for exactly this purpose – to deliver robust data analysis and mining into the hands of the business professionals where it is needed most.


WAM’s Predictive Analytics is a solution that allows users to mine their supply chain operating data and quickly establish advanced interactive reports that help monitor and alert users to outliers, urgent issues and opportunities. By using a simple web-based user interface, the user can select key data elements to track and include in scoping and filtering schemes which support trend analysis, regression analysis and spot reporting. This simple, easy to install solution connects to your WAM supply chain data and provides an intuitive platform within which you can navigate all of your historical, current and future supply chain data.

Delivered with our pre-defined suite of supply chain views, WAM's Predictive Analytics allows you to get started right out of the gate by navigating through function-specific charts that display the critical information needed to understand and evaluate your company’s performance. Once up to speed with the technology you can begin to create your own displays that instantly adopt the point and click drill down capabilities and extend your data mining in any direction.

The immediate response of your interaction supports real-time analysis and decision making. This results in a tool that is ideal for group meetings such as your Sales and Operations Planning (S&OP) meeting where specific questions about the data can be explored as you collectively review the displays.

Selected Highlights Analysis of WAM's Supply Chain data, including all inventory projections and forecast data Gain a quick overview of KPI performance to targets Identify trends in KPIs Look for relationships between KPIs Drill from top-level KPIs to transactional data Slice, dice, sort, filter – all in real-time Analyze data across different time periods and levels Create unlimited user-defined custom analyses without burdening your IT organization Export your results to spreadsheet programs Support executive review of supply chain performance

Supply Chain Professionals Use WAM Predictive Analytics to: Examine your current supply chain performance against targets across your entire organization and/or at any one specific location Drill down by market, product line / grade, product family, location, package, SKU, region, season, year / month / day, production asset, HR asset, order / order type, order, requested date / ship date -- any key KPI to your organization Compare forecast against plan Examine production utilization Review profitability of product lines Review the performance of product lines Expose forecast bias by sales Review overforecast and underforecast trends Identify outliers in your forecast vs. volume comparison – large volume, high error problems Examine order fill rates / customer service levels for any product or region Identify problematic spikes in inventory levels Compare legacy product lines against new product lines – accuracy of forecasting or profitability Evaluate your forecast error against inventory levels Determine the costs of the volatility in your inventory holdings