Sales and Operations Planning Part Three: Game Plan Guidelines

Sales and Operations Planning
Part Three: Game Plan Guidelines
Featured Author - Dr. Scott Hamilton - December 13, 2003

Guidelines Concerning S&OP Game Plans

Effective game plans lead to improved firm performance and bottom line results. Metrics include reductions in stock-outs, delivery lead-time, missed shipments, partial shipments, expediting efforts, and improvements in customer service. The lack of effective game plans is typically cited as a leading cause of poor system implementation. The following guidelines provide suggestions for improving the effectiveness of sales and operations planning (S&OP) game plans.

Minimum Planning Horizon for Each Game Plan. A saleable item's cumulative lead-time represents the minimum horizon for a game plan. Additional visibility of six to twelve months is recommended.

Reviewing and Updating Game Plans. The process for reviewing and updating each game plan should be embedded into the firm's regularly scheduled management meetings focusing on demands and supply chain activities. An agreed-upon game plan reflects a balance of conflicting objectives related to various functional areas, such as sales, engineering, manufacturing, purchasing, and accounting.

Primary Responsibility for Maintaining Game Plans. The person(s) acting as a master scheduler maintains the game plans and obtains management agreement. This role typically requires an in-depth understanding of sales and supply chain capabilities, as well as the political power to achieve agreed-upon game plans. The responsibility for providing sales order and forecast data typically belongs to the sales function, with a hand-off to the master scheduler.

Formulating Realistic Game Plans. Realistic game plans require identification of capacity and material exceptions that would constrain the plans, and then eliminating the constraints or changing the plan. Identification of material-related exceptions typically starts with suggested actions on a planning worksheet, while capacity exceptions are identified using work center load analysis. In many cases, a realistic game plan must anticipate demands and demand variations via forecasts and inventory plans for stocked material.

Enforcing Near-Term Schedule Stability. Near-term schedule stability provides one solution for resolving many conflicting objectives, such as improving competitive efficiencies in purchasing and production, and reducing exceptions requiring expediting. It provides a stable target for coordinating supply chain activities and removes most alibis for missed schedules. Near-term schedule stability can benefit from inventory plans and realistic order promises about shipment dates. It involves a basic trade-off with objectives requiring fast response time and frequent schedule changes. The critical issue is that management recognizes the trade-offs to minimize near-term changes.

Making Realistic Sales Order Promises. Realistic delivery promises represent the key link between sales commitments and supply chain activities. Delivery promises can be based on an item's existing inventory and scheduled receipts (via ATP logic), or on lead-times to purchase or manufacture the item (via CTP logic). The critical issue is to reduce and isolate the number of sales order exceptions requiring expediting. One solution approach involves splitting delivery across two sales order line items with different shipment dates.

Maintaining Valid Sales Order Shipment Dates. Sales order shipment dates are used by planning calculations to communicate required supply chain activities. Changes in supply chain activities or demands sometimes require updates to indicate later shipment dates. In particular, past due shipment dates must be updated to reflect a current or future date.

Executing Supply Chain Activities to Plan. Planning calculations make an underlying assumption that everyone works to plan, and the system provides coordination tools to communicate needed action. For example, it is assumed that procurement will ensure timely delivery of purchased material so that manufacturing can meet production schedules. It is assumed distribution will make on-time shipments because sales made valid delivery promises and procurement and production are working to plan. An unmanageable number of exceptions will impact this underlying assumption and the usefulness of coordination tools.

Reducing Exceptions Requiring Expediting. The intent of near-term schedule stability, valid delivery promises and shipment dates, realistic game plans, and executing to plan is to reduce the number of exceptions to a manageable level. This improves the usefulness of coordination tools to meet the game plans.

Business Analytics and S&OP

The S&OP process translates business plans (expressed in dollars) into sales, production, and inventory plans (expressed in units), and requires management information about planned and actual results for each game plan. Business analytics—also termed business intelligence, data warehouses, and executive information systems—are one way to provide this management information in dollars and units. The data reflects summarized information with drill-down for more detail. The results are presented in a variety of formats—ranging from lists and tables to graphs and charts—for financial and operational metrics. For example, the set of sales forecast data provides the basis for planned sales while shipment history defines actual sales. Business analytics can also highlight key performance indicators about operational metrics, such as on-time shipping percentages, production performance (about quality, delivery, and costs) and vendor performance.

This is Part Three of a three-part article reprinted from Managing Your Supply Chain Using Microsoft Navision by Dr. Scott Hamilton.

The book provides a simple yet comprehensive explanation of how to use Microsoft Navision in small-to-midsize firms involved in manufacturing and distribution. Describing usage in a wide variety of environments and illustrated with more than fifty case studies, it covers how the entire system fits together to coordinate supply chain activities within the company and with business partners. It explains the integration with E-commerce capabilities and with relationship management, service management, business analytics, and accounting applications. Written for those individuals that are considering or currently using Microsoft Navision, it enables readers to focus on distribution or manufacturing environments (or both) and on single-site or multisite operations.

For those involved in system selection, the book provides a vision of an integrated system and helps evaluate system fit and needed customizations. For those involved in system implementation, it can help accelerate and broaden the learning process, suggest changes to improve system usage, reduce resistance to change, and reduce implementation costs and time.

This excerpt on "Sales and Operations Planning," one chapter in the book, is presented in three parts. The book can be ordered on amazon.com or books.mcgraw-hill.com.

Case Studies

Case #17: S&OP Simulations. Many firms require simulations to assess the impact of changing demands or supplies. Using multiple sets of forecast data to represent various scenarios and a designated set of forecast data for planning calculation purposes, the management team can analyze the impact of changing demands on material and capacity requirements. The management team can also analyze the impact of using only sales order demand (and ignoring forecasted demand) by not designating a set of forecast data for planning calculation purposes.

Case #18: Common Component Forecast for Process Manufacturing. One product line within a batch process company consists of many end-items built to order from a common manufactured item. The bill of material for each end-item identifies the common manufactured item and packaging components such as labels and bottles. In this case, the S&OP game plans for packaging components are expressed in terms of min-max quantities, while a component forecast drives production of the common manufactured item.

Case #19: Kanban Coordination in Consumer Products Manufacturing. A consumer products company recently implemented a dedicated manufacturing cell for producing one product line. They wanted minimal reporting requirements and automatic generation of Kanban cards to coordinate production activities. Prior to cut-over for production in the new manufacturing cell on July 1, they used component date effectivities in the bills for each affected item to flatten the product structure. Routing information was only defined for the end-items, using a routing revision (with a July 1 start date) that defined run rates in the manufacturing cell. Purchased components were kept in floor stock bin locations with bin replenishment based on projected daily usage rates and a min-max reordering policy. Based on end-item demands and product structure information, planning calculations were customized to calculate projected daily usage rates for components and to generate Kanban cards for end-items and some intermediates. A customization provided an orderless approach to reporting end-item output. Only the item number and a completed quantity were reported, which then triggered auto-deduction of components from the floor stock bin locations.

Case #20: S&OP by Job for Construction Material. A distribution company sold several product lines to the commercial construction industry, where the products also required job-specific installation services. Each job involved multiple phases and tasks (with material and resource requirements) that were closely tied to progress on the construction site. For example, multiple steps were required for plumbing and electrical installation. Using the job functionality within Navision, and customizations to planning calculations and a job schedule board, the time-phased requirements for material and resources were synchronized with scheduled installation dates at the construction sites.

Case #21: Statistical Forecasting. A distribution company used statistical forecasting to calculate future sales demand in monthly increments based on historical data. This required historical data about previous years (prior to cutover to Microsoft Navision). In addition to shipments, the historical data included customer returns, credit memos, and selected inventory adjustments. Further refinements included the requested shipment date (to give a true picture of demand patterns) and information about sales of substitute items. Statistical forecast information was also needed to drive component forecasts for stocked components, where the historical data reflected item ledger entries about usage rather than shipments.

Case #22: Planning Bills for Make-to-Order Equipment. An equipment company wanted to perform sales forecasting using a planning bill that specified mix percentages for equipment options. Building on the standardized functionality for make-to-order manufactured items, they modified planning calculations so that a sales forecast demand blew through the product structure for a make-to-order item and created component forecast demand for stocked components. The planning bill was also used during order entry as the basis for selecting options in a configuration. A further modification ensured the system automatically created an order-dependent bill with the selected options when the user generated production orders from the sales order. This approach resulted in matched sets of components, recognized planned changes in bills and routings, provided visibility of capacity requirements, and simplified the forecasting process (compared to entering individual component forecasts for stocked items).

Case #23: Manual Master Scheduling for Medical Devices. An equipment company produced a line of medical devices that required a manually maintained master schedule to reflect the planner's decision-making logic about production constraints. The medical devices required an expensive outside operation for sterilizing a batch of multiple end-items. The scheduling considerations included a cost-benefit analysis about amortizing the fixed fee for sterilization over the largest possible batch weight subject to a batch weight maximum while still building the product mix for customer demands and avoiding excess inventory. A manual schedule proved most effective for this case.

Case #24: S&OP for a One-Time Product. A fabricated products company often designed and built a one-time product to customer specifications. They used a simulated production order and order-dependent bills to define the product structure and to calculate estimated costs. This information was used to calculate a projected completion date based on forward scheduling logic. After receiving the sales order, this information was used to create a released production order and drive purchasing and production activities.

Executive Summary

The ability to run the company from the top requires a sales and operations planning (S&OP) process that formulates an S&OP game plan for each saleable product. The nature of each game plan depends on several factors such as the visibility of demands, delivery lead-time, and a make-to-stock versus make-to-order production strategy. The starting point for each game plan requires identification of all sources of demand such as sales orders and forecasts, and forecast consumption logic determines how the combination of these demands drive supply chain activities. Several scenarios illustrated how to formulate game plans for a distribution product and three types of manufactured products (make-to-stock, completely make-to-order, and partially make-to-order). Special cases involved a manually maintained master schedule and a partially defined make-to-order product. Guidelines were suggested to improve S&OP game plans, such as how to formulate realistic game plans, enforce near-term schedule stability, and make realistic delivery promises. The case studies highlighted variations in S&OP game plans, such as S&OP simulations, kanban coordination, planning bills, statistical forecasting, and one-time products.

This concludes Part Three of a three-part presentation of the chapter on sales and operations planning.

Part One discussed identifying demands.

Part Two presented game plan guidelines.

About the Author

Dr. Scott Hamilton, as a consultant, developer, user, and researcher, has specialized in information systems for manufacturing and distribution for three decades. Scott has consulted worldwide with over a thousand firms, conducted several hundred executive seminars, and helped design several influential ERP packages. He previously co-authored the APICS CIRM textbook on How Information Systems Impact Organizational Strategy and recently authored Maximizing Your ERP System. Scott is currently working closely with Microsoft partners involved with manufacturing and distribution, and can be reached at ScottHamiltonPhD@aol.com or 612-963-1163.