Archive for July, 2012

Forecasting with JD Edwards

Posted in Uncategorized on July 10, 2012 by johnpaulson1

To remain competitive, businesses must continually look for ways to improve their supply chain effectiveness. One important input to supply chain management is effective forecasting. Being able improve the prediction of demand is critical in today’s businesses. The ability to take this information and effectively manage the supply chain in a timely manner is a key component to remaining competitive.

Forecasting is a primary input of the planning and control systems of a company. The objective of a forecast system is simply to provide timely information to managers that will facilitate in effective decision-making.

Forecast systems come in many shapes, sizes, and calculations. From Excel based spreadsheet systems utilizing simple averaging techniques, to forecasting systems with built-in business intelligence integrating quantitative, qualitative, and technological approach. A forecasting system is a tool used by many functions of an organization including; finance, marketing, inventory management, production, human resources, strategic corporate planning. A transparent, easy to use, real-time, integrated forecast system is important points to look for when choosing a forecasting system.

Since my early days doing corporate forecasting at SpaceLabs, methodical and technological improvements in forecasting systems have certainly come along way expanding the ability of management to effectively use these tools across the organization. Leading forecast systems today are more transparent, user-friendly, and providing timely and effective forecast information required in business decision-making.

The JD Edwards Forecasting system provides ease of use utilizing 12 standard forecasting methods, along with functionality that identifies best fit forecast method based on historical data.  It is not as robust as some of the leading forecasting  packages available, however it does offer some nice features that could be leveraged for your basic forecasting needs.

Some of the features within the JD Edwards system include;

  • Batch process of sales history extract
  • System calculated forecasts utilizing 12 system forecasting methods
  • Ability to make weight adjustments to forecast method calculations.
  • Ability to recommend ‘Best Fit’ forecasting method of the 12 methods
  • Ability to support both manually entered forecasts and forecasts generated by the system.
  • Ability to review and adjust both forecast and actual sales order figures
  • Ability to summarize detailed forecasts by Sales Territory, and by Category Code including; Master Planning Family, Sales Category, and others.
  • Ability to store and display both original and adjusted forecast quantities and amounts.
  • Ability to identify demand patterns.
  • Ability to do simulations.
  • Ability to drive the JD Edwards Manufacturing and Distribution Planning system (MPS/MRP/DRP)
  • Text attachment to summary or detail forecast

The JD Edwards system utilizes the quantitative forecast approach to forecasting, with the ability for system users to adjust forecast based on qualitative information and analysis. Quantitative forecasting techniques have no simple, reliable way to predict what will happen when set patterns or relationships change. Because quantitative methods base their forecasts from history, patterns, and correlations, they work well only when the future ‘actual’s’ is similar to the past. This is where a qualitative approach using human judgement to aid in the forecasting process and adjust accordingly.

JD Edwards Forecasting system identifies a ‘Best Fit’

The system recommends the best fit forecast method by applying the selected forecasting methods to past sales order history and comparing the forecast simulation to the actual history. When you generate a best fit forecast, the system compares actual sales order histories to forecasts for a specific time period and computes how accurately each different forecasting method predicted sales. Then the system recommends the most accurate forecast as the best fit.

JD Edwards Forecasting methods include:

  1. Percentage Over or Under Last Year; useful to forecast demand for seasonal items with growth or decline
  2. Calculated Percentage Over or Under Last Year; useful in budgeting to simulate the effect of a specified growth rate or when sales history has a significant seasonal component
  3. Last Year to This Year; useful to forecast demand for mature products with level demand or seasonal demand without a trend.
  4. Moving Averages; useful to forecast demand for mature products without a trend
  5. Linear Approximation; useful to forecast demand for new products, or products with consistent positive or negative trends that are not due to seasonal fluctuations
  6. Least Square Regression;useful to forecast demand when a linear trend is in the data.
  7. Second Degree Approximation; useful when a product is in the transition between life cycle stages.
  8. Flexible Method – percent Over n Prior Months; similar to Method 1, This method is useful to forecast demand for a planned trend.
  9. Weighted Moving Averages; similar to Method 4, you can assign unequal weights to the historical data when using weighted moving average.
  10. Linear Smoothing; similar to method 9, a formula is assigned to give weights. For short-range forecasts of mature products
  11. Exponential Smoothing; this method is useful to forecast demand when no linear trend is in the data. Exponential smoothing relies on the assumption that the data are stationary.
  12. Exponential Smoothing with Trend and Seasonality; Method 12 uses two Exponential Smoothing equations and one simple average to calculate a smoothed average, a smoothed trend, and a simple average seasonal index.

Forecast Consumption with JD Edwards

I find that the JD Edwards forecast consumption functionality is one of the least understood functions in the planning system. Forecast consumption is simply a method of accounting for sales within a forecast planning period for planning purposes. Sales order demand “consumes” the forecast until eventually the sales order quantity is equal to or greater than the forecast quantity.  At that point, the excess sales order demand would drive requirements planning. Forecast consumption setup is certainly not difficult, however, understanding the mechanics is important for planning and troubleshooting.

Conclusion

In the competitive world of business, the changing  market demands and economical events that may take place, decisions must be made quickly, with greater reliance on real-time quantitative analysis, along with proper qualitative analysis. Understanding your requirements of a forecasting system may be your first logical step to improving your demand planning and the supply chain. With your business requirements identified, assess the functional gap and fit analysis with your existing forecasting system and proceed to develop a road map for improvement.

To learn more about the JD Edwards Forecasting system, functions, features, and  ‘best of breed’ third party forecasting package options that integrate with JD Edwards, contact John Paulson at jpaulson@jderesource.com, or phone John at 503-819-0190.

John Paulson, a JD Edwards manufacturing and distribution consultant and trainer, has been providing supply chain solutions to some of the nations leading companies  for over 15 years.