Using QAD’s MFG/PRO for Annual Planning and Budget Formulation

Posted on: September 2, 2008 | By: SuperUser Account | QAD Financials

The obvious key to this process is to establish a solid sales budget. Over the years, companies using MFG/PRO as their ERP system have created a wealth of sales analysis data. The process of posting invoices in MFG/PRO creates both detailed invoice history and sales analysis data. The sales analysis data created includes items, product lines, customer, sales volume by month, sales dollars by month and average margin by month.
The Forecasting Module in MFG/PRO can greatly assist your company in developing a sales volume forecast. In the forecast simulation module, QAD has provided you with standard algorithms. These algorithms will leverage the historical data to create forecast simulations. QAD defines the list below:
· Method 01 – Best Fit (default) This uses all predefined methods (02-06) and selects the results with the least Mean Absolute Deviation.
· Method 02 – Double Moving Average This method is the simplest of forecasting techniques. It uses a set of simple moving averages based on historical data and then computes another set of moving averages based on the first set. The moving averages are based on four months of data. This method produces a forecast that lags behind trends effects.
· Method 03 – Double Exponential Smoothing This method is the most popular of forecast techniques. It is similar to the Double Moving Average with the addition that it weights the most recent sales data more heavily than the older sales data. This method produces forecast that lags behind trends effects.
· Method 04 – Winter’s Linear Exponential Smoothing This methods produces results similar to Double Exponential Smoothing. It has the extra advantage of incorporating a seasonal/trend adjustment factor. This method can be used to forecast based on sales history that contains both trends and seasonal patterns.
· Method 05 – Classic Decomposition This method recognizes three separate portions of underlying patterns within sales history: the trend factor, a seasonal factor, and a cyclical factor. The trend is assumed to be a straight line that eliminates all random fluctuations due to seasonal and cyclical factors. The seasonal factor relates to the annual fluctuations in sales. The cyclical factor follows the pattern of a wave oscillating between high and low sales values. The cyclical factor spans a period of time longer than one year. Classic Decomposition is usually the preferred method to forecast seasonal, high- cost items.
· Method 06 – Simple Regression This is also called the least squared method. It analyzes the relationship between the objects (sales) and time span (month). It ensures that the forecasted quantity is equally likely to be higher or lower than the quantity actually sold.
Ultimately, you need to run the analysis to understand what method best reflects your business. Recognize this data is based on history; therefore, any new items and product lines will need to be considered outside of this analysis. Logan has developed a User Forecast Simulation load tool to assist your Financial Analyst in combining the new item forecast with the simulation based on history. The forecast simulation is bucketed into giving you a starting point for your annual budget.
Vet the sales volume and the sales dollars (based on next year’s pricing) with the Organization including Sales & Marketing, Finance Planning and Analysis and your Supply Chain organization.

For more information regarding this Blog, feel free to contact me at avitullo@logan-consulting.com

Andy Vitullo
Principal, Logan Consulting

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