fully integrated ax module demand forecasts sales orders transfer orders purchase orders production...
Post on 17-Jan-2016
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Fully integrated AX module
Demandforecasts
Sales orders
Transferorders
Purchaseorders
Productionorders
Master Planning
DemandForecasting
Let’s look at an example
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Demand History
Let’s look at an example
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Demand History & ForecastDemand HistoryForecast
Now let’s compare the results
Forecasting No Forecasting
Average Forecast Error % 35% -
Now let’s compare the results
Forecasting No Forecasting
Average Forecast Error % 35% -
Average Safety Stock 144 144
Average Stock Level 261 295
These results compare the replenishment of stocks over an 18 month period for the item on the previous screen, assuming a 3 month replenishment lead time and a safety stock factor of 1.65 (95% service level)
Now let’s compare the results
Forecasting No Forecasting
Average Forecast Error % 35% -
Average Safety Stock 144 144
Average Stock Level 261 295
Service Level % 100.0% 98.5%
Now let’s compare the results
Forecasting No Forecasting
Average Forecast Error % 35% -
Average Safety Stock 144 144
Average Stock Level 261 295
Service Level % 100.0% 98.5%
If Safety Stocks are calculated based on forecast accuracy, not demand variability, even greater savings can be achieved. In this case a 17% reduction in average stock levels are produced, while still achieving a 100% service level
Major Points
• Safety stocks should be calculated, not guessed- It’s easy to inflate safety stocks to achieve service levels, but there’s a cost
• Lead times are a major factor- Reducing lead times reduces risk of stock-outs (and reliance on forecast
accuracy)
• Forecasting can be simple- Your existing customers have the data already- It can be implemented quickly & easily
The Forecasting Cycle
Generate demand history
Generate base forecast
Copy to final forecast
Generate forecast
allocations
Review forecasts
Final forecasts may contain additionalitemdimensions(depends on each item’s coveragerequirements)
Demand history is consolidated by SKU, customer groups & forecast periods. A SKU contains all item dimensions from demand transactions
Forecasts only contain the item dimensions specified in each item’s Input Dimension Group
Allocations are used to distribute final forecasts over additional item dimensions (if required)
Sales orders or sales invoices
Project item trans-actions
Inventory BOM Jnl lines, Production BOM lines
Key features
• Forecasts can be calculated automatically or entered manually
• Forecasts can be changed by quantity and/or value and at multiple levels
• Graphical view for comparison of forecasts and demand history
• Adjust forecasts either online, or offline using Excel
• Review forecasts within companies, or summarized over multiple companies
• Built within Dynamics AX – no interfacing required!
Demand Forecasting R6.0
• Flexible selection of transactions when generating demand history
• Multi-level forecasting review
• Forecasts can now be reviewed/changed by value
• Regenerate forecasts for selected item groups only
• Generate forecasts from any date in the past
• Weekly periods can now start on the same weekday
• User-defined number of periods for calculating average sales price
• Improvements to Item Supersessions
Item Supersessions
Demand history for a new item can now be built before the Supersession End Date, and forecasts can be delayed to start at a later date
Start Date
End Date
Forecast Start
Demand copy
New item demand
Old item demand
New item forecast
Demand Forecasting R6.0
• Forecast Model Copy (easy snapshotting of forecasts)
• New Forecast Allocations replace use of Item Allocations Keys
• Allocations corrected for different units of measure
• Budget periods fixed (based on budget copy date)
• Average sales price now calculated using only demand history records with the same item dimensions as the forecasts
• Forecast Groups no longer attached directly to customers (removal of mods to standard AX tables)
Items are grouped for ease of maintenance
Customers are grouped to consolidate demand and improve forecast accuracy
Forecast at any dimension level
Collaborative Forecasting
• Forecast Sales Groups specify who manages forecasts for each customer
• Forecasts can be adjusted online, or offline using Excel
Abnormal Demand
• Ability to flag abnormal demand– For example an abnormally large order is received from a
customer to stock stores for a sale– You want to adjust the demand history to prevent future
forecasts being inflated– Manual adjustments are always held separately from
actual demand history
Promotions
• Ability to enter the likely impact of promotions for forward planning
• A promotion may drive up sales in a period, but reduce sales in a subsequent period
Item Supersessions
• New product– Automatically copy history from a similar or superseded
item
• Old product– Manually determine when the
run-out should occur– Disable item from being forecast– Copy history to a new item
Forecasting Formulae
• Same as last year’s demand +/- n%• n-month moving average• n-month moving average with trend• Average of same months last 2 years• ‘Best fit’ formula selection using advanced
forecasting algorithms
Advanced Forecasting Formulae
• Simple Moving Averages• Discrete Data Models• Croston’s Intermittent Demand Model• 9 Exponential Smoothing Models• Univariate Box-Jenkins Model• Event Models• 4 Curve Fitting Models• Dynamic Multiple Regression
Other Features
• Forecast periods– Forecasts are calculated by week, month or user-definable periods– Monthly forecasts can be automatically split into weekly forecasts (or
even further if required) using period keys
• Forecast accuracy– Multiple forecast models enable a forecast to be frozen and compared
to actual demand over the forecast period
• Fully multi-lingual capable– English language labels are shipped with the product– Other language labels to be developed by resellers
Demand Forecasting Roadmap
• Additional item group
• Multi-level forecast generation
• Automatic detection of demand history ‘outliers’
• Improved forecast exception tracking
• Safety stock calculations
• User-definable forecasting formulas
• Extensions to notes to allow for changes at multiple levels
• Audit recording of changes and who made them
Demand Forecasting R6.1
• Ability to select individual Forecast Pro formulas
• Automatic detection of demand history ‘outliers’
• Improved forecast exception tracking
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