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Oracle Forecasting explained
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Your first question may be “What is Forecast Consumption?” And I’d say, “It’s a tool that’s been around for a while
but gets little airplay with all the other cool features ASCP offers.” Properly configured and managed, it can help
Sales and Operations work together in a manufacturing organization. Simply put, Forecast Consumption helps keep
your Demand drivers “real,” giving you a better chance of shipping on time. Plus, you can export data from Oracle
and measure Item Forecast Accuracy based on user-defined formulas. Read on to learn how to capitalize on the
power of Forecast Consumption functionality.
Posted on November 6, 2014 by Stephen Bernard
In a perfect world, we would use Forecast Consumption functionality to reduce the current quantity of a forecast entry
when we created a sales order due on the same day. This would prevent the sales order and forecast demand from
“double driving” the Planning engine for the same requirement. Forecast Consumption has been around since Oracle
Planning (MRP). So, when we mention the “Planning Engine,” it could be MRP, SCP (unconstrained multi-org), or
ASCP.
Many companies don’t forecast for a variety of reasons. So, they might not have even been aware of Forecast
Consumption. As time marches on, some of these companies decide to start forecasting and ponder, “Where do we
start?”
First, businesses should consider these frequently asked questions:
What parts do we want to forecast? Why?
How far in the future do we want to forecast?
Should we have optimistic, neutral, and/or pessimistic forecasts?
How would we manage multiple forecasts?
How do we reach consensus between Operations and Sales? (Ex: when the operations folks are a wee bit wary
of forecasts created by the sales team).
How do we control Forecast Consumption so that forecasts and sales orders don’t double drive demand from the
same requirement?
Forecast Consumption’s basic setup is simple and flexible:
Set profile: MRP: Consume Forecast to “Yes” site level.
For the parts you want to forecast at the org level, set the item attribute “Forecast Control” to “Consume” or
“Consume and Derive.”
o “Consume” is used when you are forecasting that item directly.
o “Consume and Derive” allows you to forecast the part directly or have the demand “derived” from a Planning
Bill of Material explosion.
The Planning Manager runs Forecast Consumption.
This manager is very stable. Start it up, and it will continue running.
Define your Forecast Sets.
OK, what is a Forecast Set? It’s an arbitrary grouping of your demand based on how YOU want to express it. You can
have as many sets as you want, but then you run the risk of duplicating the same demand stream in another set.
Separating by Product Line or Geography are two popular schemes. Suggestion: Start simple (maybe with just one
Forecast Set).
Strategy: Bucket types are Days, Weeks, or Periods.
“Days” are usually too specific for most companies. “Weeks” tend to be the best choice from a Material Planning
perspective. The wider window reduces manual cleanup significantly yet is not too wide from a Forecast Accuracy
measurement perspective. Periods are usually too wide from a Material Planning perspective, however, they are
often used by Marketing and Finance at a later stage of planning.
Check “Consume” to activate consumption for all items in the Forecast Set.
Check “Advanced Planning Collections” to collect this Forecast Set for ASCP.
The Backward and Forward Days parameters allow you to create a custom window of consumable days based on the
Scheduled Ship Date. Each sales order line item counts back in working days based on the Backward Consumption
Value. Many customers with a standard Monday-Friday workday calendar use weekly buckets and the values BCD=3
and FCD=3. Count back three work days from Wednesday, and you’re in the previous weekly bucket on Friday.
Count forward three work days from Wednesday, and you’re in the next weekly bucket on a Friday. This yields at
least two weeks of consumption potential. If the sales order line item falls on a Wednesday, then you have a three-
week consumption window.
A large company was training its sales people on this functionality. Their forecast accuracy in the consumption
window was going to be measured for the first time, and their bonuses would be based on their accuracy. They paid
rapt attention and encouraged their customers to book orders for Wednesday deliveries. Now, that’s motivation!!
Next step: Click on the “Forecast Items” button and set up your four-step hierarchy.
Forecast Set: The “container” for one or more forecasts.
Forecast(s): One or more defined forecast(s)
Item(s): The Item(s) to be forecasted.
Detail: The dates and quantities for each item.
That’s it! This forecast is defined.
You can have multiple forecasts in one Forecast Set. For example, if your grouping scheme is Geography, you might
have three forecasts for US Sales: East, Central, and West. The same items might be forecasted for different
quantities in each of the three sales regions. How you organize your forecasting world is entirely up to you. One
suggestion is to enter the grouping scheme you’re using in the Forecast Description field (e.g., East US Sales).
Guess what? A customer has ordered some of your items!
When a Sales Order is Booked, the line items are Scheduled and the Planning Manager runs the Forecast
Consumption process.
So how do you measure Forecast Accuracy?
There is no defined process since every company does it differently, if at all. However, Oracle automatically captures
the data. You can export that view to Excel and then, from there, define your custom accuracy formulas.
Data are captured in the following format: Material Planning > Inquiry > Forecast > View Sets
Select the Forecast Set name with NO Forecast name next to it. This is required because the Forecast Set captures
all Overconsumption information. At the forecast level, you would see the entire forecast entry consumed, but you
would not see the overconsumption information (i.e., you sold more than you expected).
Overconsumption entries are easy to spot because they are marked as a negative value.
Click on the Overconsumption line and click the “Consumptions” button to view details.
Close the “Forecast Consumptions” window and click on the “Bucketed” button.
Your Bucketed view is displayed.
This is the view that can be exported to Excel (File>Export) if you wish to measure Item Forecast Accuracy using
custom formulas.
This view can be bucketed in Days, Weeks, or Periods and displayed in Dollars or Units. The bottom three columns
represent data within the defined date range. Change the date range and the Cumulative columns recalculate. Notice
some columns have TWO headings for the same date. One is for “normal” consumption; a second column is added if
there is Overconsumption.
This view is also handy for a quick item review. In the near term, “Cum Current” should be at or near zero. This
means that the cumulative quantity forecasted in the date range up to the point you are viewing is being sold
(consumed). If “Cum Current” is high in the near term, your forecast is too high. If “Cum Current” is zero and you have
Overconsumption (selling more than expected), your forecast is too low.
Note: If you have Oracle’s Demand Planning or Demantra applications, you can execute Forecast Consumption
during the ASCP plan run using ASCP Plan options. Also, you can define worksheets to calculate Forecast Accuracy.
Demantra offers predefined worksheets.
Final thoughts on forecasting with Forecast Set functionality:
Start simple (with just one Forecast Set). Add complexity only if you really need it.
Like any other setup, MAINTAIN the data over time.
Planning and Sales folks can actually work together!
Marketing and Finance might use this data in the future, for planning and budgeting purposes.
Happy Forecasting!!
