In addition to the data already obtained on the platform following the calculation of your forecasts, you have the possibility to upload external forecasts from another source. This allows you to
Compare them to the forecasts generated by the platform
(ex: forecasts provided by a sales department to challenge them or forecasts from customers).Use your forecasts as a baseline forecast on the platform
(using a forecasting model specific to your dataset, for example, based on a machine-learning algorithm).Automatically upload them into the forecast adjustments in order to directly obtain the comparison KPIs for each new cycle (notably the forecast value-added FVA).
At this point, you have already uploaded demand data to the platform. Then you will proceed with the following steps
Option 1: Comparison with forecasts generated by SKU Science.
Uploading the external forecast file
To add your file, click on the gear
icon at the top right section of the tool and select Data upload Wizard
.
Then click on the Upload forecasts
button.
Select your file and the tab corresponding to your forecast in the file.
Check the file format
Similarly to uploading historical demand data, the platform analyzes your file to identify the dates. Here, our header contains a "Part number" and "Location" column and the rest of the columns contain the dates of the forecasts starting in May.
As with previous uploads, please ensure that the date and number formats are properly recognized. We recommend that you use the same formats as the previous uploads.
At this stage, the platform should map your fields automatically if you use the same labels as in previous uploads.
Here we use the "Part number" field and the "Location" field because it is the granularity level of the forecasts defined on the platform. If you create your forecasts at the "Article " or " Part number " level, you can provide only one column for the mapping.
If it is not the case, correct the mapping manually.
Check the summary before confirming
The platform proposes a summary before confirming the file upload.
Note that there is a checkbox that we will use later for option 3.
After confirming, the platform loads the file and organizes data in the external forecast fields available for each combination of "Item" "Location" on the platform.
Once the upload is complete, click on the Navigator
tab and select the eye icon to select the first item.
View your external forecasts
Once you reach the selected forecast, click on the +
in the graphic part of the screen to add a new curve, and select External
.
Now you can see your external forecast represented by the green line.
Option 2: Use your external forecast as a baseline forecast
After proceeding similarly to option 1 and you can visualize your external forecasts on the platform, you can now replace the SKU Science forecasts.
Select Forecast computation
(the calculator icon).
A new window pops-up
In the Forecast for all SKUs
drop-down menu, select Externa
l
and then click on Confirm & Launch
.
The platform will then replace all previous baseline forecasts with the external forecasts from your file.
Visualize your forecasts
Now you can view your external forecasts in the forecast table instead of the platform forecasts, as well as graphically. You can see that the red (consensus) and green (external) curves are now stacked.
If you wish to return to the platform forecast, simply select SKU Science
for the forecast calculation instead of External
in the menu previously used. Be sure not to view the data in an aggregated format, in which case you will see a different selection window.
Option 3: Upload your external forecasts directly into the forecast adjustments
After proceeding as in option 1, before confirming your upload, check the box Copy to forecast adjustments
.
Visualize your forecasts
At the end of the upload, you can visualize your external forecasts in the forecast table but located in the Forecast adjustments
line this time, as well as graphically. You can see that the red (consensus) and green (external) curves are now stacked.
During the next forecast cycle and after a new demand data period is uploaded, the forecast will be automatically archived. You will then directly get the calculation of the forecast value added (FVA) in the KPI table.
This will allow you to compare at a glance the difference between the user forecast (external) and the one calculated by the platform.
Do not hesitate to contact us to ask your questions directly in the interface of the tool, using the messenger at the bottom right of the screen.