Editing Product Detail
It is possible to edit all the data that are in green cells. If the data cell is not green, it is not editable.
Confidence factor, as well as other item settings, can be edited within the Forecast Settings. Confidence factor is the service level required on the product, the higher the level the greater the availability of stock. It is a good practice to categorise products according to their importance, i.e. A, B or C products according to traditional ABC Pareto Analysis, where ideally 20% of your SKU’s are classified as A items and represent 80% of the earning and determine the optimal confidence factor for each category. Note that the confidence factor should reflect the importance of the product.
It can vary between industries what is the appropriate confidence factor. Below are some suggestion meant as guidelines:
- Confidence factor = 99.9999. This is the highest factor, resulting in almost no chance of stock out.
- Confidence factor = 90. This should be enough for all products that require a high safety stock, but in extreme cases there might be stock out situations.
- Confidence factor = 65. This can be suitable for C products (from ABC analysis) if we want some safety stock, but it is acceptable to get stock outs when sales volume is higher than expected.
- Confidence factor = 50. No safety stock is added on top of the forecast.
- Confidence factor = 0. No forecast will be created (zero forecast). The product will only include quantity in an order proposal if there is some quantity reserved (pending orders).
Editing Historical Data
The sales forecast is based on historical sales data. It is possible that historical data does not accurately reflect demand patterns enough to base forecasts on. For example, if a stock out occurred for a two month period due to supplier problems, then the forecast module will predict that no sales will occur again the same time next year. In such instances, it can be necessary to change historical data, so the sales forecast can be generated data that reflects normal demand patterns.
This can be done in the chart view. In the upper right corner is a pencil, where the user can edit sales history.
If we have adjusted the sales history, but have later decided to revert to the original sales numbers, it is important to do this correctly:
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In the graph, you double click on the adjusted sale bar. It will then jump to original sale.
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In the data, you delete the line and then press Enter. Do not write in the original number.
If you do not follow one of the two steps above, the monthly value will be distributed evenly through all the weeks.
Recalculate Chart Data
Clicking on this button allows the user to refresh the chart data. Sometimes purchase plans are not showing the correct data due to an outdated forecast. Clicking on this button, the user can then make sure they are using the newest forecast. If the chart data seems a bit off to the user, they can click on this button and check if the graph updates itself.
Info
The user can see all relevant information about an item by click on the i button within the item card. This will open an information sidebar within the item card. The item card with an opened information sidebar can be seen below.
Open in New Window
It is possible to open the item card in a new window by clicking the button below.
