Mass Stock Write-On's

Created by Migration Bot, Modified on Fri, 23 Oct at 2:29 PM by Migration Bot

Originally written by John Hardwick, last updated Oct 24, 2023, on the Swan Retail knowledge base (FRS).

Based on SwanFRS Release version 1207

Overview

This document describes how to load large volumes of ‘non-optioned’ stock into SwanFRS.

Configuration

If you have not used this method of loading stock into SwanFRS before or have used the process prior to version 1207, please raise a call with Swan Support to ensure you have the correct load configuration.

Operation

This process will only create stock write-on records for SKUs which DO NOT have options. items with options will be rejected.

Import File

To mass load stock into SwanFRS construct a csv data file and place in the tmp\in folder on your file share, ensuring the name of the file begins with FRSStock. For Example FRSStock32432.csv

The file has a maximum of 8 columns

Column	Name	Description	Example
1	SKU / Model Number	This can be the SKU or Supplier’s Model Number of the item. If using Model Numbers please be aware that the system will use the first model number it encounters when searching for a match, therefore if the model number is replicated across many SKUs the first SKU created will be used in preference to any other code. When storing the data ensure model numbers are encapsulated within quotation marks. This tells the load program to use the SKU literally and not to ‘read’ the data as a date. This column is mandatory and cannot be left empty.	“12-23-35”
2	Qty	Specify how many units of this item are to be ‘written-on’ This value must be an integer value greater or equal to 1. Decimal or negative numbers will cause the import to fail, with the file not being processed. This column is mandatory and cannot be left empty.	1
3	Location Description	Specify the trading name of the location holding the stock. This MUST match the description of the location as set within Set Up Locations. See https://swanretail.atlassian.net/wiki/spaces/FRS/pages/2078277832/Set+Up+Locations?search_id=c03ce427-a4d1-44e6-8857-8279312324a0 This column is mandatory and cannot be left empty.	Main Street
4	Bay Name	Optionally specify the bay or storage area this row (item) is located. This MUST match the description of a storage area within the specified location. See https://swanretail.atlassian.net/wiki/spaces/FRS/pages/2099676353/Set+Up+Storage+Areas?search_id=e9abea10-06c3-47f2-9251-0b2465d108ab If this column is omitted from the data structure, all subsequent columns must also be omitted. It is possible to include the bay name and omit the remainder.	104
5	Write On Date	Optionally specify the data this row (item) became a item of stock. Dates must be formatted in the CCYY-MM-DD format. For example, 10th January 2023 would be 2034-01-10. If this field is set, ALL subsequent column MUST ALSO be present within the data structure. If included, this field cannot be blank. Dates cannot be earlier than 1900-01-01.	2023-01-01
6	Actual Cost	Optionally specify the cost of the stock item as at the date it was received. This value can be null / empty, in which case the prevailing cost price as of today will be used. This column allows a 2 decimal place currency value. Decimal or negative costs will cause the import to fail, with the file not being processed.	123.45
7	Display	Optionally specify if the item is to be marked as ‘on display’. Set the column to 1 to mark as on display. Set to null / blank or 0 to mark as NOT on display Only blanks, 1’s and 0’s are allowed, any other character(s) will cause the load process to error with the file not being processed.	1
8	Cannot Sell	Optionally specify if the item is to be marked as ‘available to sell'. Set the column to 1 to mark as cannot sell. Set to null / blank or 0 to mark as saleable. Only blanks, 1’s and 0’s are allowed, any other character(s) will cause the load process to error with the file not being processed.	1
9	Imperfect	Optionally specify if the item is to be marked as ‘imperfect' Set the column to 1 to mark as on imperfect. Set to null / blank or 0 to mark as perfect. Only blanks, 1’s and 0’s are allowed, any other character(s) will cause the load process to error with the file not being processed.

The table can be either 3, 4 or 9 columns, but not a mixture within the one load file.

An example of a file structure is shown below. Note this file would create several write-ons breaking the load out by stock holding location and write-on dates.

"53-1-132",Main Street,104,2023-01-01,123.45,1,1,1
"53-1-133",Main Street,,,,,,
"54-1-134",Warehouse,A1,,,,,
"123-2302-232","Warehouse,A3,2024-02-02,44.45,,1,

Once ready, the file MUST be placed in the tmp\in file share named FRSStock*.csv, where * indicates any number of optional additional characters.

Once processed, the file is moved to the READ folder and give a datetime stamp suffix.

For example FRSStock123.csv would become FRSStock123.csvCCYYMMDDhhmmss (where CCYY - 4 character year, MM= 2-digit month, DD - two digit day of the month, hh = 2 digit hour, mm = 2 digit minute and ss is the seconds)

The load will process all valid records, writing rejections to an audit log.

Loading Data

Menu Location: Accounts > Accounts Interface

To import the data, once the load file is in the designated folder, use the REFERENCE DATA button within the Import section of the Accounts Interface program.

Once completed, red narrative to the right of the button will indicate the number of records loaded. This is the number of accepted rows in the load file and not the number of stock items loaded.

Use the Find Write-On Notes program to view the details of the load.

It is important to remember the process may result in multiple write-on notes being created for various dates. SwanFRS presents the write-on notes in write on date sequence not note sequence, therefore the newest notes are not always at the top of the list.

Rejections

The Mass Stock Load Rejections report provides an audit of load file record which were correct in structure but contained data elements which prohibited loading into the database.