Warehouse activity profile

The goal is to find patterns within the customer orders and then tune warehouse processes to be a more efficient match for these patterns. Customer orders are available to us from a sales history. This is extremely valuable information and companies are understandably reluctant to share it.

We must be able to guarantee protection. This can include asking specifically that No financial information be shared — we do not need it since our concerns are operational — and that product descriptions can be omitted if necessary.

Plan for data transfer

Client will prepare two files:

• sales.txt, which lists all customer orders picked on during the recent past, preferably the last year.
• skus.txt, which describes the stock-keeping units shipped from this warehouse.

The files will be prepared in two stages: First, skus.txt together with one week’s worth of sales.txt, which we will validate and then return a summary to the client. (One week’s data is small enough to be easily handled. For example, it will be viewable by a spreadsheet program, while the full data set may not be.)

Then the client prepares the full files (all SKUs and all lines). We will then validate the full files and return an exception report.

Structure of data files

• Format: ASCII text
• Field delimiter: a single Tab character
• Record delimiter: end-of-line
  • Which convention? Cr (unix)? CrLf (Microsoft)? Lf (Apple)?
• No missing (empty) fields unless meaning agreed upon in advance
• Date format: YYYYMMDD
• Records of lines.txt sorted by date and, within date, by order number so the lines of each order are consecutive.

Data

Description of customer orders

• Unique order number
• Pick date
• Unique SKU identifier
• Quantity ordered
• Quantity shipped

Description of SKUs

• Unique SKU identifier
  • Is this case sensitive?
  • Does it encode any special information?
  • Have there been any recent changes?
• SKU description (text, for reality checks)
• Product family
• Current storage location
  • Zone
  • Aisle
  • Bay
  • Shelf
• Packaging
  • Pieces per case
  • Cases/pallet
• Dimensions
  • Piece length, width, height, weight
  • Case length, width, height, weight
  • Stack height of cases, pallets
• Activity status
  • Active? New product date?
  • Discontinued? When?
  • Purged? When?

Description of Warehouse

This data may be unstructured and typically requires discussion with warehouse personnel.

• Addressing scheme (how are addresses assigned to storage locations?)
• Map giving layout of warehouse. (This does not have to be of AutoCAD level of detail; it can be a drawing in a spreadsheet.)
• List of types of storage and their dimensions (example: shelving, with openings 18 inches deep, 36 inches wide, and 16 inches high; 5 shelves per bay.)
• Explanation of key warehouse processes (receive, put-away, pick, check/pack/ship).

File transfer

• Process (CD, ftp, http, etc.)
• Compression (zip, bzip, gzip, etc.)