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Documentation for Streamline 4.x

User Guide

1. General Information

2. Starting Up

3. Connecting data

4. Demand and Sales Forecasting

5. Inventory Planning

6. Reference

connecting-data

3.1. General Requirements

Data import is the first step in creating a new project in Streamline. Streamline can import data from a number of sources starting from Excel files in different formats and ending with various databases.

When you first create a new project from your data source, Streamline automatically saves all your import settings and creates a link to the data source. It uses this link to synchronize the project with your data source as you click the Update data button.

Data that can be imported, the corresponding Streamline features and reports are shown in the table below.

Data Feature Report
Sales data Sales history Demand forecasting and planning, unit-based ABC analysis. Demand plan, forecast adjustments report, forecast accuracy report, ABC analysis report.
Sales prices Revenue forecasting. Revenue plan, revenue-based KPIs in KPI report.
Revenue history Revenue-based ABC analysis. ABC analysis report.
Inventory data Basic information Inventory planning, stockout and overstock analysis. Purchase/replenishment plan, projected inventory levels report, expected stockouts and overstocks.
In transition information More precise inventory optimization. More precise inventory reports.
Pending sales orders
Inventory value or purchase prices ABC analysis based on gross profit, COGS, or inventory value. ABC analysis report.
Locations or Channels Locations Demand forecasting and inventory planning by location. All of the reports can be viewed from the location view.
Channels Demand forecasting by channel or customer. Demand plan by channel.
Kitted items Disassembling of kitted items. All of the reports are generated for kit's components.
Bill of materials Material requirements planning. Material requirements plan, production plan.
Product shelf life Inventory optimization for products with a shelf life. Purchase/replenishment plan is adjusted to account for the shelf life.
To get more precise inventory reports, we strongly recommend you to provide Streamline with the orders-to-receive information and orders-to-ship information.

Streamline supports product and location or channel dimensions. Product and location dimensions allow all of the information imported and produced by Streamline (forecasts, plans, reports) to be seen from item and location views. Product and channel dimensions allow you to plan your demand by distributing channel or customer and plan the inventory on an item basis. Locations or channels must be, certainly, imported, to activate corresponding views. In these cases, the forecasted entity is a unique product-location or product-channel pair which is called planning item.

Streamline can aggregate imported data in given periods (days, weeks, and months) depending on your forecasting and planning needs. For example, if you want to see monthly forecasts, aggregate the data by month.

To get accurate forecasts, we recommend you to provide Streamline with at least 24 months of sales history. Streamline implements special approaches to provide accurate enough forecasts in situations of forecasting a new product when the history is very short (three or two periods) or is totally absent.

To discover all the Streamline's data connections, click the New button on the toolbar.

All Streamline's connections can be divided into three categories:

  • Spreadsheet connections. These are designed to import data from Excel files and CSV files in certain formats.
  • Database connection. This connection is the most generic and powerful. It allows you to pull data from any database that has an ODBC driver.
  • 3rd party system connections. These connections were specifically designed to work with a certain accounting or inventory management system. They have a simple user interface and require minimum efforts to import the data into Streamline.

Spreadsheet Connections

There are two spreadsheet connections in Streamline, the Aggregated data and Transaction data. Any of them can import data from Excel and CSV files. The Aggregated data requires the data (sales, on-hand, revenue histories) to be aggregated in certain periods prior to the import. Unlike Transaction data can import raw transactions and makes the aggregation while the data is being imported.

Since CSV files do not have multiple sheets, they limit the information that can be imported.

The Aggregated data connection comes in handy if you run (or can format) your sales and inventory information in a single Excel spreadsheet or CSV file. It is intended for a common format of manual bookkeeping. It has the weakest import capabilities and can import the least amount of data comparing to the Transaction data connection or the Database connection.

If you keep all the information in a database, ERP, accounting or inventory management system and have an ability to make an extract of inventory movement transactions as an Excel or CSV file, use the Transaction data connection.

Database Connection

If your system does not have an ability to export the information, you can use Database connection that can import entire spectrum of data types directly from the system’s database into Streamline. It allows importing full spectrum of data that Streamline understands and has the strongest import capabilities. In this case, SQL-queries knowledge is required.

3rd Party System Connections

Streamline has several integrations with different accounting or inventory management systems. The integrations have their own connections that import all necessary data to make forecasts and procurement plans in Streamline.

There are two types of integrations, one-directional integration and bi-directional integration. The difference is that bi-directional integration additionally allows exporting the recommended replenishment information as purchase orders into the system back.

Bi-directional integrations are the following:

One-directional integrations are:

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Next: Excel and CSV files

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connecting-data.txt · Last modified: 2019/07/11 07:20 by admin