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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

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6.8. Reports

The Reports tab gives you an ability to generate a number of reports. It consists of a toolbar and a table showing the result of the selected report.

Toolbar

  • Period drop-down allows you to select a past period from the project's archive and view the reports for that period. This control is available for the following reports:
    • Final forecast.
    • Forecast overrides.
    • Forecast error.
    • Projected revenue.

  • Aggregate by drop-down allows you to group the selected report by one or several columns. The options are:
    • Item.
    • Item category.
    • ABC classification.
    • Supplier.
    • Location.
    • Channel.
    • All.
  • Sum by drop-down allows you to aggregate the Final forecast report by year or quarter.
  • Number of periods control allows setting the number of the last periods to show in the following reports:
    • Historical on hand
    • Historical lost days
  • Export report allows you to export the current report to an Excel file.
  • Import changes is used to import an exported report back into Streamline with or without changes you made in Excel.

Final Forecast Report

The report shows items’ statistical forecasts and overrides made manually through the Forecast adjustments row of the table on the Demand forecasting tab. The overrides are shown in blue color.

Forecast Overrides Report

This report shows only forecast adjustments you made manually in the Forecast overrides row of the table on the Demand forecasting tab. It is useful when you need to ensure that all the adjustments you intended to do were done.

Forecast Error Report

The Forecast error report helps you to evaluate the forecast using MAPE. This measure uses the difference between actual data and the forecast, thus this report can be calculated only when the Period control is set to any option, except the last period.

To demonstrate the report, we open a built-in example and set the Period to Sep 2018 (see figure below).

Now, we have an evaluation of the forecasts for the first three months. The rest of the periods were not evaluated because we don't have actual data for those months.

All the data in the Percentage error section are the Absolute Percentage Error (APE) calculated for a particular planning item/period. The formula is:

APE = 100 * delim{|}{(F - A)/A}{|},

where F is the forecast for a particular period, and A is the actual demand in this period.

The Percentage error section might have gaps or even empty rows. A gap occurs when there were no actual sales in the period. Streamline can’t calculate APE in this case. An empty row arises if either the item is inactive or an intermittent model is used.

The last column of the report represents MAPE calculated across all of the periods for each planning item.

The Overall MAPE, shown in the toolbar, is MAPE weighted across all the items in the project. If the products’ prices are given this is a price-weighted MAPE measure that represents overall revenue percentage error. Otherwise, it is calculated based on the volume of sales. You can read more about WMAPE on Wikipedia.

You can also switch the forecast quality measure between error and accuracy. To do this, click the Settings button found on the toolbar and select the Accuracy option for the Measure of forecast quality (see figure below).

Now, the report shows the percentage accuracy of the forecasts for each period in the Percentage accuracy section and the average accuracy across the available evaluations in the Accuracy column (see figure below).

The Overall accuracy in the toolbar equals to 100% - Overall MAPE now.

Projected Revenue Report

The Projected revenue report shows the revenues based on the current selling prices or adjusted selling prices, or the forecasts of seasonal selling prices.

Projected Sales Prices Report

This report shows the adjusted future selling prices. By default, the current sale price is used. However, the report displays the sales prices forecast if you import the selling prices history data. The adjustments can be made in the Average sales price row of the Table. They are displayed in blue in the report.

Historical Revenue Report

This report shows the revenue obtained during each historical period based on the Sales price/unit or Transaction revenue data imported from the data source.

Historical On Hand Report

This report displays on-hand at the end of each past period and the current period as well (see figure below).

This report is calculate if you provide data to detemine On-hand history, which is one of:

The Number of periods control allows setting the number of last periods to show in the report. As you see from the figure above, the report shows on-hand for the last 5 months.

Historical Lost Days Report

This report shows the number of days you had run out of stock for each past period and the current period as well.

This report is calculated if you provide data for On-hand history.

Historical Turnover Report

This report shows the turnover of each planning item in each historical period (see figure below).

Turnover can be measured in turns (how many times an item was purchased and then sold out during a period) and days (how many days it takes to make one turnover cycle). A drop-down in the Report toolbar lets you choose one of these options. By default, this report shows information in turns.

Zero value in a period means that there were no sales during this period. An empty cell means that Streamline can't calculate turnover due to zero on-hand in that period.

KPI report

KPI (Key Performance Indicators) report shows important indicators of the project performance. Streamline calculates a variety of indicators. Most of them evaluate the inventory planning process, however, the Annual revenue and Revenue next year can be estimated based on the forecasts and given selling prices only.

Annual revenue

Let’s explain, how this indicator is calculated. Consider the product sales history depicted in the figure below.

To calculate annual revenue in such cases, Streamline always skips zero demand before the sales have started. So only the sales of the last 8 months are taken into account. The formula looks like:

annual_revenue = RevenueMay-Dec/8 * 12

If we have sales history shown in the figure below, then sales of all the months are taken into account:

annual_revenue = RevenueJan-Dec/12 * 12

So, as you see, this indicator depends on the sales history of the last 12 months, and thus, may significantly change from month to month.

Revenue data of the current period is taken into account only if this period is complete. Thus, Annual revenue accounts for the data of the last 12 complete months.

Revenue next year

If the forecast horizon is one year, the next year revenue is the summed revenue of the next 12 months. Otherwise, it is calculated proportionally using the available data. For example, if data aggregation period is one month, this indicator is calculated as:

next_year_revenue = Revenuen/n * 12,

where:

  • n is the number of months to forecast ahead;
  • Revenuen is summed revenue over the future n months.

Annual gross profit

This indicator is an aggregation of transactions' profit over the last 12 complete months. It is calculated in two ways depending on the available data:

  1. It is the sum of the Transaction profit imported from the data source.
  2. It is calculated using the formula:

Annual~gross~profit=sum{t=1}{N}{(averSalesPrice_t - itemValue)*sales_t}

where:

  • N – the number of data aggregation periods making up 12 months.
  • averSalesPricet – the average sales price over the t-th period. It can be calculated if Sales price/unit was imported.
  • itemValue is imported either from Inventory value/unit or Item purchase price data type. If both of them were imported, the former is used in the formula.
  • salest – the item quantity sold in the t-th period.

The way using the Transaction profit is primary for Streamline.

Days of supply

This column shows the number of days of the future demand that can be covered by the (On hand - Pending sales orders) quantity. It is also depicted in the Inventory report.

Item value-dependent indicators

There is a set of KPIs which are calculated based on the item_value. These indicators are:

item value is imported from a data source using the Inventory value/unit or Item purchase price data type. If both data types are given, the former will be used.

  • Inventory value shows the value of the item in stock. If it is not imported directly using Aggregated spreadsheet connection, it is calculated as:

inventory_value = item_value * on_hand_qty.

  • Expected overstock value is the item's expected overstock cost. It is calculated as:

expected_overstock_value = item_value * overstock_qty.

  • Expected stockout value is the expected inventory deficiency cost. It is calculated as:

expected_stockout_value = avg_sales_price * stockout_qty.

where avg_sales_price is the average sales price in the current period; if we don't have sales in the current period, data of the previous period is used.

  • Non-moving inventory value is calculated for the items that will not be sold during the forecast horizon period according to the forecast. This KPI is not calculated for the items which are forecasted using an intermittent demand model. The formula for the indicator is:

Non-moving_inventory_value = item_value * on_hand_qty.

  • Gross margin is the annual item gross profit margin. Its calculation is based on the compound interest and the formula looks like:

Gross_margin = (1 - item_purchase_price * inflation_coefficient ^ sellout_time / aver_sales_price) * 100%

where:

item_purchase_price - the item purcahse price per unit imported from the datasource;

aver_sales_price - the average selling price calculated over the last 12 months;

inflation_coefficient = 1 + interest_rate;

sellout_time = (lead_time + days_to_sell)/365.25;

interest_rate – the annual interest rate that is taken from the project settings;

days_to_sell – the Average days to sell value.

2017/10/02 12:02

Inventory turnover

Inventory turnover tells how many times an item was purchased and then sold out over a particular period of time. Its formula looks like:

Turnover_period=sum{i=1}{N}{Sales_i}*K/sum{i=0}{K}{On~hand_i},

where:

  • N – the number of days in the period.
  • Salesi – the item quantity sold on i-th day.
  • K – the number of days in the period without stockout.
  • On handi – stock on hand on i-th day. It is determined based on On hand change or On hand (as remaining after a transaction) imported from the data source.

If sales history can't cover the period, it is brought to it proportionally using the formula:

Sales_period = sum{i=1}{K}{Sales_i}* N/K

where:

  • N – the number of days in the period.
  • K – the sales history length in days.
  • Salesi – the item quantity sold on i-th day.

Inventory turnover column of this report shows the turnover over the last 12 months.

Average days to sell

This indicator displays how many days it takes to make one turnover cycle.

Turn-earn index

This indicator shows an item gross margin accumulated over the last 12 months and calculated as:

Turn-earn_index = gross_margin * inventory_turnover.

This indicator is usually used to rank products and find the most profitable items.

Purchase value

The Purchase value column of the report shows the purchase amount for each planning item. It is calculated based on the current Streamline's purchase recommendations. This column allows you to view the total purchase amount by each supplier when you set the Aggregate by control to the Supplier option.


Next: Inventory Report

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