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"Results" area is designed to display the forecast results and the factors that affects them, as well as for studying their nature.
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"Results" area consists of two components:
analysis area – designed for in-depth study of the forecast model, predictors and their influence on the forecast;
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results display area – designed to display the results of the forecast and the values of the parameters.
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Button "More" opens additional displaying parameters of the forecast results (to hide additional parameters, you need to press the button "Less"):
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You can setup results displaying in next ways:
change the displaying of forecast date to weekly/monthly;
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select forecast range to display (from the start date to the end date);
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сhange the display of the forecast sales by sales volume or by sales value.
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To apply the changes, click "Show".
Additional parameters tab has the pane that allows you to work with files:
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To load previously calculated model to analyze it you have to select file in field "Select a file…" field, and then press load button ;
Для сохранения построенной модель прогноза в формате json (для возможности ее загрузки в будущем) нужно нажать кнопку ;
save and download the calculated forecast and the configuration matrix (forecast parameters) in csv format press .
Analysis area
Analysis area is one of the "Results" area components, it is designed for in-depth study of forecast model, its components and their influence on forecast. Area is used to manually analyze the forecast by SKU, to understand forecast numbers, to analyze the factors that affect it. This is a very important part of the software, since it allows the user to get complete information about the influence of various factors on the forecast, to understand how sales change with price changes, and also to see in numerical terms how different factors will change sales.
Analysis area is represented by header and elements panel.
Header displays:
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Group Name / SKU;
Stores count / Store name;
– button for downloading results into csv file.
Elements panel allows you to get detailed information about all positions and consists of next elements:
– drop-down list, which elements allow analyzing sales and forecasting model by SKU. It consists of:
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SKUs chart – visualizes "Components" element in the form of a chart for all SKUs (the user himself selects which component to display on the chart). Details on all components are described in the Forecast analysis components guide;
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SKUs table – visualize "Components' element values as a table for all SKU (the user himself selects which component to display on the chart);
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SKUs list – allow selecting for analysis forecast model for a particular SKU. The forecast model for the selected SKU is displayed as a separate area under the parent area (in list, SKU element disappears);
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Stores – drop-down list, which elements allow analyzing sales and forecasting model by Store. It consists of:
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Stores chart – visualizes "Components" element in the form of a chart for all stores (the user himself selects which component to display on the chart). Details on all components are described in the Forecast analysis components guide;
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Stores table – visualize "Components' element values as a table for all Stores (the user himself selects which component to display on the chart);
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Stores list – allows selecting for analysis forecast model for a particular Store. The forecast model for the selected Store is displayed as a separate area under the parent area (in list, Store element disappears);
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Components – Allows you to add a new component, parameter, result or characteristic of the calculated forecast model to the results display area. Different components display either their influence on the forecast in sales volume or value, and also display historical values of factors that affect the forecast. The use of components allows a more detailed study of the influence of factors on the forecast, as well as understanding why the forecast has one or another value. Anomaly sales and excluded weeks are also added using components (described in detail in theAnomaly & Excludedsection). After being added, the component disappears from the list; The component is returned to the list after it is removed from the display area. For more detailed information about the "Components" elements, use theСправочник компонентов анализа; section;
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Forecast – designed for visual analysis of the forecast results on the chart. The chart allows you to visually estimate built forecast, as well as using components to understand the forecast behavior (for example, using the stock component, you can see changes in the stocks balance and understand that, for example, sales fell precisely because of shortages);
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By default chart displays historical sales, forecast, and historical sales shifted by 52 weeks to the right (for visual forecast estimation) Also chart displays selected components. The user can turn off the display of any element by clicking on its name under the chart.
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Predictors – designed for visualization and assessment of the impact of predictors on the predictive model (those predictors that were included in the model are displayed). Allows you to analyze, because of what parameters the forecast has one or another value. For more information on predictors, seePredictors. This element is very important for understanding the forecast itself. It displays the numerical values of the influence of various factors on the forecast and understand on what exactly the sales depend in different periods. User can turn off the display of any element by clicking on its name under the chart.
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Price – designed to visualize the chart of price elasticity of demand. This chart allows the user to see how demand changes when the price of a product changes using price elasticity. The system calculates average sales in volume, value and margin relative to different prices. The system also calculates theoretically optimal price values to maximize sales in value and margin. The area around the chart line indicates the possible range of sales for a particular price value. It is built based on the forecast error, it is logical that the larger the error, the larger the area and the greater the range of predicted sales values.
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There are 3 interpretations of price elasticity (depending on what it is considered). To select, click on the required field; the current price value is indicated by a dot on the graph):
Volume – influence on sales volume, purchase price – estimated purchase price;
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Value – influence on sales value, purchase price – estimated purchase price, best sales price – price, that, theoretically gives the highest sales;
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Margin – influence on sales margin, purchase price – estimated purchase price, best sales price – price, that, theoretically gives the highest margin.
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Trends – designed to visualize the influence of prices, discounts and weather predictors on sales on the chart with a range of error. It allows the user to see how changes in these factors will change sales.
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The necessary parameter is selected from the elements of the "Predictors" drop-down list; if the necessary parameter is not in the list, the influence of this factor is not observed.
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There are 2 interpretations of influence (current value is marked with a dot):
Volume – influence on sales volume;
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Value – influence on sales value.
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Models – designed to study and analyze forecast model, to study the influence of various predictors, to analyze reports on model calculation, to select another forecast model in case of disagreement with the model selected earlier.
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The element has 3 display variants:
general – for the aggregated forecast model of stores and SKU, is displayed when the model tab is selected at the group or SKU level until individual stores are selected. Displays models for all selected stores, as well as for regions.
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normal - displayed after selecting a specific store. It can be displayed for all SKUs as well as for selected ones (to select this parameter, you have to choose one particular store), it displays:
Forecast estimate - shows values for different forecast estimates;
Tested trial models - built models, their assessment, the impact of the predictor options previously specified in the file for each model. The model that the system has selected as the best based on the standard error is highlighted in green. The user can manually change the model by clicking next to the selected model in the "Fix"
Correlation Coefficients - coefficients of dependencies of different components on each other and on sales;
Trends - formulas for recovering the values of forecast elements;
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detailed – for detailed studying of the forecast calculation process model, it is displayed as a log of calculation process and works only in the "52-weeks log" mode (log automatically appears in Model area)
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Results display area
Results display area – is one of the "Results" area components, that is used to display forecast results, historical data values, recovered data, and other resulting components.
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By default, the following components are displayed:
week in ISO format;
historical sales volumes (or values) for the relevant week;
sales volume (or values) forecast for the relevant week;
historical sales volumes (or values), shifted 52 weeks ahead in time, for the relevant week.
Also, it is possible to add other components by using the analysis area component "Components"; for more detailed information about the components, use the "Forecast analysis components guide" section.
Forecast analysis components guide
Components of the forecast analysis (element "Components") are designed for detailed analysis and study of the calculated forecast model.
Components of the forecast analysis are divided into the following categories:
volume – components that display the results of the forecast in the form of sales volumes;
value – components that display the results of the forecast in the form of sales values;
original – components that display historical data and intermediate forecast results (predictors that were used at any of the forecast stages) based on historical data;
competitors - components that display competitors price for the selected SKU from competitors;
regressed – сomponents that represents the influence of price factors, weather factors and the width of the assortment of the group;
economy – components that represents the economic effect when correctly used by MySales;
models – components that represents forecast when using alternative forecast models (not shown for aggregated models).
Category 'Volume'
Category volume consists of the following components:
order – represents the sales forecast with safety stock (recommended results for ordering);
seasonality – represents the influence of the seasonality on sales volume (taking into account the coefficient of influence on the forecast);
trend – represents the influence of the trend on sales volume (taking into account the coefficient of influence on the forecast);
region – represents the region sales influence on sales volume (taking into account the coefficient of influence on the forecast);
group – represents the group sales influence on sales volume (taking into account the coefficient of influence on the forecast);
auto error – represents the influence of unknown factors on sales volume (taking into account the coefficient of influence on the forecast). It is based on the avg error component, and the duration of the component effect can be 2, 4, or 6 weeks, depending on which duration gives the best result (min error);
min – represents the influence of the sales conversion on sales volume, in the case of a forecast below the historically limiting volume (taking into account the coefficient of influence on the forecast). The limiting sales volume is the lower quartile of sales by default;
price % – represents the price changing influence on sales volume (taking into account the coefficient of influence on the forecast);
discount – represents the discount influence on sales volume (taking into account the coefficient of influence on the forecast);
discount % – represents the discount (in percent) influence on sales volume (taking into account the coefficient of influence on the forecast);
rate – represents the dollar rate influence on sales volume (taking into account the coefficient of influence on the forecast);
a. price – represents the actual price (price with discount) influence on sales volume (taking into account the coefficient of influence on the forecast);
price – represents the price influence on sales volume (taking into account the coefficient of influence on the forecast);
item count. – represents the influence of the width of the available assortment (the width of the assortment on the stock) on the sales volumes (taking into account the coefficient of influence on the forecast);
group disc – represents the influence of the average discount of all SKUs in the product group that the SKU belongs to (taking into account the coefficient of influence on the forecast);
group price – represents the influence of the average price of all SKUs in the product group that the SKU belongs to (taking into account the coefficient of influence on the forecast);
base – represents the base sales level (taking into account the coefficient of influence on the forecast);
temp. – represents the average air temperature during the week influence on sales volume (taking into account the coefficient of influence on the forecast);
rain – represents the proportion of raining days of the week influence on sales volume (taking into account the coefficient of influence on the forecast);
snow – represents the proportion of snowing days of the week influence on sales volume (taking into account the coefficient of influence on the forecast);
anomaly - displays the volume of anomaly sales, and also allows you to enter the value of anomaly sales in the opened field. Anomalies are described in detail in the section 'Anomaly & Excluded';
исключения - displays excluded weeks, and also allows you to exclude weeks in the field that opens. Excludes are described in detail in the section. 'Anomaly & Excluded'.
If any components from the list are not displayed, this means that they were not included in the predictive model as predictors.
The sign ® or the prefix "reg" before the component means that this component is present in the recovered value (regressors).
Category 'Value'
Category value consists of the following components:
sales – historical sales value;
forecast – forecast of sales value;
last year saels – historical sales value, shifted 52 weeks ahead in time;
order – represents the sales forecast with safety stock (recommended results for ordering);
seasonality – represents the influence of the seasonality on sales value (taking into account the coefficient of influence on the forecast);
trend – represents the influence of the trend on sales value (taking into account the coefficient of influence on the forecast);
region – represents the region sales influence on sales value (taking into account the coefficient of influence on the forecast);
group – represents the group sales influence on sales value (taking into account the coefficient of influence on the forecast);
auto error – represents the influence of unknown factors on sales value (taking into account the coefficient of influence on the forecast). It is based on the avg error component, and the duration of the component effect can be 2, 4, or 6 weeks, depending on which duration gives the best result (min error);
min – represents the influence of the sales conversion on sales value, in the case of a forecast below the historically limiting volume (taking into account the coefficient of influence on the forecast). The limiting sales volume is the lower quartile of sales by default;
price % – represents the price changing influence on sales value (taking into account the coefficient of influence on the forecast);
discount – represents the discount influence on sales value (taking into account the coefficient of influence on the forecast);
discount % – represents the discount (in percent) influence on sales value (taking into account the coefficient of influence on the forecast);
rate – represents the dollar rate influence on sales value (taking into account the coefficient of influence on the forecast);
a. price – represents the actual price (price with discount) influence on sales value (taking into account the coefficient of influence on the forecast);
price – represents the price influence on sales value (taking into account the coefficient of influence on the forecast);
item count. – represents the influence of the width of the available assortment (the width of the assortment on the stock) on the sales values (taking into account the coefficient of influence on the forecast);
group disc. – represents the influence of the average discount of all SKUs in the product group that the SKU belongs to (taking into account the coefficient of influence on the forecast);
group price – represents the influence of the average price of all SKUs in the product group that the SKU belongs to (taking into account the coefficient of influence on the forecast);
base – represents the base sales level value (taking into account the coefficient of influence on the forecast);
temp. – represents the average air temperature during the week influence on sales value (taking into account the coefficient of influence on the forecast);
rain – represents the proportion of raining days of the week influence on sales value (taking into account the coefficient of influence on the forecast);
snow – represents the proportion of snowing days of the week influence on sales value (taking into account the coefficient of influence on the forecast);
anomaly - displays the value of anomaly sales, and also allows you to enter the value of anomaly sales in the opened field. Anomalies are described in detail in the section 'Anomaly & Excluded'.
If any components from the list are not displayed, this means that they were not included in the predictive model as predictors.
The sign ® or the prefix "reg" before the component means that this component is present in the recovered value (regressors).
Category 'Original'
Category original consists of the following components:
seasonality – represents the seasonality of sales;
trend – represents the trend influence on sales;
a. price – represents the actual price (price with discount);
price – represents the price;
price % – represents how many times the price has changed;
discount – represents the discount;
discount % – represents the discount (in percent);
stock – represents the goods balance on stock;
group price – represents the average price of all SKUs in the product group that the SKU belongs to;
group disc. – represents the average discount of all SKUs in the product group that the SKU belongs to;
region – represents the region sales redestribution influence on sales;
group – represents the group sales redestribution influence on sales;
rate – represents the dollar rate;
rate % – represents the changing in the dollar rate (how many times has it changed);
seas. mult – represents the seasonal increase in sales in the form of coefficient (how many times will sales increase);
avail – represents the availability of goods (enough was the goods in the stock for its maximum sale). In store level displaying a "0" or empty space – the product was unavailable, "1" – the goods was enough. In store aggregated level the component represents the number of stores where the goods were avail;
temperature – represents the average air temperature during the week;
temperature, Δ – represents the difference between the average temperature for a particular week and the average temperature for the last 13 week
rain – represents the proportion of raining days of the week;
snow – represents the proportion of snowing days of the week;
seas. type – represents a season type (value of 0 for the normal season, -1 for the low season and 1 for the high);
promo ratio – represents number of days per week in percentage for which promo was held;
avg. error – represents the average error of forecast;
auto error – represents the influence of unknown factors on sales volume. It is based on the avg error component and the duration of the component effect can be 2, 4, or 6 weeks, depending on which duration gives the best result (min error);
median – represents the median of sales;
base – represents the base sales level;
min – represents the influence of the sales conversion on sales volume, in the case of a forecast below the historically limiting volume. The limiting sales volume is the lower quartile of sales by default;
item count – epresents the width of the available assortment (the width of the assortment on the stock);
receivings – represents the sum of all goods receiving in stores (from the supplier or from the warehouse), minus the write-offs of shortages;
# of Stores – represents the count of stores in which group or SKU is represented (available at the region level).
Category 'Regressed'
Category regressed consists of the following components:
reg. a. price – represents the actual price (price with discount) influence on sales;
reg. price – represents the price influence on sales;
reg. price % – represents the price changing influence on sales;
reg. disc. –represents the discount influence on sales;
reg. disc. % – represents the discount (in percent) influence on sales;
reg. rate – represents the dollar rate influence on sales;
reg. rate % – represents the dollar rate changing influence on sales;
reg. item count – оrepresents the influence of the width of the available assortment (the width of the assortment on the stock) on the sales;
reg. temp. – represents the average air temperature during the week influence on sales;
reg. rain – represents the proportion of raining days of the week influence on sales;
reg. snow – represents the proportion of snowing days of the week influence on sales.
Category 'Economy'
Category economy consists of the following components:
stock reduce – represents how much the use of the forecast can reduce the balances in the stock;
sales lost – represents the loss of sales due to a lower forecast;
sales increase – represents how much the use of the forecast can increase sales.
Use cases
This form is created for sales and forecasting analysis and has a very wide application. The most successful and largest retailers in the world use the expression "Retail is detail".
The "Analysis" form can be used both for forecasts verefication in the process of setting up and implementing the system, and for analyzing various factors in the process of using the system. It allows user to understand and analyze the factors affecting sales. Using this form will help the user to get answers to a wide range of requests while using the system, including, but not limited to:
What is the sales forecast for a specific product, product group, store, region or the whole chain in volume, value or margin
Visual estimation of forecast and sales, comparison with last year's sales
Estimation of forecast components and factors included in it:
Estimating the influence of various factors that affects forecast and sales, including prices, discounts, promotions, weather (temperature, rain, snow), macroeconomic factors (for example, exchange rates), seasonality and trend, cannibalization (mutual influence of goods in the group on sales of each friend) and even prices and promotions from competitors!
Analyzing the impact of the factors mentioned above on the sales, at the level of the all stores, regions and specific stores
Modeling the impact of influencing factors on the future forecast. For example, how sales will change if you lower the price by 10% or increase the discount by 10%
View sales correlation coefficients and factors that influence the forecast
View all models tested by the forecasting system and their accuracy, estimated by the coefficient of variation (standard deviation divided by average sales) and absolute error
View forecast errors on weekly or 4-week ranges, estimated as an absolute error in percent (MAPE), an absolute error in units (MAD), standard deviation in units (RMSE) and standard deviation in percents (RMSPE)
View mathematical formulas of dependencies between sales and influencing factors, which was determined using automatic regression analysis
Analysis of products stocks, trx, presentation and safety stocks
View a detailed forecast calculation log (forecast log in the system)
If you find that for a certain position there are any problems with stock balance, for example, there is a out of stocks, or an overestimated stocks, it is recommended to look in this form to analyze the reasons.
The specific cases that apear while users are working with the system and for which the "Analysis" form provides an answer can be found in Questions / Answers.
View
Overview & Use
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Page "View" is designed to display in a convenient format forecast data. The user can choose which data for which items he wants to see.
The list of records is displayed in the form of a table that has the following fields:
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Store - store number;
Group id – Group ID;
Name – Group name;
Week number – data for each week.
Operation manual
Template creation
To create template you have to select "Create New Template".
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And after press the button "Create Template".
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After clicking the button, a modal window for template creating opens. The user chooses which for which group, store, positions the data will be displayed, as well as display period, margins and accuracy. It consists of the following elements:
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Name - the name of the template;
Level - the level at which data will be displayed (depending on the choice the appearance of different fields for filling is possible);
Groups - group numbers;
Stores - store numbers;
SKUs – SKU numbers;
Regions - regions numbers;
Filter by name - filter positions by name;
Week from - the week number from which the data displaying will starts;
Week to - the week number to which the result will be displayed;
Fcst value – display the forecast in value;
Sales volume – display the sales in volume;
Sales price – display the sales price;
Fcst purch. value – display the forecast in value at the purchase price;
Sales value – display sales in value;
Purchase price – display purchase price;
Fcst master – display master forecast;
Sales purch. value – display sales in value at a purchase price;
Safety stock – display safety stock;
Assort stores -
Current stock -
Avg Safety Stock -
Precision – a number of symbols after the comma.
Template selection
To select an already created template, select the desired template from the drop-down list by clicking on the following field:
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To open a template, click "Run". A table with names and data on previously specified positions will open.
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Editing and deleting
To edit a template, you have to select the desired template from the drop-down list, and then click "Edit" button:
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After clicking the button, a modal window for editing the template opens. Using it, the user can change the same fields that were available when creating, save changes by clicking the button "Save", or delete the template by clicking the button "Delete".
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Filter
For a more handy items searching and displaying there is a search string. The search is possible for the following fields:
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SKU id;
Name;
Store.
Use cases
This functionality is recommended to be used if it is necessary to upload the forecast and other data (for example, safety stock) for one or several SKUs, several stores, or for groups, with the forecast weeks to be deployed horizontally. If a horizontal spread of weeks is not needed, you can also use the "Reports" functionality.
Examples of situations in which you can use forecast upload:
Given that the supplier’s production and supply planning cycle is much longer than the retailer’s supply cycle, this functionality will be useful to share SKU sales forecasts with the supplier or distributor, which will allow the supplier to improve the level of service due to long-term planning production, as well as reservation of a certain volume of goods
Uploading a forecast for product groups will be useful in order to improve the strategic planning process at the beginning of the year/quarter by comparing the sales plan for the top-level categories and the sales forecast for the lower product groups. The difference in the forecast between these levels, when the plan for categories is higher than the total forecast for product groups, as a rule, can be covered by a promotion, listing of additional regular or promotional assortment, opening of new stores.
Analysis of expanding distribution sales potential by comparing forecasts at different levels. For example, comparing the forecast at the regional level 0 (the whole chain) with the total forecast at the store level often shows the difference in the future (when the forecast at the regional level 0 in the future is greater than the total for stores), which can be covered by expanding the chain and opening new stores
Analysis of the potential of product groups to expand the assortment. For example, the difference between the forecast at the product group level and the forecast at the SKU level often shows the difference (when in the future the forecast at the product group level is larger than the forecast at the SKU level), which can be covered by rotation/expansion of the assortment in this product group.
Master
Overview & Use
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Page "Master" designed to manually set the forecast of a specific SKU for a specific week for all stores. The established forecast is distributed proportionally to all stores during the work of MySales.
Operating manual
Working with Master
Page "Master" has a wide functionality that allows to:
display a list of forecasts;
add forecast;
edit forecast;
delete forecast;
apply filters to display forecasts;
load forecasts from a file;
download forecast.
The list of forecasts is displayed in the form of a table, which displays the latest version of the forecast and has the following fields:
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Sku id – SKU ID number;
Sku Name – the name of Sku;
Week – week on which the forecast was added;
Type - the type of SKU;
Stores - stores selection for which the master forecast is distributed;
All - indicator of the selection of all stores;
Forecast – manual forecast;
FIX - indicates whether to fix the specified master forecast if the daily correction is triggered. For example, if the master is not fixed and the system sees that the sale is less than specified by the master, it will automatically lower the master forecast. And if the master is fixed, then the system will leave the master forecast unchanged (values 1 - fix, 0 - do not fix);
Date from - a field that indicates the start date of the promo (active only for Promo type items);
Date to - a field that indicates the end date of the promo (active only for Promo type items);
Updated by – user who last made the changes;
Updated – date of last change;
Notes – short remarks.
Filters
For more handy forecasts displaying and searching page "Master" has filters:
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