ABC-XYZ анализ продаж

Добрый день,
ABC-анализ состоит в сортировке всех объектов анализа на три группы (A, B и C) в соответствии со степенью их важности.
XYZ-анализа – это оценка объекта анализа по вариации спроса. Его суть состоит в следующем: если товар продается постоянно, то он относится к группе Х, если нерегулярно – то к группе Z.
Совмещая два отчета (ABC анализ и XYZ анализ) можно построить отчет, который показывает, какие из товаров обеспечивают максимальный доход и стабильный спрос (сочетание A и X). Именно эти товары должны всегда быть в наличии в магазине, так как они приносят максимальную прибыль. Соответственно, товары, соответствующие сочетанию групп C и Z - это те, которые приносят минимальную прибыль и продаются нерегулярно. Они требуют особого рассмотрения, возможно, их необходимо будет вывести из ассортимента. Товары, которые относятся к сочетанию C и X – это товары, приносящие маленький доход, но на которые есть спрос.
К примеру,  если Вы строите отчет на основании суммы продаж  и к примеру выставили следующие параметры:
Группа А - 70
Группа В - 20
Группа С - 10,
В группу А попадут товары сумма продаж которых составляет 70% от общей суммы продаж, в группу В  - 20% от сумму продаж и т.д.

Спасибо, очень информативно!
А как сделать чтобы отображалось "ABC анализ покупателей", "АВС анализ товаров", "XYZ анализ покупателей", "XYZ анализ товаров" ?
У него отображается только "АВС-XYZ анализ"

Просьба уточнить не отображаются в списке отчетов?
Группа Z не отображается так как анализируется по остаточному признаку. Все что не попадает в X и Y, попадает в Z.

Да, при данном интерфейсе эти отчеты не отображаются.

В данном интерфейсе их тоже нет. Эти отчеты отражаются для полного интерфейса.

Добрый день! у нас отчет не показывает группы A-Y, B-Y, C-Y, A-Z,B-Z,C-Z?
Только первые
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[/img]

А если мы хотим увидеть и другие группы? изменить процент?

Ничего не изменилось, только в группы A-X, B-X, C-X стало попадать больше товара

Суть метода понятна, а как просмотреть состав групп A-Y, B-Y, C-Y, A-Z,B-Z,C-Z?  

Выводятся только группы группы A-X, B-X, C-X, а как просмотреть состав групп A-Y, B-Y, C-Y, A-Z,B-Z,C-Z?