Dashboard Commercial: https://app.powerbi.com/view?r=eyJrIjoiYzk5NDYzYzUtOWQyZi00OWIyLWE5OTQtYTMyOTAzNWE5NTA4IiwidCI6IjgyYTU4NjE2LTY4ZDYtNDA1MS05Y2E5LWIyY2U2YmE1MjEzNCJ9
Dashboard Logistics: https://app.powerbi.com/view?r=eyJrIjoiMTQ0ZDhlY2MtZTM1Ny00NThmLTg2NzYtM2I3MmFiODgyMDU4IiwidCI6IjgyYTU4NjE2LTY4ZDYtNDA1MS05Y2E5LWIyY2U2YmE1MjEzNCJ9
Metrics by Logistics and Linguage DAX used:
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Placed Orders = count of orders placed.7
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Delivered Orders = count of orders, exclude those with blank delivery data.
DAX: Volume expedido = SUM(fNotasFiscais[Volumes])
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Open Orders = accumulated value of the difference between orders placed and delivered over the period.
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Order Fill Rate (OFR) = average of days between the order date and the CTE issuance date. Represents the time that the operation takes to pick an order, including all activities — from the recipient of the purchase order to shipment.
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Order Cycle Time (OCT) = average days between order and delivery date. It aims to measure how long the company takes to make a delivery, from dispatch to arrival at the destination, that is, the overall efficiency of the operation.
DAX: Tempo Médio Entrega = AVERAGE(fNotasFiscais[PrazoEntrega])
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On Time = number of orders delivered with a delivery date less than or equal to the expected date. Measures order timeliness.
DAX: Qtd On time = CALCULATE([Notas fiscais], fNotasFiscais[On Time Delivery] = "On Time")
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% On Time = proportion between orders On Time in relation to the total orders delivered.
DAX: % On time = DIVIDE([Qtd On time], [Notas fiscais])
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In Full = number of orders with zero occurrences of returns. Evaluates compliance with specifications agreed with the customer, such as quality, dimensions, quantity and price.
DAX: Qtd In full = CALCULATE([Notas fiscais], fNotasFiscais[In Full Delivery] = "In full")
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% In Full = proportion between In Full orders in relation to the total number of delivered orders.
DAX: % In full = DIVIDE([Qtd In full], [Notas fiscais])
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% OTIF = % On Time and % In Full multiplication. This segmentation makes it possible to identify whether the origin of the problem is in the delivery or in the expedition. Low On Time means that there is a need to review the transport process or improve negotiation of expected delivery data. On the other hand, a low In Full may indicate problems in processing, sorting, packaging, checking or dispatching the products.
DAX: OTIF = [% In full] * [% On time]