RightChain Insights

powered by RightChain.ai

PARTITIONS

PARTITIONS

Partition Distinct Types of Customers, SKUs, Orders, and Lanes

PARETOS

PARETOS

A, B, C, D and F Classifications of Customers, SKUs, Orders, Suppliers, Carriers and Lanes

STRATIFICATIONS

STRATIFICATIONS

Multi-criteria Stratification of Orders, Customers, Shipments, SKUs, and Lanes

OUTLIERS

OUTLIERS

IDs Anomaly Orders, Customers, Products, and Patterns

PREDICTIONS

PREDICTIONS

AI-based forecasting and predictions.

SUB-NETWORKS

SUB-NETWORKS

IDs Supply Chains within the Supply Chain

CORRELATIONS

CORRELATIONS

IDs Correlated Products and Patterns

Demo Screenshot

Demo Screenshot

Maps Supply Chain Activity to Country, State, City, and Postal Code

RightChain Insights Overview

RightChain Insights provides deep actionable analytics on supply chain activity data including sales order activity, purchase order activity, transport order activity, warehouse order activity, shipping manifests, airway bills, and inventory records. The analytics include Paretos, Stratifications, Partitions, Outliers, Predictions, Correlations, Activity Networks, and Activity Maps. 

Supply Chain Activity Paretos

Supply Chain Activity Paretos rank and compute the number and portion of products, SKUs, categories, customers, carriers and suppliers that comprise the first 50% (A's), next 30% (B's), next 15% (C's), and last 5% (D's) of orders, lines, units, pallets, cartons, cube, weight, dollars, mistakes, and inventory.

Supply Chain Partitions

Supply Chain Partitions identifies statistically significant activity cells within supply chain activity based upon user specified criteria including SKUs, categories, suppliers, channels, customers, carriers, geographies, and ABC strata.

Supply Chain Outliers

Supply Chain Outliers identifies supply chain data points (e.g. SKUs, products, customers, locations, carriers, lanes or commodities with unusual activity and activity ratios) that are statistically far enough removed from the remainder of their data family that they are considered outliers or anomalies. Those points may or may not be removed from their data family for on-going analytics.

Supply Chain Predictions

Supply Chain Predictions forecasts future supply chain activity in orders, lines, units, cases, pallets, cube and weight at the daily, weekly, monthly, quarterly, and annual level.

Supply Chain Correlations

Supply Chain Correlations identifies the degree to which key units of measure (units, cube, weight, and currency) and supply chain entities (SKUs, products, customers, commodities, geographies, channels, etc.) are correlated with one another. 

Supply Chain Sub Networks

Supply Chain Networks identifies supply chains within the supply chain that merit consideration for bespoke service, inventory, transportation and warehousing designs.

Supply Chain Maps

Supply Chain Maps geographically illustrates supply chain activity (orders, lines, units, cases, pallets, cube and weight) by ship to/from address, city, state, country and region for user selected business units, divisions, product categories, commodities, modes, carriers, and ship dates.