Analytics/Business Intelligence

Analytics and BI-related technologies, practices, examples

Data-Enabled Digital Transformation—Part One

Data democratization and self-service analytics are a gateway to companies’ data-driven decision-making in this post-digital transformation world. Rapid digitalization has altered the scope and scale of data usage across industries and throughout supply chains. Database structures and data management processes require accessible, accurate, and timely data, integrated from many sources to progress alongside this evolving landscape.

Analytics Advantage – Part 3B

A ‘self scorecard’ can help shippers improve their own turn-around times, detention metrics, dock door scheduling, load tender timing, and fulfillment of volume commitments. We also examine how trade data can be used for supply chain risk management, supplier discovery, price discovery, total landed cost optimization, and competitive intelligence.

Analytics Advantage – Part 3A

Analytics can be used to improve carrier performance, enabling data-driven negotiations, improving delivery performance, reliability, responsiveness, and information sharing.

Analytics Advantage – Part 2B

The mandatory adoption of ELDs provides all kinds of data that can be used to improve driver performance in many ways. Analytics can also be used to improve route and service planning, optimizing the cost of service tradeoffs.

Analytics Advantage – Part 2A

How shippers and carriers can leverage analytics to improve the performance of their private fleets using near-real-time shipment location data, combined with customer orders, routing plans, electronic proof-of-delivery data, service/work order schedules, vehicle inspection/maintenance data, and other sources of data.

Analytics Advantage – Part 1B – Democratization

Implementing advanced analytics requires data science expertise, analytic technology, data integration, data-wrangling capabilities, and ideally the ability to rapidly implement advanced analytics. Some transportation and logistics solution providers have these capabilities, so their customers don’t have to acquire them. Here we discuss how to assess whether or not a logistics software solution provider has the right capabilities.

Analytics Advantage – Part 1A: Democratization

We explore the kinds of data being produced by transportation and logistics systems, how that data can be used to create a data-driven enterprise, and the substantial obstacles to achieving an analytic advantage.

Agile Demand-Supply Alignment – Part 2E

A discussion of requirements for Agile Demand-Supply Alignment (ADSA) solutions for demand management (demand-side visibility, time-phased views, POS and channel data visibility, order pegging, demand sensing, retail planning capabilities), and analytic capabilities (e.g. supplier performance, carrier performance, lead-time analytics, total landed cost optimization.)

Agile Demand-Supply Alignment – Part 2B

A framework for understanding Agile Demand-Supply Alignment solutions. We present questions to ask solution providers about how they detect, contextualize, prioritize, predict, and prescribe solutions for demand-supply imbalances.

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