Big Data & Analytics Savi Supply Chain

4 Qualities That Make Netflix a Good Model for Supply Chain Visibility

Netflix has revolutionized the way we watch movies and TV shows. By embracing innovation and employing new technologies, it has made the process of picking and watching on-demand movies easy and inexpensive.

Innovative companies can follow Netflix’s model and transform their supply chain operations using some of the same technologies. How? A lot of the technology Netflix uses is similar to the technology today’s supply chain management needs as well.

By using real-time content, big data analytics, machine learning and a single system of engagement, supply chain leaders can manage risk, improve efficiency, eliminate blind spots by achieving true in-transit visibility of their supply chain.

4 Things Netflix Does That Can Improve Supply Chain Visibility

Here are four tools that Netflix successfully uses that can be a model for transforming your supply chain to have better real-time, in-transit visibility:

1. Streaming and real-time content

Netflix allows its subscribers to stream its content anywhere, anytime. With streaming video, customers can watch videos wherever they are with no limits on the amount of content they can access.

Streaming can be used in the supply chain as well – live streaming data, that is. With live streaming data, logistics managers can manage shipments in real-time, pinpointing their exact location and collecting data about shipments’ status and condition as well.

Companies can track shipments using a range of data sources, including GPS, sensors, telematics, AIS, weather, traffic, and mobile phones. Collecting real-time information allows companies to not only view and track their shipments end-to-end at any time across their supply chain network but also to optimize their supply chain operations.

2. Big data analytics

Netflix takes the data that it collects from its users to understand patterns. Then, using machine learning algorithms, it predicts what shows and movies people will want to watch next. This feature saves customers’ effort searching, and generates more revenue.

Companies can apply the same concept to logistics. Supply chain managers can combine Internet of Things (IoT) and big data with machine learning algorithms to provide predictive and prescriptive analytics.

But instead of movie preferences, supply chain pros can analyze patterns based on the efficiency of transportation lanes, cost, carrier performance, risk, and other relevant factors. Applications predict and recommend solutions to prevent supply chain disruptions. These insights provide end-to-end visibility across the supply chain network.

3. Single system of engagement

Netflix’s entire database is right at its customers’ fingertips. Viewers can easily switch between hundreds of movies and TV shows across a range of genres. The interface for comparing options and looking at titles and series is simple and easy to use, within a single system of engagement.

By the same token, logistics teams should be able to easily locate all information about every single shipment so that they can quickly make decisions.

There should be a single system of engagement that displays every route in the supply chain network so that companies can see the status of all active shipments at a glance. That way, supply chain managers can quickly identify those shipments at risk of missing their scheduled arrival time.

By tracking shipments in real time, the system accurately predicts the arrival time of inbound, intracompany, and customer shipments.

4. Innovative technology

Before Netflix, streaming video was not popular or affordable. Netflix completely disrupted the DVD rental market and put Blockbuster out of business when it failed to adapt.

Likewise, supply chain leaders have started to transition from using barcode scanning, milestone tracking, TMS, and other legacy technologies to capturing real-time information and achieving global in-transit visibility.

The implementation of IoT, big data, machine learning, and predictive and prescriptive analytics is revolutionizing supply chain management. These new technologies are improving estimated arrival time accuracy, increasing cross-docking efficiency, and reducing transportation costs.

This post has been updated; it was originally published in July 2016. 

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