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FedEx Works to Monetize their Big Data

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Summary

FedEx is working to monetize the large amounts of data they collect from the 17 million packages they ship per day. FedEx Dataworks uses data science and machine learning to improve the shipping process and make deliveries more efficient. They are using predictive analytics to intervene in and improve the success rate of shipments, such as those of the COVID-19 vaccines. They are also looking to leverage their customers' data to better predict demand and returns, and to help with international shipments, fraud prevention, and more. This data can benefit both FedEx and their customers.

Q&As

How does a network effects business model work?
A network effects business model allows a company to gain more value as more companies use its products or services. The value of the offering rapidly increases because each additional user increases the value of the network.

What data is captured by Google and Twitter and how do they monetize it?
Google and Twitter mainly capture data through targeted advertising and monetize it through targeted advertising.

How is FedEx using data science and machine learning to improve their services?
FedEx is using data science and machine learning to help make shipping more efficient. The richness of FedEx’s data comes from the 17 million packages they ship per day around the globe. Each shipment is scanned many times as it moves from origin to destination. FedEx enriches this data with weather and traffic data. FedEx is using predictive analytics to improve the flow of goods through their network and make themselves into a more reliable carrier.

What was FedEx Surround's first use and what was the success rate?
FedEx Surround's first use was in tracking critical, sensitive shipments of COVID-19 vaccines as they moved from manufacturers and distributors to medical centers across the U.S. In the first year of COVID-19 vaccine distribution, FedEx delivered approximately 300 million doses throughout the U.S. with the help of predictive analytic tools and had a 99.91 success rate on getting vaccines delivered on the day of commit.

How can FedEx and their customers benefit from better forecasting and data analysis?
By better forecasting demand and returns, customers can save on shipping by injecting the package at the right time and place into the FedEx delivery network. For example, seven-day ground is cheaper than express deliveries. The right injection point is not necessarily the FedEx sort center closest to the customer. Traffic and congestion might suggest injecting packages into a more distant sort center will actually improve the odds of an on-time delivery. Over time, machine learning will be leveraged so that forecasts will get better. FedEx will also benefit from stickier customer relationships.

AI Comments

👍 This article does a great job of illustrating how FedEx leverages Big Data to improve their services and offer more value to their customers.

👎 This article fails to address any potential drawbacks of using Big Data for shipping and delivery services.

AI Discussion

Me: It's about Fedex trying to monetize their big data. They're using predictive analytics and machine learning to make their shipping more efficient, and they're looking for ways to use their customers' data too.

Friend: Wow, that's interesting. It sounds like Fedex is trying to create a bigger network effect business model to increase their value and stay competitive.

Me: Yeah, that's exactly it. It looks like they're hoping to use the data to help predict demand and returns, improve shipment success, and even prevent fraud.

Friend: That's really impressive. It seems like this is a great way for them to increase efficiency and stickiness with their customers. It could potentially help them save money on shipping too.

Action items

Research other companies that are leveraging Big Data to monetize their services.
Explore ways to use predictive analytics to improve the flow of goods through a delivery network.
Develop a plan to use customer data to help predict demand and returns in a joint planning process.

Technical terms

Network Effects Business Model: A business model in which the value of a product or service increases as more companies use it.
Big Data: A term used to describe large and complex datasets that are difficult to process using traditional data processing applications.
Predictive Analytics: The use of data and statistical algorithms to predict future outcomes.
SenseAware ID: A small Bluetooth tracking sensor that can be placed on a package.
White Glove Service Team: A team of professionals who provide specialized services such as delivery, installation, and setup.
API Framework: A set of programming instructions and standards for accessing a web-based software application or web tool.
Denied Party Screening: A process used to identify individuals or entities that are prohibited from engaging in certain activities, such as receiving goods or services.