A Vacation Lesson: Mastering Logistics with Analytics
Okay, so my vacations don’t necessary seem like other folks’ vacations. Yes, we relax. Yes, we spend too much money. Yes, we eat too much food. But for some reason, unusual learning opportunities pop up during our vacations, and this year’s vacation was no different. This year’s vacation theme was… logistics.
Our logistics foray started by watching the artsy-fartsy movie “The Lunchbox.” I hate artsy-fartsy movies, but my wife insists on watching them on vacation. The movie was excellent. However, I was totally mesmerized by the lunchbox delivery system that was a featured part of the movie. The lunchbox delivery system, called dabbawalas, delivers hot lunches from homes and restaurants to people at work in Mumbai, India. The lunchboxes are picked up mid morning, delivered to husbands at noon using bicycles and railway trains, and returned to the originating source in the afternoon.
The dabbawallahs are extremely efficient; delivering up to 250,000 lunches daily and they rarely make a mistake. The delivery system is a very complicated dance of many elements, including the railway system in Mumbai. And it’s all done without the services of computers, iPhones or even an operating manual! Every step of the process, even the return address for each lunchbox, is memorized by the dabbawallahs.
But watching the movie “The Lunchbox” wasn’t enough. Next we made a journey to Sarasota, FL to check out the Ringling Bros Museum. My favorite part was the “Day in the Life of the Circus.” This amazing display showed all of the logistical complexities of setting up and taking down the circus…done in miniature (see Figure 1).
The Ringling Bros Circus traveled with 1,300 workers and performers, and over 800 animals. In less than four hours time (starting when the first of three trains arrived at 3am), the workers would have set up the Big Top’s six center poles, 74 quarter poles, 122 sidewall polls, 550 stakes, 26,000 yards of canvas, three rings, four stages, a hippodrome track, and seats for 15,000 people. The first tent that went up was the mess tent, so that the battery of cooks could start cooking the 3 meals necessary to feed the workers and performers!
In a single season, the circus performed in 150 towns and cities. Fewer than 20 of the venues were more than a single day which meant setting up AND tearing down the enormous circus in a single day!
Big Data and Logistics
Logistics optimization has historically separated winners from losers in the world of commerce. Just like Ringling Bros mastered the art of logistics to bring “The Greatest Show On Earth” to cities across the United States, companies in industries such as retail, travel, entertainment, healthcare, consumer goods, manufacturing and hospitality must master logistics to:
- Improve the predictability of on-time delivery of goods and services, while
- Reducing operational costs and eliminating operational inefficiencies, in order to
- Provide a differentiated, “delightful” customer experience
Think of the strategic role that logistics plays in Amazon’s business model (i.e., free two-day delivery and even same-day delivery in select zip codes). Amazon has mastered logistics in order to fulfill their customer promise to get make the delivery of products easier than driving to the store! Select what you want to buy on the Amazon website or mobile app, pay with [1-Click] and your order magically appears within two days or less at your doorstep. Or better yet, just yell at Amazon Alexa what you want and the user experience is even more seamless.
To master logistics, Amazon isn’t afraid to try new things. For example, the stocking in Amazon’s Prime Now locations looks random…because it is random! The items are stocked wherever is closest and fastest, and the location of the items is captured so that the analytic algorithms can optimize the picking process. The random stocking actually accelerates the picking process…with the help of analytics. Amazon couples the real-time, detailed stocking data with advanced analytics to get items out the door almost immediately after an order is placed in their Amazon Prime Now locations. And Amazon still isn’t satisfied, as they hope that drone delivery can actually reduce the delivery process to 30 minutes or less.
Monetizing Your Logistics Data
Tomorrow’s logistics battleground will likely be waged in how logistics organizations leverage the “commerce of the world” data to create new revenue or monetization opportunities.
“Information about the package is as important as the package itself.” -Frederick “Fred” W. Smith, Founder and CEO of Federal Express
Fred Smith said it well – back in 1978 – that the data about the package might be more valuable than the package itself. There is a bounty of analytic insights that can be gathered from the detailed logistics data of moving products from manufacturer and retailer to the end consumer, including:
- Economic growth by geography and industry
- Rapidly developing (and declining) markets and geographies
- Financial health of a company
- Market share changes by product category and geography
- Promotional effectiveness
- Product problems (by the number of returns)
- Real-time changes in traffic patterns
- Real-time weather conditions
- Road surface conditions (potholes, missing lines, bumpy surfaces)
For example, logistics companies like DoorDash and GrubHub know as much about the success of a restaurant as anyone, as they can track not only what was ordered and by whom, but can also track re-orders by customers (which is the best measure of customer satisfaction). They know what types of foods what types of customers like, and when (time and dates) they prefer to place orders.
Monetizing Your Organization’s Data
Opportunities to exploit an organization’s data are only limited by the organization’s imagination, and willingness to experiment, fail and learn! However the real “monetization” event won’t be centered on selling one’s data. Instead the “monetization” event will likely be driven by monetizing the insights derived from the data; insights that can be monetized by 1) understanding the decisions that key market players are trying to make and 2) creating and packaging analytic insights to help those market players make better and more timely decisions.
As we discuss in our Big Data Business Model Maturity Model (see Figure 2), organizations should not focus on monetizing their data by selling their data (“value in exchange” to quote Adam Smith). Instead, organizations should focus on monetizing the insights gleaned from that data to improve today’s and tomorrow’s key operational, customer and market decisions (“value in use” to again quote Adam Smith).
Identifying, validating and focusing on the most important decisions that customers (and prospects) are trying to make to optimize their business models can identify monetization opportunities for new products, new services, new markets, new audiences, new channels and new partnerships.
“What Harvard learned by studying India’s lunchbox delivery system”
Stupendous! Amazing! Ringling Museum In Sarasota Does Circus Tradition Proud
The Howard Bros. Circus
How Amazon Delivers Packages in Less Than an Hour