Cybersecurity and Risk
Delivery giant Yamato uses data science to drive growth
The pandemic accelerated the growth of e-commerce globally as consumers turned to their computers and smartphones to buy goods. Take Tokyo-based Yamato Holdings, for example. The door-to-door delivery provider handled nearly 300 million more parcels in fiscal year 2021 than in 2020 and about 180 million more parcels in fiscal year 2022 than in 2021.1
Maintaining operational excellence while dealing with a surge in orders is a key pillar of Yamato’s digitization strategy—one that relies primarily on data science and scientists.
The role of data science
Norihiko Nakabayashi, the executive officer responsible for Yamato’s digital transformation promotion, describes the growth of the data science role inside the company: “Three years ago, we had no data scientists at Yamato,” he says.
Today, the role is essential to the company’s operations. Nakabayashi outlines the four layers of data science within the company:
Managing cloud services and other data infrastructure
Collecting and organizing data
Conducting analysis and deriving insights—often using artificial intelligence (AI)
Applying gained insights to individual business units
This structure forms a pyramid and allows Yamato to work with the vast amounts of data that flow through its digital pipes daily—from where customers prefer to pick up their packages to the number of parcels sitting in its warehouses to how long it takes couriers to reach their destinations.
Positive feedback loop
Yamato’s executives can then turn this information into a strategy for growth. Rather than relying on experience and gut feel to make decisions, they’re “building a loop that returns the data to the front lines,” Nakabayashi says.
This positive feedback cycle is crucial to building a 21st-century logistics operation, one that puts end users first. As Yamato expands into business-to-business (B2B) services, it must cater to increasingly diverse and unique customer needs.
“Our B2B operation is the epitome of our digital capabilities,” Nakabayashi says. “For instance, when we deliver specialty medical products, we have to monitor their temperature and location in real time. This is mission-critical stuff. It is not a ‘nice-to-have’ for our clients.”
Ask the data concierge
Helping Yamato’s enterprise customers manage their own inventories via efficient and hyper-responsive delivery networks is a broader application of the company’s data science upgrades. “Our efforts allow us to map out optimal routes, making sure our customers get their goods when they need them,” Nakabayashi says.
Applying this kind of granular agility to the 2.2 billion parcels the company delivers annually, across an army of more than 180,000 employees and a fleet of 54,000 vehicles, is no easy feat. To help, Yamato has created the role of data concierge in its IT department, falling within the second layer of the data science pyramid.
“The role of the data concierge is to find important data sets that are not in our existing database,” Nakabayashi explains. “They handle data sets, which are disorganized and dispersed, put them together in an integrated way, and cleanse them so the requester is able to use them effectively and in a way that makes sense.”
Streamlining processes, saving time
Yamato Holdings has integrated eight operating companies into one and built a digital platform that serves all business units. ServiceNow solutions have been a major component of that business transformation, helping Yamato deliver innovation and exceptional customer service.
ServiceNow IT Service Management (ITSM) helps ensure smooth and seamless flow of work, tasks, and information between different layers of Yamato’s data management pyramid.
Deployment of ITSM has decreased the time the concierges need to both collect and package the data they deliver up the pyramid. The process, which used to take about one month, can now be done in about two weeks.
This means data concierges can handle several hundred requests from business units per month instead of only dozens, according to Nakabayashi.
Improving efficiency, freeing workers
In addition, the company can forecast demand up to three months in advance. This allows it to place the optimal number of workers and other resources in each fulfillment center, reducing waste and overlap.
When Junior Data Concierge Sakiko Imai joined the company more than a year ago, she found it challenging to achieve a sufficient depth of analysis given the huge volume of data Yamato has amassed.
Improvements made since then have helped her and her colleagues handle inquiries from analysts and better manage data workflows, boosting the team’s efficiency. Imai credits ServiceNow solutions with centralizing the flow of requests.
“We can now respond to inquiries through a single channel, reducing the workload on both the administrator and user of the data,” she says. “This frees up resources for other tasks.”
Charting a data-centric future
Looking ahead, Nakabayashi and his team will continue developing more seamless methods of data integration. They plan to automate much of the work of the data concierges, further freeing their time to engage in deeper consultation with business units and to formulate strategy.
This can help the company cultivate a more holistic, data-driven culture in which people like Imai, who are responsible for handling data, work side by side with business decision-makers at every turn.
Part of this entails the creation of digital twins, or simulations, in which Nakabayashi’s team can test hypotheses about certain business decisions and assess potential outcomes.
Connecting ServiceNow IT Operations Management with ITSM helps Yamato automate its service operations. It also allows the company to predict and resolve service incidents before failures occur.
“ServiceNow IT Service Management is critical to the whole endeavor of our data scientists,” Nakabayashi sums.
Find out more about how ServiceNow can help your organization embrace speed and agility through automation.
1 Statista, Number of parcels handled by Yamato Holdings Co., Ltd. from fiscal year 2013 to 2022, May 12, 2022
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