How Did Coca-cola In Japan Use Data Warehousing To Improve Its Business Processes?

Decisions at the bear on of a push button

Coca-Cola Japan puts the buzz back in vending machine sales

by Karen D. Schwartz

Haruhiku Inagaki, president and CEO of the Hokuriku Coca-Cola Bottling Company (left), and Takehiko Ikeda, Concern Intelligent Solutions.

It�s 3 p.m. on a typical workday in Japan�the perfect time for an afternoon break. Y'all walk downward the hall to a large vending machine standing ready to dispense a multifariousness of hot and cold beverages. You make a option from nearly 30 available products, and soon you�re dorsum to work, drink in manus. You never stop to think that the car stocks your favorite beverage, dispenses your selection�the newest health drink�without fail and gives y'all the correct change automatically. That�s just to be expected, correct?

Backside that level of simplicity is a lot of hard work and conscientious planning past Japanese bottling companies, who have to decide which drinks will sell all-time in their machines while at the same time eliminating out-of-stocks and reducing equipment failures.

Calculation to those pressures is the fact that Japanese consumers are enervating newer, fresher and healthier drink choices, forcing companies to promote and distribute new products while creating shorter life cycles for existing products.

Such challenges have meant a decline in sales for a market that traditionally is highly profitable for bottlers. Subsequently all, the convenience of buying a single, chilled bottle of your favorite beverage instead of an entire case comes at a premium cost. At the same time, still, supermarkets and convenience stores in Japan offering greater selection and availability than vending machines tin can ever hope to offer, making these outlets attractive alternatives for choosy consumers.

So how does a successful bottling visitor ensure that its vending machines continue to turn a turn a profit in the highly competitive soft drinkable industry? The answer for Hokuriku Coca-Cola Bottling Company (HCCBC) is a solution from Teradata.

History of change

In 1998, Mikuni Coca-Cola Bottling Company, i of xv Coca-Cola bottlers in Japan, was the first to use a Teradata Warehouse to leverage the information each of its vending machines was already capable of gathering�unit of measurement sales, sellouts and mechanical failures. Before Mikuni implemented Teradata, no bottler had used this data, which was uploaded to a salesperson�s handheld terminal when he or she visited the location.

Japanese soft-drink market

SUPPLIERS
More than 10 major suppliers

MARKET SIZE
1.half-dozen billion cases per year

VENDING MACHINES 2.four million

NUMBER OF VENDING MACHINES CURRENTLY ON A WIRELESS NETWORK 20,000

PERCENTAGE OF SALES ATTRIBUTED TO VENDING MACHINES xl%

TOTAL Almanac SALES OF SOFT DRINKS US$42.1 billion

The information was taken back to a host estimator at the end of the day, except for when settlements and sales reporting were required.

Mikuni used the data to observe under-performing routes. With the new system in place, the vending machines showed cracking improvements in the book of sales per auto. Because of that success, the Coca-Cola Due west Nihon Company (CCWJ), the sole anchor bottler in Japan, adopted the same Teradata system.

It expanded upon this system using the key business concern indicator concept to measure the operational performance of vending machines, including such factors as out-of-stock rate, replenishment rate, rate of actual planned visits and the rate of unplanned visits.

Against these indicators, Teradata analyzes the data and reports to the headquarters staff and area managers well-nigh the performance of the vending machines along a specific route or in a sure area.

The main objective of the Mikuni and CCWJ systems was to abound sales with the least corporeality of operational costs, thus raising sales and functioning levels.

HCCBC realized the potential of this new arroyo to information analysis and decided to copy the Teradata system. Yet, the visitor knew it could further develop the system and use the data more effectively past leveraging fresh point-of-sale data from the machines and a �Column Management System,� a planning tool for column assortments.

�We had to find a way to larn a bully deal about our customers� preferences, including their lifestyles, values and reasons for selection,� says Haruhiku Inagaki, HCCBC�s president and CEO. Client preferences differ profoundly, he says, depending on occupation, gender or fifty-fifty time of day.

Inagaki believed the company needed to view every vending car as a �store� optimized for the needs of the consumers it serves. To accomplish this, the company had to transform customer data into intelligence, enabling the bottler to accept the right products in each vending machine at the right time to meet customer preferences.

Under HCCBC�s proposed Teradata Warehouse, data would be thoroughly analyzed in an effort to better sales and operational efficiency. Every bit envisioned, the solution would collect not only historical data simply also near real-time data that could then be transmitted via wireless connection to headquarters. Currently, data is collected one time a day and delivered to the headquarters via wireless connection. Automobile failures and out-of-stocks are reported to the headquarters in real fourth dimension from mobile phones hooked to the vending machines.

The initial stage of the project was rolled out in 2001. Information technology armed front-line managers�those responsible for specific vending machines�with a improve understanding of the customers in their specific market place, thus enabling them to serve those customers more than effectively.

Making a selection

On the technical side, the first step in the projection was to determine whether the company�south existing databases were upward to the chore.

HCCBC had been using a combination of an Oracle database and diverse business intelligence software tools to run its sales information analysis systems.

Just every bit the company�s forward-thinking vision took shape, it became clear that the existing combination of technology merely would not come across HCCBC�southward needs.

�(Our previous solution) didn�t take sufficient capability to analyze extensive data,� Atsumasa Shimizu, HCCBC CIO notes, �and equally we began considering the option of adding a wireless component to the mix, nosotros saw some real limitations.�

HCCBC executives selected a Teradata Warehouse running Teradata Database V2R5 on a 4900 NCR Server with Unix SVR4. The system, based at the company�south main data eye in the city of Takaoka, has plenty power to meet the company�s current needs and is fully scalable to satisfy its future needs.

The Teradata solution, combined with HCCBC�s existing Column Management System, will aid managers understand which products have sold well, enabling them to quickly conform the production mix to avoid out-of-stocks and respond to market trends.

That�s a meaning change from the previous arrangement, where each salesperson performed his or her own column (production assortment) assay. Past marrying the two, managers can utilise the data to achieve optimum stock assortment for each individual vending machine.

�Now, nosotros can look directly into the vending car as it is prepare up or stocked and see how space is being utilized, and we tin can evidence how to change columns to eliminate out-of-stocks and increment sales of other products,� Inagaki explains. �We tin can even show what will happen when yous replace a production or swap out products. No affair what data we collect, the programme can analyze the results, which will help tell us what works best in a given state of affairs.�

The technique uses an iterative process of developing assumptions for optimizing individual stores, column array and space resource allotment, and verifying the effectiveness of inventory changes. Every bit the speed of the process increases, the system will permit constant updating of vending machine status to respond to consumer changes and maintain product freshness.

It will also allow managers to react more quickly to a multifariousness of potential problems. The new approach provides detailed product information, such every bit time and date of each auction, when a product sells out, whether someone was short-changed or whether some office of the auto is malfunctioning.

In any of these cases, an alert is triggered and the automobile immediately sends a written report to the data center via wireless transmission. The overarching goal is more than effective noesis sharing.

Takehiko Ikeda, the former CIO of the Coca-Cola Japan Company and current BI consultant to HCCBC, says, �We wanted to use data warehousing as a tool to transform the visitor into a �noesis creation company� by enabling effective sharing of knowledge or intelligence to operate the vending business.�

Hokuriku Coca-Cola Bottling Visitor

RANKING Amid COCA-COLA JAPAN BOTTLERS No. 1 in sales growth in 2003, up from No. 2 in 2002

Almanac SALES IN CASES xxx million

TOTAL NUMBER OF VENDING MACHINES 66,000

VENDING MACHINES ON WIRELESS NETWORK (2003) three,500

PERCENTAGE OF SALES ATTRIBUTED TO VENDING MACHINES xl%

ANNUAL SALES United states$5.45 billion

EMPLOYEES i,500

FACTORIES ii

BRANCHES 40

DISTRIBUTION CENTERS six

Enjoying the results

In 2002, HCCBC conducted a program to test its new Column Management Organisation. HCCBC placed all of its vending machines in Nagano, Japan, on a wireless network. The company gathered near real-time POS data nerveless from each machine.

The results were staggering. Not but did sales increase 10% overall, simply overtime and other associated costs decreased 46%. Additionally, the number of vending machines that could be served per sales-person increased by as much as 42%.

Other benefits�many of them overall goals for company growth�have included fresher products, better customer service, increased brand sensation and higher margins due to a greater production turnover and increased sales.

The pilot test was so successful that a company-wide deployment is now planned, with the active data warehouse component and expanded online vending capabilities beyond the Nagano region. Currently, almost three,500 of the company�s 60,000 vending machines are networked and using the column management solution; eventually, Inagaki would like to see all of HCCBC�s vending machines operate online. In total, the Coca-Cola Bottlers network in Japan includes more than 1 million machines, and Inagaki is hopeful that they, also, will someday be networked.

Inagaki envisions that the point-of-sale data from equally many of Japan�south Coca-Cola vending machines as possible be used not only to back up the sales staff, merely also to link to a country-wide supply concatenation management project now being undertaken. �That�s what�s necessary to maintain competitive reward and customer satisfaction�something every visitor needs to sustain future growth.�

Editor'southward Addendum

Japan has approximately ane vending machine for every 20 people. The more than 5.5 one thousand thousand machines primarily dispense beverages (soda, java, teas, beer), but vending machines also dispense a wide variety of other items including cigarettes, flowers, water ice foam, gifts, and toilet paper. Japanese phone call vending machines jido-hanbaiki (Jido means automatic, hanbai ways vending, and ki is machine). Check http://www.isop.ucla.edu/eas/japan/2minute/vendingmachines.htm .

Update: In August 2005, approximately v,000 out of 60,000 vending machines are on the Hokuriku Coca-Cola Bottling Company wireless network. The Teradata database is being expanded to 1.6TB. The vending machine organisation described in the case will exist incorporated in Coca-Cola Grouping Japan's new integrated vending machine system supported by Teradata. The new arrangement will include Coca-Cola West Nippon and other bottlers of Coca Cola in Japan. Hokuriku Coca Cola Bottling Visitor's information warehouse will continue to serve other needs of Hokuriku Coca Cola.

Some Questions for Further Analysis and Discussion

What is the purpose of the data warehouse?
What is a wireless network? How does it facilitate computerized conclusion support?
Is the enterprise data warehouse function of a data-driven Decision Support Organization? Why or why not?
Is the Column Management System a DSS?
What determination support technologies were used?
Does the data warehouse support any transaction processing?
What is the major benefit of the enterprise data warehouse (EDW)? Why?
Should other soft potable vendors create this type of conclusion support capability? Is it viable in Europe, United states? Why or why not?
What bug or difficulties practise yous anticipate with the utilize of this type of determination support solution?

Please cite every bit:

Schwartz, K. D., "Decisions at the bear on of a button", August 19, 2005, at URL DSSResources.COM.

Karen D. Schwartz is a Washington, D.C.-based concern and technology author. Her piece of work has appeared in publications such as Information Week, CIO, Business organization ii.0 and Mobile Computing & Communications. Photo by Alex Hayden.

Dan Conway, Managing director, Public Relations, Teradata, a segmentation of NCR Corporation, provided permission to publish this case study at DSSResources.COM on July 20, 2005. Conway's email accost is dan.conway@ncr.com. This case study was posted at the Teradata website in 2004 and appeared in Teradata Mag, Vol. 4, No. 1, 2004. This case study was posted at DSSResources.COM on Friday, August nineteen, 2005.

Case study � 2004 NCR Corporation. Used at DSSResources.COM by permission. Product names and trademarks may be trademarks and/or registered trademarks of their respective companies.

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