Prepare an in-depth analysis of three case studies. Here are some guidelines:
This is an individual assessment, which is apart from your course score. It requires effort and
Answer all the questions listed below for each case.
The ‘answers’ to the questions are best formulated by reviewing the case and the reading
The questions are worded to help you apply the readings to the case, so don’t limit yourself
to the case’s terminology and perspective. The best analysis will abstract the case content by
applying the reading materials to draw broader lessons about the material
Case Study1: American Water Keeps Data Flowing
American Water, founded in 1886, is the largest public water utility in the United States. Headquartered in
Voorhees, N.J., the company employs more than 7,000 dedicated professionals who provide drinking water,
wastewater and other related services to approximately 16 million people in 35 states, as well as Ontario
and Manitoba, Canada. Most of American Water's services support locally managed utility subsidiaries that
are regulated by the U.S. state in which each operates as well as the federal government. American Water
also owns subsidiaries that manage municipal drinking water and wastewater systems under contract and
others that supply businesses and residential communities with water management products and services.
Until recently, American water's systems and business, processes were much localized, and many of these
processes were manual. Over time, this information environment became increasingly difficult to manage.
Many systems were not integrated, so that running any type of report that had to provide information about
more than one region was a heavily manual process. Data had to be extracted from the systems supporting
each region and then combined manually to create the desired output. When the company was preparing to
hold an initial public offering of its stock in 2006, its software systems could not handle the required
regulatory controls, so roughly 80 percent of this work had to be performed manually. It was close to a
Management wanted to change the company from a decentralized group of independent regional businesses
into a more centralized organization with standard company-wide business processes and enterprise-wide
reporting. The first step toward achieving this goal was to implement an enterprise resource planning (ERP)
system designed to replace disparate systems with a single integrated software platform. The company
selected SAP as its ERP system vendor.
An important step of this project was to migrate the data from American Water's old systems to the new
platform. The company's data resided in many different systems in various formats. Each regional business
maintained some of its own data in its own systems, and a portion of these data was redundant and
inconsistent. For example, there were duplicate pieces of materials master data because a material might be
called one thing in the company's Missouri operation and another in its New Jersey business. These names
had to be standardized so that every business unit used the same name for a piece of data. American Water's
business users had to buy into this new company-wide view of data.
Data migration entails much more than just transferring data between old and new systems. Business users
need to know that data are not just a responsibility of the information systems department: the business
"owns" the data. Business needs determine the rules and standards for managing the data. Therefore, it is
up to business users to inventory and review all the pieces of data in their systems to determine precisely
which pieces of data from the old system will be used in the new system and which data do not need to be
brought over. The data also need to be reviewed to make sure they are accurate and consistent and that
redundant data are eliminated.
Most likely some type of data cleansing will be required. For example, American Water had data on more
than 70,000 vendors in its vendor master data file. Andrew Clarkson, American Water's Business
Intelligence Lead, asked business users to define an active vendor and to use that definition to identify
which data to migrate. He also worked with various functional groups to standardize how to present address
One of the objectives of American Water's data management work was to support an enterprise wide
business intelligence program based on a single view of the business. An analytical system and data
warehouse would be able to combine data from the SAP ERP System with data from other sources,
including new customer information and enterprise asset management systems. That meant that American
Water's business users had to do a lot of thinking about the kinds of reports they wanted. The company had
originally planned to have the system provide 200 reports, but later reduced that number by half. Business
users were trained to generate these reports and customize them. Most financial users initially tried to create
their reports using Microsoft Excel spreadsheet software. Over time, however, they learned to do the same
thing using SAP Business Objects Web Intelligence tools that came with the system. SAP Business Objects
Web Intelligence is a set of tools that enables business users to view, sort, and analyze business intelligence
data. It includes tools for generating queries, reports and interactive dashboards.
At present, American Water is focusing on promoting the idea that data must be "clean" to be effective and
has poured an incredible amount of effort into its data cleansing work—identifying incomplete, incorrect,
inaccurate, and irrelevant pieces of data and then replacing, modifying, or deleting the "dirty" data.
According to Clarkson, just as water treatment plants have measurements and meters to check water quality
as its being treated, data management needs to ensure the quality of data at every step to make sure the final
product will be genuinely useful for the company.
Case Study 1: American Water Keeps Data Flowing
1) How did implementing a data warehouse help American Water move toward a more
centralized organization? (1 Mark)
2) Give some examples of problems that would have occurred at American Water if its
data were not "clean"? (1 Mark)
3) How did American Water's data warehouse improve operations and management
decision making? (1 Mark)
Case Study 2: Driving Ari Fleet Management with Real-Time Analytics
Automotive Resources International®, better known as simply ARI®, is the world's largest privately-held
company for vehicle fleet management services. ARI is headquartered in Mt. Laurel, New Jersey and has
2,500 employees and offices throughout North America, Europe, the UK, and Hong Kong. The company
manages more than 1,000,000 vehicles in the U.S., Canada, Mexico, Puerto Rico and Europe.
Businesses that need vehicles for shipments (trucks, vans, cars, ships, and rail cars) may choose to manage
their own fleet of vehicles or they may outsource fleet management to companies such as ARI which
specialize in these services. ARI manages the entire life cycle and operation of a fleet of vehicles for its
customers, from up-front specification and acquisition to resale, including financing, maintenance, fuel
management, and risk management services such as driver safety training and accident management. ARI
also maintains six call centers in North America that operate 24/7, 365 days a year to support customers'
fleet operations by providing assistance regarding repairs, breakdowns, accident response, preventive
maintenance, and other driver needs. These call centers handle about 3.5 million calls per year from
customers, drivers, and suppliers who expect access to real-time actionable information.
Providing this information has become increasingly challenging. Operating a single large commercial
vehicle fleet generates high volumes of complex data, such as data on fuel consumption, maintenance,
licensing, and compliance. A fuel transaction, for example, requires data on state taxes paid, fuel grade,
total sale, amount sold, and time and place of purchase. A simple brake job and preventive maintenance
checkup generates dozens of records for each component that is serviced. Each part and service performed
on a vehicle is tracked using American Trucking Association codes. ARI collects and analyzes over 14,000
pieces of data per vehicle. Then multiply the data by hundreds of fleets, some with up to 10,000 vehicles,
all operating simultaneously throughout the globe, and you'll have an idea of the enormous volume of data
ARI needs to manage, both for itself and for its customers.
ARI provided its customers with detailed information about their fleet operations, but the type of
information it could deliver was very limited. For example, ARI could generate detailed reports on lineitem expenditures, vehicle purchases, maintenance records, and other operational information presented as
simple spreadsheets, charts, or graphs, but it was not possible to analyze all the data to spot trends and make
recommendations. ARI was able to analyze data customer by customer, but it was not able to aggregate
data across its entire customer base.
For instance, if ARI was managing a pharmaceutical company's vehicle fleet, its information systems could
not benchmark that fleet's performance against others in the industry. That type of problem required too
much manual work and time, and still didn't deliver the level of insight management thought was possible.
What's more, in order to create reports, ARI had to go through internal subject matter experts in various
aspects of fleet operations, who were called "reporting power users." Every request for information was
passed to these power users. A request for a report would take 5 days to fill. If the report was unsatisfactory,
it would go back to the report writer to make changes. ARI's process for analyzing its data was extremely
In mid-2011, ARI implemented SAP BusinessObjects Explorer to give customers the enhanced ability to
access data and run their own reports. SAP BusinessObjects Explorer is a business intelligence tool that
enables business users to view, sort and analyze business intelligence data. Users search through data
sources using an iTunes like interface. They do not have to create queries to search the data and results are
shown with a chart that indicates the best information match. The graphical representation of results
changes as the user asks further questions of the data.
In early 2012, ARI integrated SAP BusinessObjects Explorer with HANA, SAP's in-memory computing
platform that is deployable as an on-premise appliance (hardware and software) or in the cloud. HANA is
optimized for performing real-time analytics and handling very high volumes of operational and
transactional data in real time. HANA's in-memory analytics queries data stored in random access memory
(RAM) instead of on a hard disk or flash storage.
Things started happening quickly after that. When ARI's controller wanted an impact analysis of the
company's top 10 customers, SAP HANA produced the result in 3 to 3 1/2 seconds. In ARI's old systems
environment, this task would have been assigned to a power user versed in using reporting tools,
specifications would have to be drawn up and a program designed for that specific query, a process that
would have taken about 36 hours.
Using HANA, ARI is now able to quickly mine its vast data resources and generate predictions based on
the results. For example, the company can produce precise figures on what it costs to operate a fleet of a
certain size over a particular route across specific industries during a certain type of weather and predict
what the impact of changes in any of these variables. And it can do so nearly as easily as providing
customers with a simple history of their expenditures on fuel. With such helpful information ARI provides
more value to its customers.
HANA has also reduced the time required for each transaction handled by ARI's call centers—from the
time a call center staffer takes a call to retrieving and delivering the requested information—by 5 percent.
Since call center staff account for 40 percent of ARI's direct overhead, that time reduction translates into
major cost savings.
ARI plans to make some of these real-time reporting and analytic capabilities available on mobile devices,
which will enable customers to instantly approve a variety of operational procedures, such as authorizing
maintenance repairs. Customers will also be able to use the mobile tools for instant insight into their fleet
operations, down to a level of detail such as a specific vehicle's tire history.
Case Study 2: Driving Ari Fleet Management with Real-Time Analytics
1) Why was data management so problematic at ARI? (1 Mark)
2) Describe ARI's earlier capabilities for data analysis and reporting and their impact on
the business. (1 Mark)
3) Was SAP HANA a good solution for ARI? Why or why not? (1 Mark)
4) Describe the changes in the business as a result of adopting HANA. (1 Mark)
Case Study 3: Zappos
Tony Hsieh’s first entrepreneurial effort began at the age of 12 when he started his own custom button
business. Realizing the importance of advertising, Hsieh began marketing his business to other kids
through directories, and soon his profits soared to a few hundred dollars a month. Throughout his
adolescence, Hsieh started several businesses, and by the time he was in college he was making money
selling pizzas out of his Harvard dorm room. Another entrepreneurial student, Alfred Lin,bought pizzas
from Hsieh and resold them by the slice, making a nice profit. Hsieh and Lin quickly became friends.
After Harvard, Hsieh founded Link Exchange in 1996, a company that helped small businesses exchange
banner ads. A mere two years later, Hsieh sold Link Exchange to Microsoft for $265 million. Using the
profits from the sale, Hsieh and Lin formed a venture capital company that invested in start-up businesses.
One investment that caught their attention was Zappos, an online retailer of shoes. Both entrepreneurs
viewed the $40 billion shoe market as an opportunity they could not miss, and in 2000 Hsieh took over as
Zappos’ CEO with Lin as his chief financial officer.
Today, Zappos is leading its market and offering an enormous selection of more than 90,000 styles of
handbags, clothing, and accessories for more than 500 brands. One reason for Zappos’ incredible success
was Hsieh’s decision to use the advertising and marketing budget for customer service, a tactic that would
not have worked before the Internet. Zappos’ passionate customer service strategy encourages customers
to order as many sizes and styles of products as they want, ships them for free, and offers free return
shipping. Zappos encourages customer communication, and its call center receives more than 5,000 calls
a day with the longest call to date lasting more than four hours. Zappos’ extensive inventory is stored in a
warehouse in Kentucky right next to a UPS shipping center. Only available stock is listed on the website,
and orders as late as 11 p.m. are still guaranteed next-day delivery. To facilitate supplier and partner
relationships, Zappos built an extranet that provides its vendors with all kinds of product information,
such as items sold, times sold, price, customer, and so on. Armed with these kinds of details, suppliers
can quickly change manufacturing schedules to meet demand.
Along with valuing its partners and suppliers, Zappos also places a great deal of value on its employee
relationships. Zappos employees have fun, and walking through the offices you will see all kinds of
things not normally seen in business environments—bottle-cap pyramids, cotton-candy machines, and
bouncing balls. Building loyal employee relationships is a critical success factor at Zappos, and to
facilitate this relationship the corporate headquarters are located in the same building as the call center
(where most employees work) in Las Vegas. All employees receive 100 percent company-paid health
insurance along with a daily free lunch.
Of course, the Zappos culture does not work for everyone, and the company pays to find the right
employees through “The Offer,” which extends to new employees the option of quitting and receiving
payment for time worked plus an additional $1,000 bonus. Why the $1,000 bonus for quitting? Zappos
management believes that is a small price to pay to find those employees who do not have the sense of
commitment Zappos requires. Less than 10 percent of new hires take The Offer.
Zappos’ unique culture stresses the following:
1. Delivering WOW through service
2. Embracing and driving change
3. Creating fun and a little weirdness
4. Being adventurous, creative, and open-minded
5. Pursuing growth and learning
6. Building open and honest relationships with communication
7. Building a positive team and family spirit
8. Doing more with less
9. Being passionate and determined
10. Being humble
Zappos’ Sale to Amazon
Amazon.com purchased Zappos for $880 million. Zappos employees shared $40 million in cash and
stock, and the Zappos management team remained in place. Having access to Amazon’s world-class
warehouses and supply chain is sure to catapult Zappos’ revenues, though many wonder whether the
Zappos culture will remain. It’ll be interesting to watch!19
Case Study 3: Zappos
1) Define SCM and how it can benefit Zappos. (1 Mark)
2) Explain CRM and why Zappos would benefit from the implementation of a CRM
system. (1 Mark)
3) Demonstrate why Zappos would need to implement SCM, CRM, and ERP for a
connected corporation. (1 Mark)
4) Analyze the merger between Zappos and Amazon and assess potential issues for
Zappos customers. (1 Mark)
5) Propose a plan for how Zappos can use Amazon’s supply chain to increase sales and
customer satisfaction. (1 Mark)
Purchase answer to see full