Analytics Case Study: Standard Coffee Company

DNSC 6290

DATABASE & WEB ANALYTICS

PROF. DAVID YENIGUN

Brendan Burns Anil Cheerla

Lauren Dufrene Khoivu Nguyen

October 17, 2011

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TABLE OF CONTENTS Ov  erview ..................................................................................................................................................................................... 3

 History ..................................................................................................................................................................................... 3

 Products and Services ....................................................................................................................................................... 4

 Competitors ........................................................................................................................................................................... 4

An  alytical Assessment ........................................................................................................................................................... 5

 Data Sources ......................................................................................................................................................................... 5

 Non‐Transactional Data ................................................................................................................................................... 6

 Current Analytics Capability .......................................................................................................................................... 6

Re  quired Infrastructure ........................................................................................................................................................ 7

 Transactional and Non‐Transactional Data Analysis .......................................................................................... 7

 Internal Analytics and Data Mining ............................................................................................................................. 8

 Reports .................................................................................................................................................................................... 8

Da  ta Warehouse and Data Marts ...................................................................................................................................... 8

 Data Warehouse Design Considerations ................................................................................................................... 8

Da  ta Marts .............................................................................................................................................................................. 9

 Customer Service ........................................................................................................................................................... 9

 Route Service Representatives/District Managers ........................................................................................ 10

 Distribution Centers ................................................................................................................................................... 10

 Marketing ........................................................................................................................................................................ 11

 Revenue/Profit Management.................................................................................................................................. 11

 Cost Management ........................................................................................................................................................ 12

On  line Presence ...................................................................................................................................................................... 12

 Website Audit ..................................................................................................................................................................... 13

W  eb Analytics Implementation .................................................................................................................................. 14

 Website Design ............................................................................................................................................................. 14

 Impact Assessment ............................................................................................................................................................... 14

 Deployment Plan .................................................................................................................................................................... 15

onclusion ................................................................................................................................................................................ 17 C

 

 VERVIEW O

 

Standard Coffee Service Company (hereafter referred to as Standard Coffee) is a privately held

company and has emerged as a leader in the national Business-to-Business (B2B) distribution of beverage

products and services. As the third largest company in the industry, Standard Coffee provides a single

point of delivery for brewed beverages to offices, restaurants and food service organizations. The

company’s customer demographic consists of 80% professional single-location firms (e.g. law firms),

% hotel chains, and 10% fast food service chains (Cox). 10

HISTORY  

Standard Coffee was founded in 1919 by William B. Reily, as a distribution point for selling

Luzianne brand coffee and teas. Headquartered in New Orleans, the company grew to include supply

chains throughout the contiguous United States. Though its roots began in the home delivery of coffee

and other household products, Standard Coffee has shifted its emphasis to business marketing, and has

diversified its product offerings to include teas, filtered water, beverage condiments, and brewing

systems. Standard Coffee’s current network includes distribution centers in Los Angeles, Denver,

Lubbock, New Orleans, Knoxville, Tampa and Baltimore (Standard Coffee Service Company).

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 Fig1: Standard Coffee network 

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 PRODUCTS AND SERVICES

Standard Coffee markets and distributes coffee, tea, brewers and water filtration systems. Its

coffee offerings include Standard brand names as well as gourmet products (Javarama, Luzianne, Peets

Coffee, Caribou Coffee, Green Mountain Coffee, Starbucks, and Barnie’s). Its single cup products

include Javarama, Flavia, and Green Mountain Coffee. The company’s tea brands include Luzianne Tea,

Bigelow, Golden Leaf and Arizona. In addition to its beverage products, Standard Coffee also distributes

creamers and sweeteners, juices and drink mixes. Standard’s subordinate companies include Relyant

Coffee Equipment Services, a stand-alone business dedicated to the installation, maintenance and repair

of brewed-beverage and water filtration equipment, and Standard Direct, a service distribution program

r remotely located businesses. fo

COMPETITORS

The relatively small number of national competitors demonstrates the niche market which 

this business occupies.  However, this may also reveal potential markets which have not yet been 

fully accessed by Standard Coffee’s competitors, revealing a strong opportunity for success with an 

expanded analytics capability.

Company Footprint Service Type

National Coffee Service & Vending National Office Filter Fresh National Office, Residential Highland Estates Coffee National Office Great American Coffee Company National Office OfficeCoffee National Office First Choice Services National Office Hubbard & Cravens Coffee Co National Office First Choice Services Regional Office Your Choice Office Regional Office

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A NALYTICAL ASSESSMENT 

Although Standard Coffee faces a fairly small competitive base, competition to obtain new

customer leads and maintain customer loyalty is fierce. The shifting dynamics of the marketplace

requires the company to constantly explore new capabilities to expand its customer base and deliver

excellent customer service. To meet this need, Standard Coffee must maximize its analytics capability to

predict customer leads, improve lead scoring, and retain its most profitable customers, through the use of

a mix of mobile, Web and social technologies, for both field and office-bound sales operations.

Research has also shown solid evidence that investing in analytics generally pays off; IDC found

that projects aimed at improving production had an ROI of 277%, those aimed at financial management

had an ROI of 139%, and those focused on customer relationship management had an ROI of 55%

(Davenport and Harris, Competing on Analytics: The New Science of Winning). This high rate of return

emphasizes the profitability which Standard Coffee could derive from a concerted analytics

plem ntation effort. im e

DATA SOURCES 

         There is a wealth of data that Standard Coffee can utilize in performing analytics to more

effectively run its business. Our assessment will show numerous opportunities that Standard Coffee can

use to dramatically improve its market prowess.

TRANSACTIONAL DATA 

         Currently, Standard Coffee utilizes IBM’s AS/400 as its Enterprise Resource Planning (ERP)

system (Cox). The company’s transactional data includes purchasing, sales, shipping and receiving,

payables and receivables, inventory management, and payroll. Because these business functions are

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performed within the ERP system, the resulting data is automatically captured, stored, and organized as

nsa ons occur. tra cti

NON‐TRANSACTIONAL DATA  

INTERNAL NON­TRANSACTIONAL DATA 

  Standard Coffee collects a portion of its internal non-transactional data, such as customer contact

information, through the ERP system. However, most is derived from other sources, such as customer

satisfaction surveys, and Route Service Representatives (RSR). RSRs serve as the face of the company to

customers, with responsibilities ranging from order delivery to providing on-the-spot customer service

(Cox). The company also utilizes its website to collect data through customer interactions, such as

estimate requests, service feedback, and account creation.  

EXTERNAL NON­TRANSACTIONAL DATA: 

  Standard Coffee’s also utilizes external data, which is collected through third parties. The

company employs third party consultants to conduct analytics relating to the company’s website, email

blasts and direct mail activities, as well as Mongoose Metrics to track customer service phone

communications data. The main source for product analytics is the manufacturers themselves. Standard

Coffee relies heavily on the extensive R&D and analytics capabilities of its vendors, to track emerging

and the product’s customer base.  market trends

CURRENT ANALYTICS CAPABILITY 

Our assessment places Standard Coffee as a Level Two capability firm (Davenport and Harris).

There are extensive opportunities for growth and diversification in Standard Coffee’s customer base and

business operations. The finance department mainly uses transactional data gathered by the ERP system

to perform analysis and forecasting. Although analytics is employed to a much greater extent within the

company’s marketing effort, an integrated internal analytics strategy would produce tremendous growth

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opportunities. Additionally, the internal analytics capability of the firm is limited to two full-time

employees within the marketing department, whose efforts are solely devoted to furthering that

department’s efforts (Cox). These individuals create reports, work with the third-party analytics provider,

and produce ad-hoc queries on request to the Marketing Director (Cox). Currently, Standard Coffee’s

analytics efforts primarily focus on new customer lead generation, with a minimal effort in using analytics

to retain current customers through customized marketing and product offerings or enhanced customer

services.

As a B2B entity, Standard Coffee utilizes marketing data and promotions it receives from its

vendor partners, relying on their more extensive capital and staffing to conduct market trend research. In

addition, analytics is not currently employed to improve customer care services, identify customer

cost/profitability or to profile loyal customers. There has been little integration of internal non-

transactional and transactional data housed in the ERP system. Our interview indicated that there was not

a high level of collaboration or sharing of knowledge and resources between finance and marketing, or

with other departments (Cox). The largest hurdle faced by the company is a disinterested leadership. The

company’s executives are not active in seeking the application of analytics to the company’s business

practices, beyond the scope of marketing and finance efforts (Cox).

R

TRANS N ‐T D A  

EQUIRED INFRASTRUCTURE 

ACTIONAL AND  ON RANSACTIONAL  ATA  NALYSIS

  Standard Coffee’s transactional data is currently available in data marts and is available to 

internal business processes such as finance, accounting, marketing, and sales, but, as stated earlier, 

is not being actively applied to internal processes (Cox).  Non‐transactional data should be sanitized 

and saved into an internal data mart, to allow for the use of it by all departments, and thereby 

integrating internal business processes, and informing management decisions.     

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INTERNAL ANALYTICS AND DATA MINING  

  Standard Coffee can implement data mining to profile and identify its most profitable 

customers or the customer segmentation that it wants to expand, instead of paying a third party to 

conduct this analysis.  By partnering with B2B ads networks such as Bizo, BBN, or LinkedIn 

Audience Network, it can target potential companies that share many common demographic 

tributes ith its profitable customer profile. at  w

EPORR TS 

  Standard Coffee should implement pre‐scheduled reporting processes for the automatic 

generation of standard reports, based upon internal analytics.  The use of internal analytics tests 

would allow the company to predefine information contained in these reports.  This capability will 

allow business analytical teams to further deepen their analysis for specific and emerging business 

needs.   The system should also be capable of generating ad‐hoc reports.   

DATA WAREHOUSE AND DATA MARTS 

  In order to truly streamline its efforts, Standard Coffee must create a fully integrated 

internal solution that allows it to effectively cross‐manage its supply chain operations, customer 

service needs, marketing, finance, and personnel management efforts.  Online B2B business 

analytics efforts will enable the company to collect data vital to maintaining a just‐in‐time 

ventory, and build a  distribution warehouse network for its service delivery operations.   in n efficient

DATA W D C  AREHOUSE  ESIGN  ONSIDERATIONS

  The establishment of a centralized data warehouse database will standardize data extracted 

from multiple sources, will provide meaningful data sets with which to conduct analytics, and will 

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heighten inter‐departmental collaboration.  In the case for Standard Coffee, the buy‐in of its 

executive leadership is essential to building a meaningful analytics capability.  Their support will 

flow down into budgets and development, as well as training and actual application.  In order to 

effectively implement a business‐wide system, we recommend:  

• Construction of internal teams skilled in business analytics, in lieu of third party 

consultants.  The creation of internal sources of analysis will allow departments outside of 

Marketing and Finance to use data mart information to improve business operations as a 

whole, with the added benefit of maintaining business‐sensitive information within the 

company.   

• . Sanitizing of data to remove duplication prior to migration

• ts  Documentation of data requirements across departmen

• Redesign of existing ERP to include new requirements.  

• asure. Establishment of data center within a cloud computing service as a cost‐saving me

• Redesign of internal practices to include routine extraction of data and analytical 

sessments. as

DATA MARTS 

We recommend that Standard Coffee create data marts specific to meeting individual 

department requirements, to reduce security and network costs of accessing a central data 

warehouse.   Because data marts are localized and contain a subset of data sets from the centralized 

data warehouse, business units have additional controls. 

C ER SERVICE 

  One of the greatest benefit links would be data gathered from its customer service center.  

The interactions between customer service representatives and customers provide an invaluable 

USTOM

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tool for streamlining processes throughout the company.  RFM Analytics within this data mart 

could indicate the company’s most profitable, and therefore highest priority customers to customer 

service representatives.  Integration of supply chain data could also allow service representatives to 

provide real‐time data regarding shipments, route service representative schedules, etc., while 

allowing for the cross‐transfer of real‐time performance data to Sales, Distribution and Marketing 

department heads.  

 ROUTE SERVICE REPRESENTATIVES/DISTRICT MANAGERS 

  RFM Analysis would use transactional data recording from RSRs and District Route 

Managers reveal the company’s most profitable customers and their purchasing profiles; i.e. those 

customers which spent the greatest amount, in relation to the amount of service time 

required.  RSRs would be able to quickly document their arrival time and departure time, as well as 

document what services were provided (machine maintenance, supply delivery, etc).  This data, 

combined with that of other departments, would readily reveal potential client profiles, product 

demand, and distribution challenges. 

DISTRIBUTION CENTERS 

  Supply chain data marts can supply real time information to customer service 

representatives, district managers, and executive leadership regarding the company’s supply chain 

logistics.  This data mart could significantly improve the company’s supply chain efficiency, by using 

predictive modeling to anticipate need, support just‐in‐time delivery and minimize inventory levels.   

HUMAN RESOURCES MANAGEMENT 

  HR data will assist Standard Coffee in not only retaining its most efficient and profit‐driving 

members, but will provide demographics for recruitment of top talent.  The use of sales, customer 

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Customer's company size (low, medium, and large) 

• Cost of service per customer or per market sector (determining most profitable customers) 

 

 

service and route management data will assist the company in rewarding its top performers, and 

testing motivational strategies for its other employees to perform to a higher level.   

 MARKETING 

  The marketing department at Standard Coffee currently uses analytics to a greater extent 

than the remainder of the company, but its dependency on third party firms reduces its internal 

capability.  The formulation of a Marketing data mart would allow this department to test 

advertisement scenarios, new marketing strategies, etc. prior to launching a full‐scale campaign.  

FINANCE/ACCOUNTING 

  A data mart would allow the Finance department to identify loyal customers, debtor 

customers and other demographic data which may be useful to Marketing, Customer Service, and 

other departments.  It would also allow for the testing of procurement and accounting strategies, to 

encourage on‐time bill payment, and other opportunities. 

R /PROFIT MANAGEMENT 

  The large market fluctuations of coffee and tea subject Standard Coffee to unpredictable 

profit/loss cycles.  Recently, Standard Coffee’s business suffered a significant loss, as a result of 

skyrocketing coffee prices.  This, combined with the recession, resulted in a large drop in business 

for the company.  The use of analytics to predict quarterly revenues would allow Standard Coffee to 

soften the blow of market depressions, and adjust its inventory to more nimbly adjust to changing 

demand.  (Davenport and Harris, Competing on Analytics: The New Science of Winning).  Possible 

prediction metrics (as illustrated in Figure 2) which Standard Coffee could apply are:  

EVENUE

• Revenue per customer or per market sector 

•

 

C ANAGEMENT 

  By applying analytics, Standard Coffee can accurately predict future sales and customize its 

marketing budget.  Potential metrics for streamlining these costs include:   

OST M

• Sales conversion rate per sale agent 

• Lead time (time required to obtain a contract since initial contact vs. time from obtaining 

act) lead to making cont

• Cost per sale agent 

ONLINE PRESENCE 

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Standard Coffee’s website is currently reactive, obtaining contact information through its website,

by requiring interested parties to enter business attribute information when requesting service quotes,

which is then used by sales representatives to customize offerings. However, this requires potential

customers to seek out their website, and to further navigate the page to a service request. Google

Analytics is used by the Marketing department to conduct web analytics and search engine optimization

(SEM). The company does not purchase sponsored links, and does not utilize the search page to produce

banner advertisements. Our initial search phrase of “coffee service” resulted in scrolling halfway down

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the results page to locate Standard Coffee’s website listing. No advertisements or ad links were present as

a result of our search. They also were not the first national service provider listed in the search 

results, and no advertisements were found in the side banner.  

Standard Coffee currently applies a median level of e‐commerce to its website.  Potential 

customers can obtain information on the company’s services, products, and request a quote.  

Existing customers are able to use the “My Account” feature to view/pay their bills, place new 

orders, and request service (Cox).  

On account of these findings, we would recommend that Standard Coffee utilize its budget 

to obtain placement in the ad links listed at the top of the search results page.  We would also 

recommend that Standard Coffee use its marketing budget to place more advertisement online, in 

banner links, and in online publications (e.g. newspaper websites in their regions with greatest 

potential).  Their largest customer demographic, professional firms, is a well‐read and highly 

educated segment of the population, and could easily be reached through online media 

publications. 

 WEBSITE AUDIT 

Currently, Standard Coffee is using Google Analytics to monitor its website activities 

(conversion rate and service requests).  A tags scanning of the company’s home page also reveals 

that they integrate with platform.twitter.com for micro social marketing.  Standard Coffee’s site is 

updated daily with new keywords based on Google Analytics reports of new search phrases.  

However, the company lacks an in‐depth strategic plan for its B2B social network marketing with 

popular social networking sites such as Facebook, LinkedIn, and Google+.   A positive addition to 

the company’s strategy would also be a partnership with B2B publisher sites such as Bzio, BBN, or 

LinkedIn Audience Network to target potential customers in its market segmentation. 

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WEB ANALYTICS IMPLEMENTATION 

WEBSITE DESIGN 

Website upgrades would drastically increase Standard Coffee’s ability to gather data for

conducting analysis of its existing and potential customers. We recommend a website redesign,

including:

• User Accounts: Monitor My Account usage and integrate data collected from customers to

improve existing relationships. Increase current user interaction to include real-time service

request status, RSR visit scheduling, and service feedback.

• Administrative Dashboard: Create an internally viewable administrative dashboard, available to

all Standard Coffee managers. This would allow departments to request or allocate resources to

swiftly meet customer or internal needs. Marketing and Sales teams can use the Dashboard to

directly communicate with customers for promoting new products, or executive leadership could

view ad-hoc query reports on sales trends, customer service ratings, etc.

• Activity Monitoring: Equip website with ability to monitor: 1) web traffic from B2B ads

networks; 2) web conversions rate of its Contact Us web page vs redesigned ordering process; 3)

visitors unique to B2B ads networks vs. social networking efforts; and 4) use of My Account

webpages to identify which features are most used. 

IMPACT ASSESSMENT 

The impact of a company-wide analytics implementation would propel Standard Coffee from a

Level Two capable entity, to potentially Level Five performance, where analytics would be used to keep

the company at the edge of performance (Davenport and Harris). The implementation of a company-wide

analytics plan would first require sponsorship by Standard Coffee’s leadership. This would not only

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provide the financial support required for such an endeavor, but would instill the expectation of

department support and alignment.

The implementation of analytics would allow Standard Coffee not only to grow its customer base

and increase its market share, but potentially allows it to tap currently less-profitable markets. Standard

Coffee’s customer demographic consists of 80% single-location professional firms, 10% hotels chains,

and 10% food service industry. The use of analytics would allow Standard Coffee to not only predict

customer leads in its largest market share, but will support predictive modeling for testing campaigns to

its largely untapped segments within the hospitality industry. By running small-scale analytics tests, the

company could experiment with marketing techniques, expanded service offerings, etc. The impact of

obtaining several national food or hotel chain contracts would have a very significant impact on Standard

Coffee’s overall corporate value.

DEPLOYMENT PLAN 

Numerous tools are available to deploy analytics across the Standard Coffee landscape. The

initial step would be to compete the proposal among software manufacturers such as SAP, Oracle, etc. for

a customized software platform. Additional features would need to be incorporated with the main data

gathering software, including survey features from customer service, timestamp applications for RSRs,

and other information metric tools.

Implementation will require deployment throughout the company on standard workstations, with

specific tools designed for each department (HR, Marketing, Distribution, etc.). Handheld devices such

as tablets and smart phones will be deployed among face-to-face representatives, such as RSRs and

District Managers. Handheld applications, outfitted with secure internet connectivity, will allow for the

swift collection of information from all employees, and filtration into the central database. Analytics tools

will be installed on standard company workstations, to enable to running of small and large-scale tests for

marketing, HR strategies, and other company analytics requirements. Reporting tools will condense data

and run automatic analytics, as programmed by each department, for the filtration and presentation of

relevant information. We estimate that it will take approximately one year to establish a solid analytics

foundation and develop appropriate data marts.

EVALUATION & MONITORING 

  Analytics systems and their effectiveness will be graded on an annual basis. A matrix from each

department shall document analytical tools utilized during this period, resulting strategic shifts, and

profitability changes as a result of implemented analytics. Recommendations shall be included, detailing

ideas for future applications, and documenting areas in which analytics has a minimal Return on

Investment (ROI). Strategic plans will be formatted by corporate leadership, emphasizing areas of

analytic growth, and minimizing investment in those areas which show the least applicability.

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0 5 10 15

Implementation Timeline2 2 6 2

Data Requirements Gathering

Capability Needs Assessment

DataMart Construction/Testing

Training/Implementation

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CONCLUSION 

Standard Coffee can differentiate itself from competitors by pursuing an effective and 

efficient business analytics framework, incorporating sophisticated quantitative and statistical 

analysis and predictive modeling.  Though Standard Coffee has the primary attributes of analytical 

competitors, it lacks a corporate approach and a commitment from executive management.  

analytic capabilities.  Our recommendations, if approved and implemented, will provide analytic 

support for internal and external business processes. 

Standard Coffee should maximize its analytical capabilities to predict customer leads, 

improve lead scoring and retain loyal customers.  By converting its current reactive stance to a 

proactive framework, Standard Coffee will effectively bridge inter‐departmental databases, 

integrate business processes, and optimize its supply chain management.  An effective analytics 

infrastructure will also assist the company in boosting its online presence, and driving business to 

its site. and boost online presence with integration of social, web and mobile technologies.  Such a 

well‐established business intelligence infrastructure will enable enterprise‐wide collaboration and 

information sharing, improving company performance across all sectors.  

 

 

 

 

 

 

 

 

 

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BIBLIOGRAPHY Cox, Troy V. Marketing Director, Standard Coffee Anil Cheerla, Lauren Dufrene, Khoivu Nguyen Brendan Burns. Interview. 22 September 2011. 

Davenport, Thomas H. and Jeanne Harris. Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business School Press, 2007. 

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