6-3 Organizational Information Information is everywhere in an organization –Data are raw facts that describe the characteristics of an event Sales event – date, item number, item description, quantity ordered, customer name, shipping details –Information is data converted into a meaningful and useful context Sales event – best/worst selling item, best/worst customer Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational information to make decisions Successfully collecting, compiling, sorting, and analyzing information can provide tremendous insight into how an organization is performing
6-4 Organizational Information GREAT BUSINESS DECISIONS – Julius Reuter Uses Carrier Pigeons to Transfer Information In 1850, the idea that sending and receiving information could add business value was born. Julius Reuter began a business that bridged the gap between Belgium and Germany. Reuter built one of the first information management companies built on the premise that customers would be prepared to pay for information that was timely and accurate. Reuter used carrier pigeons to forward stock market and commodity prices from Brussels to Germany.
6-5 Organizational Information Customers quickly realized that with the early receipt of vital information they could make fortunes. –Those who had money at stake in the stock market were prepared to pay handsomely for early information from a reputable source, even if it was a pigeon. –Eventually, Reuter’s business grew from 45 pigeons to over 200 pigeons. Eventually the telegraph bridged the gap between Brussels to Germany, and Reuter’s brilliantly conceived temporary monopoly was closed.
6-6 Organizational Information Levels, formats, and granularities
6-7 The Value of Transactional and Analytical Information Information TypesRangeExamples Information LevelsIndividualIndividual knowledge, goals and strategies DepartmentDepartmental goals, revenues, expenses, processes and strategies EnterpriseEnterprise-wide revenues, expenses, processes and strategies Information FormatsDocumentLetters, memos, faxes, e-mails, reports, marketing materials PresentationProduct, strategy, process, financial, customer and competitor presentations SpreadsheetSales, marketing, industry, financial, competitor, customer, and order spreadsheets DatabaseCustomer, employee, sales, order, supplier and manufacturer Information GranularitiesDetail (Fine)Reports for each salesperson, product and part SummaryReports for all sales personnel, all products and all parts Aggregate (Coarse)Reports across departments, organizations and companies
6-8 The Value of Transactional and Analytical Information
6-9 The Value of Timely Information Transactional information – encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks Analytical information – encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks
6-10 The Value of Timely Information Organizations capture and store transactional information in databases and use it when performing operational tasks and repetitive decisions such as analyzing daily sales reports and production schedules Transactional information examples include withdrawing cash from an ATM, making an airline reservation, purchasing stocks
6-11 The Value of Timely Information Analytical information includes transactional information –Includes external organizational information such as market, industry, and economic conditions –Used to make ad-hoc decisions –Includes trends, sales, product statistics, and future growth projections Could also include cost/benefit analysis, sales forecast, market trends, industry trends, and regulations
6-12 The Value of Timely Information Timeliness is an aspect of information that depends on the situation –Real-time information – immediate, up-to- date information –Real-time system – provides real-time information in response to query requests
6-13 The Value of Quality Information Business decisions are only as good as the quality of the information used to make the decisions You never want to find yourself using technology to help you make a bad decision faster
6-14 The Value of Quality Information Business decisions are only as good as the quality of the information used to make the decisions Characteristics of high quality information include: –Accuracy Are all the values correct? Is the name spelled correctly? Is the dollar amount recorded properly? –Completeness Are any of the values missing? Is the address complete including street, city, state, and zip code? –Consistency Is aggregate or summary information in agreement with detailed information? Do all total fields equal the true total of the individual fields? –Uniqueness Is each transaction, entity, and event represented only once in the information? Are there any duplicate customers? –Timeliness Is the information current with respect to the business requirements? Is information updated weekly, daily, or hourly?
6-15 The Value of Quality Information Low quality information example
6-16 The Value of Quality Information Issue 1: Without a first name it would be impossible to correlate this customer with customers in other databases (Sales, Marketing, Billing, Customer Service) to gain a compete customer view (CRM) Issue 2: Without a complete street address there is no possible way to communicate with this customer via mail or deliveries. An order might be sitting in a warehouse waiting for the complete address before shipping. The company has spent time and money processing an order that might never be completed Issue 3: If this is the same customer, the company will waste money sending out two sets of promotions and advertisements to the same customers. It might also send two identical orders and have to incur the expense of one order being returned Issue 4: This is a good example of where cleaning data is difficult because this may or may not be an error. There are many times when a phone and a fax have the same number. Since the phone number is also in the e-mail address field, chances are that the number is inaccurate Issue 5: The business would have no way of communicating with this customer via e-mail Issue 6: The company could determine the area code based on the customer’s address. This takes time, which costs the company money. This is a good reason to ensure that information is entered correctly the first time. All incorrect information needs to be fixed, which costs time and money
6-17 Understanding the Costs of Poor Information The four primary sources of low quality information include: 1.Customers intentionally enter inaccurate information to protect their privacy 2.Information from different systems have different entry standards and formats 3.Call center operators enter abbreviated or erroneous information by accident or to save time 4.Third party and external information contains inconsistencies, inaccuracies, and errors
6-18 Understanding the Costs of Poor Information Potential business effects resulting from low quality information include: –Inability to accurately track customers –Difficulty identifying valuable customers –Inability to identify selling opportunities –Marketing to nonexistent customers –Difficulty tracking revenue due to inaccurate invoices –Inability to build strong customer relationships
6-19 Understanding the Costs of Poor Information Poor information could cause the SCM system to order too much inventory from a supplier based on inaccurate orders Poor information could cause a CRM system to send an expensive promotional item (such as a fruit basket) to the wrong address of one of its best customers What occurs when you have the inability to build strong customer relationships? –Decreased seller power
6-20 Understanding the Benefits of Good Information High quality information can significantly improve the chances of making a good decision Good decisions can directly impact an organization's bottom line
6-21 Relational Database Fundamentals Information is everywhere in an organization Information is stored in databases –Database – maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)
6-22 Relational Database Fundamentals Database models include: –Hierarchical database model – information is organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships –Network database model – a flexible way of representing objects and their relationships –Relational database model – stores information in the form of logically related two-dimensional tables
6-23 DATABASE ADVANTAGES Database advantages from a business perspective include –Increased flexibility –Increased scalability and performance –Reduced information redundancy –Increased information integrity (quality) –Increased information security –Spreadsheet limitations Limited number of rows and columns (Excel - 65,536 rows by 256 columns) Once you use more than 65,536 rows you have outgrown your spreadsheet Only one users can access the spreadsheet Users can view all information in the spreadsheet Users can change all information in the spreadsheet
6-24 Entity – a person, place, thing, transaction, or event about which information is stored –The rows in each table contain the entities –In Figure 6.5 CUSTOMER includes Dave’s Sub Shop and Pizza Palace entities Entity class (table) – a collection of similar entities –In Figure 6.5 CUSTOMER, ORDER, ORDER LINE, DISTRIBUTOR, and PRODUCT entity classes RELATIONAL DATABASE FUNDAMENTALS
6-25 Attributes (fields, columns) – characteristics or properties of an entity class –The columns in each table contain the attributes –In Figure 6.5 attributes for CUSTOMER include: Customer ID Customer Name Contact Name Phone –Possible other attributes: Address Fax E-mail Cell phone RELATIONAL DATABASE FUNDAMENTALS
6-26 Keys and Relationships Primary keys and foreign keys identify the various entities (tables) in the database –Primary key – a field (or group of fields) that uniquely identifies a given entity in a table –Foreign key – a primary key of one table that appears an attribute in another table and acts to provide a logical relationship among the two tables
6-27 Keys and Relationships –Example Hawkins Shipping in the DISTRIBUTOR table has a primary key called Distributor ID – DEN8001 Hawkins Shipping (Distributor ID DEN8001) is responsible for delivering orders 34561 and 345652 Therefore, Distributor ID in the ORDER table creates a logical relationship (who shipped what order) between ORDER and DISTRIBUTOR
6-28 How many orders have been placed for T’s Fun Zone? –Ans: 1 Order IT 34563 How many orders have been placed for Pizza Palace? –Ans: None How many items are included in Dave’s Sub Shop’s two orders? –Ans: Order 34561 has 3 items and order 34562 has one item for a total of 4 items in both orders. Who is responsible for distributing Dave’s Sub Shop’s orders? –Ans: Hawkins Shipping Which products are included in Order 34562? –Ans: 300 Vanilla Coke RELATIONAL DATABASE FUNDAMENTALS
6-29 Potential relational database for Coca- Cola
6-30 ***Relational Database Advantages Database advantages from a business perspective include –Increased flexibility –Increased scalability and performance –Reduced information redundancy –Increased information integrity (quality) –Increased information security
6-31 Increased Flexibility A well-designed database should: –Handle changes quickly and easily –Provide users with different views –Have only one physical view Physical view – deals with the physical storage of information on a storage device –Have multiple logical views Logical view – focuses on how users logically access information
6-32 Increased Scalability and Performance A database must scale to meet increased demand/growth, while maintaining acceptable performance levels –Scalability – refers to how well a system can adapt to increased demands –Performance – measures how quickly a system performs a certain process or transaction
6-33 Reduced Information Redundancy Databases reduce information redundancy –Redundancy – the duplication of information or storing the same information in multiple places Inconsistency is one of the primary problems with redundant information
6-34 Increase Information Integrity (Quality) Information integrity – measures the quality of information Integrity constraint – rules that help ensure the quality of information –Relational integrity constraint rule that enforces basic and fundamental information- based constraints –Business-critical integrity constraint rule that enforce business rules vital to an organization’s success and often require more insight and knowledge than relational integrity constraints
6-35 Increase Information Integrity (Quality) Relational integrity constraint for an ordering system –Users cannot create an order for a nonexistent customer Business-critical integrity constraints for an ordering system –Product returns are not accepted for fresh product 15 days after purchase –A discount maximum of 20 percent
6-36 Increased Information Security Information is an organizational asset and must be protected –Access levels will typically mimic the hierarchical structure of the organization and protect organizational information from being viewed and manipulated by individuals who should not have access to the sensitive or confidential information
6-37 Increased Information Security Databases offer several security features including: –Password – provides authentication of the user –Access level – determines who has access to the different types of information –Access control – determines types of user access, such as read-only access
6-38 Database Management Systems Database management systems (DBMS) – software through which users and application programs interact with a database
6-39 Database Management Systems Direct interaction – –The user interacts directly with the DBMS –The DBMS obtains the information from the database Indirect interaction –User interacts with an application (i.e., payroll application, manufacturing application, sales application) –The application interacts with the DBMS –The DBMS obtains the information from the database
6-40 Data-Driven Websites A data-driven website is an interactive website kept constantly updated and relevant to the needs of its customers through the use of a database. –Data-driven websites are especially useful when the site offers a great deal of information, products, or services.
6-41 Data-Driven Websites –A data-driven website invites visitors to select and view what they are interested in by inserting a query, which the website then analyzes and custom builds a Web page in real-time that satisfies the query. –The figure displays a Wikipedia user querying business intelligence and the database sending back the appropriate Web page that satisfies the user’s request
6-43 Data-Driven Website Business Advantages Development Content Management Future Expandability Minimizing Human Error Cutting Production and Update Costs More Efficient Improved Stability
6-44 Data-Driven Website Business Advantages Development: Allows the website owner to make changes any time—all without having to rely on a developer or knowing HTML programming. A well- structured, data-driven website enables updating with little or no training. Content management: A static website requires a programmer to make updates. This adds an unnecessary layer between the business and its Web content, which can lead to misunderstandings and slow turnarounds for desired changes.
6-45 Data-Driven Website Business Advantages Future expandability: Having a data- driven website enables the site to grow faster than would be possible with a static site. Changing the layout, displays, and functionality of the site (adding more features and sections) is easier with a data-driven solution.
6-46 Data-Driven Website Business Advantages Minimizing human error: Even the most competent programmer charged with the task of maintaining many pages will overlook things and make mistakes. This will lead to bugs and inconsistencies that can be time consuming and expensive to track down and fix. Unfortunately, users who come across these bugs will likely become irritated and may leave the site. A well-designed, data-driven website will have ”error trapping” mechanisms to ensure that required information is filled out correctly and that content is entered and displayed in its correct format.
6-47 Data-Driven Website Business Advantages Cutting production and update costs: A data-driven website can be updated and ”published” by any competent data entry or administrative person. In addition to being convenient and more affordable, changes and updates will take a fraction of the time that they would with a static site. While training a competent programmer can take months or even years, training a data entry person can be done in 30 to 60 minutes.
6-48 Data-Driven Website Business Advantages More efficient: By their very nature, computers are excellent at keeping volumes of information intact. With a data-driven solution, the system keeps track of the templates, so users do not have to. Global changes to layout, navigation, or site structure would need to be programmed only once, in one place, and the site itself will take care of propagating those changes to the appropriate pages and areas. A data-driven infrastructure will improve the reliability and stability of a website, while greatly reducing the chance of ”breaking” some part of the site when adding new areas.
6-49 Data-Driven Website Business Advantages Improved Stability: Any programmer who has to update a website from ”static” templates must be very organized to keep track of all the source files. If a programmer leaves unexpectedly, it could involve re- creating existing work if those source files cannot be found. Plus, if there were any changes to the templates, the new programmer must be careful to use only the latest version. With a data-driven website, there is peace of mind, knowing the content is never lost—even if your programmer is.
6-51 Data-Driven Business Intelligence The customer enters search criteria in the website The database runs a query on the search criteria The company can gain BI by viewing how often items are searched, which item is searched the most – the least, etc. Companies can gain business intelligence by viewing the data accessed and analyzed from their website. The figure displays how running queries or using analytical tools, such as a Pivot Table, on the database that is attached to the website can offer insight into the business, such as items browsed, frequent requests, items bought together, etc.
6-52 Integrating Information among Multiple Databases Integration – allows separate systems to communicate directly with each other –Forward integration – takes information entered into a given system and sends it automatically to all downstream systems and processes –Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and processes
6-53 Integrating Information among Multiple Databases Forward integration
6-54 Integrating Information among Multiple Databases Backward integration
6-55 Integrating Information among Multiple Databases Building a central repository specifically for integrated information
6-56 OPENING CASE STUDY QUESTIONS It Takes A Village to Write an Encyclopedia Is an entry in Wikipedia is an example of transactional information or analytical information. –From the customer’s perspective Wikipedia entries are an example of analytical information. They are using the information to research a topic, make a decision, or perform an analysis. From Wikipedia’s perspective each entry is an example of transactional information since it is their primary business to gain entries from individual contributors.
6-57 OPENING CASE STUDY QUESTIONS It Takes A Village to Write an Encyclopedia Wikipedia and the five common characteristics of high quality information –Timeliness – Wikipedia’s information must be timely. If users are receiving old and outdated entries, or no entries for a new topic, they will not continue using Wikipedia. An encyclopedia that is outdated is not very useful. –Accuracy – Wikipedia’s entries must be accurate, and if they are inaccurate the users can change the definition to ensure it is accurate. An encyclopedia that is inaccurate is useless.
6-58 OPENING CASE STUDY QUESTIONS It Takes A Village to Write an Encyclopedia –Consistency – Wikipedia’s results must be consistent. Users will not trust the system if it provides different definitions for the same entry. An encyclopedia that offers inconsistent terms is not useful. –Completeness – Wikipedia’s entry results need to be complete. An encyclopedia that does not contain vast amounts of information is not useful. –Uniqueness – Wikipedia’s customers want unique answers to each entry. Multiple answers to a term will confuse the customer and they will not be able to know which answer is correct. An encyclopedia cannot have multiple answers for each term.
6-59 OPENING CASE STUDY QUESTIONS It Takes A Village to Write an Encyclopedia How is Wikipedia resolving the issue of poor information? –Wikipedia originally allowed unrestricted access so that people could contribute to the site without undergoing a registration process. –As with any database management system, governance is a key issue. Without governance, there is no control over how information is published and maintained. But as Websites like Wikipedia grow in volume, it will be nearly impossible to govern them. –Wikipedia began tightening its rules for submitting entries following the disclosure that it ran a piece falsely implication a man in the Kennedy assassination. Wikipedia now requires users to register before they can create articles.
6-60 OPENING CASE STUDY QUESTIONS It Takes A Village to Write an Encyclopedia Why is database technology so important to Wikipedia’s business model? –Without databases, Wikipedia simply would not exist for two primary reasons. –First, vast amounts of information are at the heart of Wikipedia and without databases it would be impossible to store and retrieve the information. This is the information that Wikipedia’s customers are editing and researching. –Second, Wikipedia uses database to store its indexes and to find and retrieve the information that its customers are looking for. 6
6-62 HISTORY OF DATA WAREHOUSING Bill Inmon, is recognized as the "father of the data warehouse" and co-creator of the "Corporate Information Factory.“ In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions The data warehouse provided the ability to support decision making without disrupting the day-to-day operations
6-63 HISTORY OF DATA WAREHOUSING Data warehouses extend the transformation of data into information In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions The data warehouse provided the ability to support decision making without disrupting the day-to-day operations
6-64 DATA WAREHOUSE FUNDAMENTALS Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes –Database store information for a single application whereas a data warehouse stores information from multiple databases, or multiple applications, and external information such as industry information This enables cross-functional analysis, industry analysis, market analysis, etc., all from a single repository –Data warehouses support online analytical processing (OLAP)
6-65 DATA WAREHOUSE FUNDAMENTALS Extraction, transformation, and loading (ETL) – a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse Data mart – contains a subset of data warehouse information –The ETL process also gathers data from the data warehouse and passes it to the data marts
6-66 DATA WAREHOUSE FUNDAMENTALS The data warehouse modeled in the next slide compiles information from internal databases or transactional/operational databases and external databases through ETL It then send subsets of information to the data marts through the ETL process Difference between a data warehouse and a data mart? –A data warehouse has an enterprisewide organizational focus, while a data mart focuses on a subset of information for a given business unit such as finance
6-68 Multidimensional Analysis Databases contain information in a series of two-dimensional tables In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows –Dimension – a particular attribute of information – such as Products, Promotions, Stores, Category, Region, Stock price, Date, Time, Weather The ability to look at information from different dimensions can add tremendous business insight –By slicing-and-dicing the information a business can uncover great unexpected insights
6-69 Multidimensional Analysis Cube – common term for the representation of multidimensional information
6-70 Multidimensional Analysis Users can slice and dice the cube to drill down into the information –Cube A represents store information (the layers), product information (the rows), and promotion information (the columns) –Cube B represents a slice of information displaying promotion II for all products at all stores –Cube C represents a slice of information displaying promotion III for product B at store 2
6-71 Multidimensional Analysis Data mining – the process of analyzing data to extract information not offered by the raw data alone –Data mining can begin at a summary information level (coarse granularity) and progress through increasing levels of detail (drilling down), or the reverse (drilling up) To perform data mining users need data-mining tools –Data-mining tool – uses a variety of techniques to find patterns and relationships in large volumes of information and infers rules that predict future behavior and guide decision making Data-mining tools include query tools, reporting tools, multidimensional analysis tools, statistical tools, and intelligent agents
6-72 Multidimensional Analysis What might an accountant discover through the use of data-mining tools to drill down into the details of all of the expense and revenue? –Which employees are spending the most amount of money on long-distance phone calls –Which customers are returning the most products
6-73 Information Cleansing or Scrubbing An organization must maintain high-quality data in the data warehouse What would happen if the information contained in the data warehouse was only about 70 percent accurate? –Would you use this information to make business decisions? –Is it realistic to assume that an organization could get to a 100% accuracy level on information contained in its data warehouse? Information cleansing or scrubbing – a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information
6-74 Information Cleansing or Scrubbing Customer information exists in several operational systems with different detail information –Determining which contact information is accurate and correct for this customer depends on the business process that is being executed
6-75 Information Cleansing or Scrubbing Standardizing Customer name from Operational Systems
6-76 Information Cleansing or Scrubbing Typical events that occur during information cleansing
6-77 Information Cleansing or Scrubbing Accurate and complete information
6-78 Information Cleansing or Scrubbing Why do you think most businesses cannot achieve 100% accurate and complete information? –Some companies are willing to go as low as 20% complete just to find business intelligence –Few organizations will go below 50% accurate – the information is useless if it is not accurate Achieving perfect information is almost impossible –The more complete and accurate an organization wants to get its information, the more it costs –The tradeoff between perfect information lies in accuracy verses completeness –Accurate information means it is correct, while complete information means there are no blanks –Most organizations determine a percentage high enough to make good decisions at a reasonable cost, such as 85% accurate and 65% complete
6-79 BUSINESS INTELLIGENCE Technology –Even the smallest company with BI software can do sophisticated analyses today that were unavailable to the largest organizations a generation ago. The largest companies today can create enterprise-wide BI systems that compute and monitor metrics on virtually every variable important for managing the company. –Technology is the most significant enabler of business intelligence.
6-80 BUSINESS INTELLIGENCE People –Understanding the role of people in BI allows organizations to systematically create insight and turn these insights into actions. Organizations can improve their decision making by having the right people making the decisions. This usually means a manager who is in the field and close to the customer rather than an analyst rich in data but poor in experience. –In recent years “business intelligence for the masses” has been an important trend, and many organizations have made great strides in providing sophisticated yet simple analytical tools and information to a much larger user population than previously possible.
6-81 BUSINESS INTELLIGENCE Culture –A key responsibility of executives is to shape and manage corporate culture. The extent to which the BI attitude flourishes in an organization depends in large part on the organization’s culture. –Perhaps the most important step an organization can take to encourage BI is to measure the performance of the organization against a set of key indicators. The actions of publishing what the organization thinks are the most important indicators, measuring these indicators, and analyzing the results to guide improvement display a strong commitment to BI throughout the organization
6-82 DATA MINING Data-mining software includes many forms of AI such as neural networks and expert systems
6-83 DATA MINING Data-mining tools apply algorithms to information sets to uncover inherent trends and patterns in the information Analysts use this information to develop new business strategies and business solutions Common forms of data-mining analysis capabilities include: –Cluster analysis –Association detection –Statistical analysis
6-84 Cluster Analysis Cluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible –Consumer goods by content, brand loyalty or similarity –Product market typology for tailoring sales strategies –Retail store layouts and sales performances –Corporate decision strategies using social preferences CRM systems depend on cluster analysis to segment customer information and identify behavioral traits
6-85 Association Detection Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information –Maytag uses association detection to ensure that each generation of appliances is better than the previous generation –Maytag’s warranty analysis tool automatically detects potential issues, provides quick and easy access to reports, and performs multidimensional analysis on all warranty information –Market basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services
6-86 Statistical Analysis Statistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysis –Forecast – predictions made on the basis of time-series information –Time-series information – time-stamped information collected at a particular frequency
6-87 Statistical Analysis Kraft uses statistical analysis to assure consistent flavor, color, aroma, texture, and appearance for all of its lines of foods Kraft evaluates every manufacturing procedure, from recipe instructions to cookie dough shapes and sizes to ensure that the billions of Kraft products that reach consumers each year taste great (and the same) with every bite Nestle Italiana uses data mining and statistical analysis to determine production forecasts for seasonal confectionery products The company’s data-mining solution gathers, organizes, and analyzes massive volumes of information to produce powerful models that identify trends and predict confectionery sales
6-88 Mining the Data Warehouse Ben & Jerry’s tracks the ingredients and life of each pint in a data warehouse. If a consumer calls in with a complaint, the consumer affairs staff matches up the pint with which supplier’s milk, eggs, or cherries, etc. did not meet the organization’s near-obsession with quality.
6-89 BI at Harrah’s The Total Rewards program allows Harrah’s to give every single customer the appropriate amount of personal attention, whether it’s leaving sweets in the hotel room or offering free meals. –Total Rewards works by providing each customer with an account and a corresponding card that the player swipes each time he or she plays a casino game. The program collects information, via a database, on the amount of time the customers gamble, their total winnings and losses, and their betting strategies. Customers earn points based on the amount of time they spend gambling, which they can then exchange for comps such as free dinners, hotel rooms, tickets to shows, and even cash.
6-90 BI at Harrah’s –Without database integration among its hotels and casinos, Harrah’s would be unable to determine what a customer’s true value is to the company. For example, a customer that spend $500,000 dollars at one casino might be treated like royalty. This same customer could visit another Harrah’s location, but since the information is not integrated, the new location would have no idea that they had a high-rolling customer on the premises and they might not treat the customer accordingly.