Monday, August 4, 2008

Harrah and its database technology

Harrah's uses database technologies in a very judicious manner to implement its service-oriented strategy. As has been told in the case, customers are the center point around which Harrah's tailor all their strategy and policy. They regard the commitment to their customers as the most important aspect of their business, thus adopting the service-oriented strategy. To make sure that they can serve their customers in the most effective and efficient manner they utilize the information about the customers in a very fruitful manner. That's where their reliance on database comes into play. It contains all the information about various habits of the customers like amount of times they gamble, the games they prefer to play the most, their betting strategies, etc. Based on that information it can go about serving the customers even more loyally. And the database technology acts as the repository from which they can retrieve that vital information.

Effect of poor information on Harrah's business strategy

There would be some serious effects from poor information on Harrah's service-oriented business strategy. As it enjoys its competitive advantage from better utilization of information rather than intuition, poor quality of information will surely affect its superiority in the casino industry. It might encounter less customer visits which will eventually result in gross market revenue, profit and ROI going down because at the end of the day customers are the lifeblood for Harrah's. It has tailored its business strategy to be service-oriented. So, any lacking into the quality of the information that they get about customers or their internal infrastructure will surely cause disruption in their act of providing service to customers which will later on affect their overall business strategy as well.

Wednesday, July 30, 2008

A Big Revolution in both the IT and business world: Data Warehouse

There is more than one company who has surely reaped the benefit from utilizing data warehousing. Thus it shouldn't be a big endeavor to find out some organizations that has been benefited by using data warehouse. I found out several companies that has achieved great success via Data Warehousing. In the next few paragraphs I am going to elaborate on the success that data warehousing resulted in, at those companies.

The first example can be that of Victoria's Secret. This company analyzes the status of every individual product by customer, by day, for each order that they get through their bricks-and-mortar stores as well as orders that they get through their website victoriassecret.com. The data warehouse that they have then enables Victoria's Secret to improve their prediction on any particular customer. It also enables the company to stay abreast of each order's profit equation. To measure the revenue of each order, Victoria's Secret starts with the merchandise price and subtracts shipping, handling, and related taxes, as well as special service charges, such as shipping upgrades and gift wrapping. This process means that the retailer can measure the profitability of every customer, order, catalog and product.

The next example can be that of Sears, Roebuck and Company, the largest department store chain and the third-largest retailer in the United States. Sears has 18 data centers, one in each 10 geographical regions as well as one each for marketing, finance and other departments. Frequent mismatches between accounting and sales figures and information scattered among numerous databases forced users to query multiple systems, even when they needed an answer to a simple query. Furthermore, there were errors when calculations were based on data from several sources. To solve these problems, Sears constructed a single sales information data warehouse. This replaced the 18 old databases which were packed with redundant, conflicting, and sometimes obsolete data. As has been the result, the data warehouse enabled Sears to monitor sales by item per store to create a sharp local market focus. Eventually, the sales and market share improved. Response times to queries have dropped from days to minutes for typical requests. Overall the strategic impact of the data warehouse implemented by Sears has been the fact that it offered Sears’s employees a tool for making better decisions. And at the end of the day, Sears retailing profits have climbed more than 20 percent annually. Kudos to the successful implementation and utilization of data warehouse.

Companies do get competitive advantage by using BI (business intelligence)

Ben & Jerry’s is using BI to improve quality. Customers know that a pint of Ben & Jerry’s ice cream is of the highest quality.

California Pizza Kitchen and Noodles & Company are using BI to improve financial analysis capabilities. Both companies can now receive more accurate and complete financial views of their businesses.

Reasons why 100 percent accurate and complete information is impossible for Noodles & Company to obtain.

Noodles & Company will never have 100 percent accurate and complete information. Perfect information is pricey. 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.

Use of BI by California Pizza Kitchen

Financial statements must be as accurate and complete as possible. There have been too many instances in the past where shoddy financial statements have lead to financial crisis such as Enron and WorldCom. It does not matter how good or how many BI tools California Pizza Kitchen uses; if the core data is dirty the results will be inaccurate.

How Ben & Jerry's use business intelligence: a simple concept actually

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 mile, eggs, or cherries, etc. did not meet the organization’s near-obsession with quality.