Over the past decades, businesses have invested heavily in IT infrastructures (e.g., ISs) to capture, store, analyze, and communicate data. However, the creation of ISs to manage and process data and the deployment of communication networks by themselves do not generate value, as measured by an increase in profitability . Viewed from the basic profitability or net income model (profit revenues expenses), profit increases when employees learn from and use the data to increase revenues, reduce expenses, or both. In this learn and earn model, managers learn—that is, gain insights—from their data to predict what actions will lead to the greatest increase in net earnings. Net earnings are also referred to as net income or the bottom line . The pursuit of earnings is the primary reason companies exist. Reducing uncertainty can improve the bottom line, as the examples in Table 3.5 show. Applebee’s International, Inc. ( applebees.com ), headquartered in Kansas, had faced these and other common business uncertainties and questions, but the company lacked the data infrastructure to answer them. Applebee’s International develops, franchises, and operates restaurants under the Applebee’s Neighborhood Grill & Bar brand, the largest casual dining enterprise in the world. As of 2008, there were nearly 2,000 Applebee’s restaurants operating in 49 states and 17 countries, of which 510 were company owned. Despite its impressive size, however, Applebee’s faced fierce competition. To differentiate Applebee’s from other restaurant chains and to build customer loyalty (defined as return visits), management wanted guests to experience a good time while having a great meal at attractive prices. To achieve their strategic objectives, management had to be able to forecast demand accurately and to become familiar with customers’ experiences and regional food preferences. For example, knowing which new items to add to the menu based on past food preferences helps motivate return visits. However, identifying regional preferences, such as a strong demand for steaks in Texas but not in New England, by analyzing the relevant data was too time-consuming when it was done with the company’s spreadsheet software. The problem for many companies such as Applebee’s International is that it is very difficult to bring together huge quantities of data located in different databases in a way that creates value. Without efficient processes for managing vast amounts of customer data and turning this data into usable knowledge, companies can miss critical opportunities to find insights hidden in the data.
Over the past decades, businesses have invested heavily in IT infrastructures (e.g., ISs) to capture, store, analyze, and communicate data. However, the creation of ISs to manage and process data and the deployment of communication networks by themselves do not generate value, as measured by an increase in profitability . Viewed from the basic profitability or net income model (profit revenues expenses), profit increases when employees learn from and use the data to increase revenues, reduce expenses, or both. In this learn and earn model, managers learn—that is, gain insights—from their data to predict what actions will lead to the greatest increase in net earnings. Net earnings are also referred to as net income or the bottom line . The pursuit of earnings is the primary reason companies exist. Reducing uncertainty can improve the bottom line, as the examples in Table 3.5 show. Applebee’s International, Inc. ( applebees.com ), headquartered in Kansas, had faced these and other common business uncertainties and questions, but the company lacked the data infrastructure to answer them. Applebee’s International develops, franchises, and operates restaurants under the Applebee’s Neighborhood Grill & Bar brand, the largest casual dining enterprise in the world. As of 2008, there were nearly 2,000 Applebee’s restaurants operating in 49 states and 17 countries, of which 510 were company owned. Despite its impressive size, however, Applebee’s faced fierce competition. To differentiate Applebee’s from other restaurant chains and to build customer loyalty (defined as return visits), management wanted guests to experience a good time while having a great meal at attractive prices. To achieve their strategic objectives, management had to be able to forecast demand accurately and to become familiar with customers’ experiences and regional food preferences. For example, knowing which new items to add to the menu based on past food preferences helps motivate return visits. However, identifying regional preferences, such as a strong demand for steaks in Texas but not in New England, by analyzing the relevant data was too time-consuming when it was done with the company’s spreadsheet software. The problem for many companies such as Applebee’s International is that it is very difficult to bring together huge quantities of data located in different databases in a way that creates value. Without efficient processes for managing vast amounts of customer data and turning this data into usable knowledge, companies can miss critical opportunities to find insights hidden in the data.
การแปล กรุณารอสักครู่..
