716 ITU‐T's Technical Reports and Specifications conditioning electric power consumption data to determine clogged filters. Eco‐point services, such as discount coupons for various services, can use the data to determine incentives for households that avoid peak use of electricity. Various service providers, such as food service outlets, can also cooperate and share data with electric power companies. These examples demonstrate that the secondary use of data can potentially create new services while enhancing the data's value. From numerous viewpoints, the secondary use of data is under consideration, and its demand is increasing. However, it is possible to know what kinds of home appliances are used in the house. Moreover, the family configuration and estimation of income could be analyzed from such data. In a smart grid and clean power conference in Britain, an executive of Siemens Energy said \"We, Siemens, have the technology to record energy consumption every minute, second, microsecond, more or less live.From that, we can infer how many people are in the house, what they do, whether they're upstairs, downstairs, do you have a dog, when do you habitually get up, when did you get up this morning, when do you have a shower: masses of private data.\". If such information is revealed, it may become a threat; e.g., a thief may enter the house when the residents are regularly absent. In equal measure, this secondary use of data can result in privacy problems. In the previous examples, the location data produced by a smart phone reveals the user's location at a given time. The amount of electricity usage recorded by smart meters may reveal excessive power consumption by the household, potentially revealing their high‐income status. Moreover, it is simple to publish sensitive data utilizing the Internet without proper regard to the privacy. If access to this information is not adequately restricted, it may promptly result in its unauthorized use. Aside from its usefulness, publishing the data may result in the infringement of privacy rights. Therefore, techniques for publishing the data while simultaneously protecting the privacy are required for the safe secondary use of the data. 6.5 Operation management Data operation management focuses on the delicate data management of internal business processes to produce and distribute products and services. Some of activities that are covered by data operation management include data creation, development, production and distribution. Other data operation management activities include managing purchases and evaluations. A great deal of the focus of data operation management is on the efficiency and effectiveness of data's processes. Therefore, data operation management often includes substantial measurement and analysis of internal processes. Ultimately, the nature of how data operation management is carried out in a city depends much on the nature of products or services. As with all forms of management, data operation management needs to be tailored to meet the specific needs and requirements of a city. Rather, it is gained through the utilization of thoroughly developed methods and processes, and shared with all members. Many factors need considering when planning, implementing and continually developing operational processes. Supply chain management is defined as the management of data as well data flows both in and between links in the chain, which include government, enterprise, social groups and individuals. The key issue for successful supply chain management is the effective full‐scale coordination between these different partners. Such relationships are dependent on the data sharing. Issues such as purchasing prices and the levels to be purchased, as well as, storage of raw data, and other product components are to be overseen. From an operations viewpoint, all of these various processes must be reviewed frequently and improved constantly in order to ensure 'smooth', efficient operations within the city.