{"id":633831,"date":"2018-04-11T00:00:00","date_gmt":"2018-04-10T22:00:00","guid":{"rendered":"https:\/\/www.ie.edu\/insights\/latest-news\/articles\/the-rising-value-of-data\/"},"modified":"2019-11-21T12:35:43","modified_gmt":"2019-11-21T11:35:43","slug":"the-rising-value-of-data","status":"publish","type":"articles","link":"https:\/\/www.ie.edu\/insights\/articles\/the-rising-value-of-data\/","title":{"rendered":"The Rising Value of Data"},"featured_media":636330,"template":"","meta":{"_has_post_settings":[]},"schools":[33],"areas":[16,22,24,26],"subjects":[],"class_list":["post-633831","articles","type-articles","status-publish","has-post-thumbnail","hentry","schools-human-sciences-and-technology","areas-competitiveness-growth","areas-sales-marketing","areas-strategy","areas-technology"],"custom-fields":{"wpcf-article-leadin":["Data have become a strategic element of organizations. In the near future, it may be practically impossible for an organization to do business unless it is fully data-oriented. The strategic step is to treat data as a key business strategy rather than as a purely technical matter. Organizations that have adopted this approach provide proof that it works."],"wpcf-article-body":["There is no longer any doubt that data science has the potential to create value and competitive<\/a> advantages. After all, any company that manages to extract value from its data and improve its performance through data analysis will be the only company with access to this particular information. Consequently, it will retain an advantage over its competitors even if they copy its products.\r\n\r\nThe power of data, as wielded in the business world, demonstrates that this is more than a technical capacity; it is a fundamental issue on the managerial agenda that affects multiple aspects of a company\u2019s life. The reason is simple: data science can add value in various ways, especially in three key areas.\r\n\r\nFirst, data can help to improve operational performance, allowing a company to do more with less. With data, you can extract the greatest possible value from the available resources by rationalizing costs, thus becoming more efficient.\r\n\r\nSecond, data can be used to create additional sources of income. Many companies have created new products based on data analytics or monetized their data by selling them to third parties.\r\n\r\nAnd third, as noted above, if a company is capable of adequately investing time, effort, and resources in data science, it can obtain additional competitive<\/a> advantages through the implementation of machine-learning algorithms, which become ever more efficient as they learn from the data.\r\n
There is no longer any doubt that data science has the potential to create value and competitive advantages.<\/blockquote>\r\nOperational efficiency<\/strong>\r\n\r\nThere are two possible approaches to improving operational efficiency: reducing costs or increasing the income generated by the company\u2019s core business.\r\n\r\nIn the human resources area, analytics can predict when valuable professionals are about to quit\u2014a problem that is usually not detected until it\u2019s too late. Since a company\u2019s main human resources expenses are derived from precisely this situation, the ability to anticipate a resignation and propose a solution before the employee reaches the breaking point will result in greater efficiency.\r\n\r\nA similar situation exists in the marketing<\/a> area, where one of the main problems is determining the best marketing mix to increase investment efficiency. Data science can be harnessed to find the optimal combination and modify it in response to external conditions. Such an approach would increase the company\u2019s sales<\/a> volume while keeping the marketing department\u2019s budget under control<\/a>.\r\n\r\nFor another example, we can look to UPS. This shipping company has used data science and advanced geographical algorithms to optimize its delivery routes and carry out predictive fleet maintenance. Instead of waiting for a vehicle to break down and then performing unplanned repair work, UPS uses algorithms to predict the likelihood of incidents. As a result, the company is able to schedule fleet maintenance during slow periods.\r\n
If a company is capable of adequately investing time, effort, and resources in data science, it can obtain additional competitive advantages.<\/blockquote>\r\nBusiness transformation<\/strong>\r\n\r\nA company\u2019s journey in data science begins with monitoring. Once it has taken that step, it is capable of extracting knowledge, which it can then incorporate into its operations. The most advanced companies end up transforming their entire business in order to sustain a data-based competitive<\/a> advantage.\r\n\r\nProduct recommendations are a further step in the evolution of data science. This approach doesn\u2019t create any more value for the core business, but it does allow the organization to offer a different product\u2014a data product\u2014based on the available data. This is the last frontier in the adoption of data science, and it implies a new stage of business transformation.\r\n\r\nThe aeronautics division of General Electric provides another good example. In the early 1980s, the division was focused exclusively on selling engines, and its relationship with its customers went no further than that. By incorporating sensors into its engines, GE was able to collect data and move from transactional relationships with its customers to contractual relationships based on service-level agreements. Since GE knew the likelihood that a material would break or work incorrectly, as well as the costs associated with such incidents, the sale of the item functioned as a way of sharing the risk with the customer, thus reducing the total cost of ownership. Moreover, the information asymmetry between GE and the customer put the supplier in a stronger position for negotiations.\r\n\r\nAnother example is Telef\u00f3nica, which is required by law<\/a> to store all information and data provided by smart devices<\/a>\u00a0for five years. Compliance with this requirement entailed a cost intrinsically linked to the core business. Eventually, however, Telef\u00f3nica recognized the value of the collected information, which prompted it to create a company called Smart Steps. What began as a structural cost ended up becoming an entirely new business.\r\n\r\nThe trend, therefore, is to collect, structure, standardize, and transform data, to choose the most appropriate model, and most importantly, to design visualizations that facilitate more effective and valuable decision-making.\r\n\r\n \r\n\r\n\u00a9 IE Insights."],"wpcf-article-extract-enable":["1"],"wpcf-article-extract":["By Ignacio Larr\u00fa<\/strong>. Data have become a strategic element of organizations. In the near future, it may be practically impossible for an organization to do business unless it is fully data-oriented. The strategic step is to treat data as a key business strategy rather than as a purely technical matter. Organizations that have adopted this approach provide proof that it works."],"wpcf-article-summary-enable":["1"],"wpcf-article-summary":["Data should now be treated as a key business strategy rather than as a purely technical matter. Data science can be harnessed to reduce costs and increase the income generated by a company\u2019s core business. In the human resources area, for example, analytics can predict when valuable professionals are about to quit. In marketing, data science can help to determine the best marketing mix to increase investment efficiency. The last frontier in the adoption of data science is the appearance of a new product: a data product. Telef\u00f3nica\u2014a company for which data storage is a structural cost\u2014showed that it was possible to create an entirely new business on the basis of this valuable information."]},"_links":{"self":[{"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/articles\/633831","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/articles"}],"about":[{"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/types\/articles"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/media\/636330"}],"wp:attachment":[{"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/media?parent=633831"}],"wp:term":[{"taxonomy":"schools","embeddable":true,"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/schools?post=633831"},{"taxonomy":"areas","embeddable":true,"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/areas?post=633831"},{"taxonomy":"subjects","embeddable":true,"href":"https:\/\/www.ie.edu\/insights\/wp-json\/wp\/v2\/subjects?post=633831"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}