{"id":3023,"date":"2017-06-06T15:13:32","date_gmt":"2017-06-06T15:13:32","guid":{"rendered":"https:\/\/www.peeriosity.com\/shared-services\/articles\/?p=3023"},"modified":"2022-09-06T22:10:56","modified_gmt":"2022-09-06T22:10:56","slug":"performing-data-mining-and-analytics-in-a-shared-services-environment","status":"publish","type":"post","link":"https:\/\/www.peeriosity.com\/shared-services\/articles\/2017\/06\/performing-data-mining-and-analytics-in-a-shared-services-environment\/","title":{"rendered":"Performing Data Mining and Analytics in a Shared Services Environment"},"content":{"rendered":"

Introduction<\/strong><\/span><\/p>\n

As mature Shared Services organizations look to expand their suite of service offerings, one area that seems to be well-suited is Data Mining & Analytics<\/a>.\u00a0 Being able to provide this type of expert service to the company as a whole can help to position Shared Services as much more than a transactional services provider and help to improve the value proposition of the overall Shared Services operation.\u00a0 However, as is the case with any new area of expertise, the challenge faced by Shared Services organizations is the ability to develop capabilities in data mining and analytics on a smaller scale before rolling out the capabilities to other organizations in the company.\u00a0 A track record of success is a great foundation, with the best opportunity to achieve a broader scope<\/a> that is combined with a lower risk of failure.<\/span><\/p>\n

Company Experience<\/strong><\/span><\/p>\n

On a recent Peeriosity PeercastTM<\/sup>, a global technology manufacturer with nearly $60 billion in revenue and more than 100,000 employees shared their approach to performing Data Mining & Analytics in a Shared Services environment.\u00a0 The presenter, who is a Data Scientist working in their Shared Services hub in Central America, first provided some background information regarding Data Science, describing it as an interdisciplinary field about scientific methods, processes, and systems, that is based upon mathematics, statistics, information science, and computer science.\u00a0 Of utmost importance was that Data Mining & Analytics needs to add value by driving change and increasing decision-making capabilities within the company.<\/span><\/p>\n

The feature company placed a lot of emphasis on building a diverse toolbox for their Data Mining & Analytics function, with the following points being stressed:<\/span><\/p>\n