Boris Scharinger, Siemens | RapidMiner Wisdom 2016
01. Boris Scharinger, Siemens, Visits theCUBE!. (00:21) 02. What Is An Audit Person Doing At This Conference. (00:36) 03. Tell Us About The scope Of Your Activity. (01:39) 04. Are You A Service Organization. (02:41) 05. What Is The Business Objective. (03:56) 06. Are You Providing Data Science Services To Help Improve Data Predicability. (05:08) 07. When Did You Move From Doing The Financial Audit Into Doing The Other Things. (05:54) 08. How Do You Prioritize The Projects. (08:18) 09. What Are Some Of The Things You've Done That Weren't Data Science. (09:11) 10. Do You See Yourselves Building Predictive Analytic Systems That Are Extentions. (10:50) 11. Do You See Data A Thousand Scientists Blooming Among The Lines Of Business. (13:37) 12. What Do You Want To See From The Technology Industry. (15:07) https://siliconangle.com/2016/01/21/siemens-it-audit-wields-analytical-weaponry-rmwisdom16/ #theCUBE #RapidMiner #SiliconANGLE #RMWisdom16  --- --- Siemens IT audit wields analytical weaponry | #RMWisdom16 by Betsy Amy-Vogt | Jan 21, 2016 You wouldn’t normally think of predictive analytics as the domain of an IT audit department, but Siemens AG is taking the opinion out of audit discussions and using an analytical approach that allows its auditors to become problem solvers that help business units to improve operational efficiency. Boris Scharinger, director, IT auditor at Siemens, talked with Dave Vellante, cohost of theCUBE, from the SiliconANGLE Media team, at RapidMiner Wisdom 2016 in New York City. Using analytical weaponry to replace opinion with facts “We’re using the analytical weapons of data science,” said Scharinger. “… data science adds so much value to our daily audit work by replacing opinion with facts.” Siemens has a global audit staff of 300, with 70-80 percent of the focus on financial systems and processes and 20-30% detecting issues and helping business units become more efficient. After weathering a corruption scandal, Siemens transformed into helping business units to improve efficiency. Now it has developed a reputation for problem solving, and it constantly has a list of candidate projects, with three to four projects in process in parallel. When asked how they prioritize, Scharinger responded that prioritization can be driven by the opportunity to educate business units to become data scientists themselves. “Can you plant some seeds that will show their potential in two to three years from now?” he asked. Speeding Brazilian imports Quoting the specific use case of a company involved in importing product into Brazil, Scharinger described how originally only a very small percentage of shipments followed the shortest route through the customs and paperwork process, with the majority of shipments taking up to 60 days to enter the country. By understanding the full process, the audit identified the root causes of the delays. A concrete set of actions was established, and the majority of shipments now follow the ideal path and are fast-tracked into the country. Data-mining + business process management = process mining Scharinger believes that “data mining is not concrete enough, not process driven enough, not actionable enough,” he told theCUBE. He is a strong promoter of process mining: the merger of data-mining and business process management. @theCUBE @RapidMiner, Inc. @Siemens @SiliconANGLE theCUBE #RMWisdom16