The reality of many bi g data analytics projects is there are troubling gaps between BI expectatio ns and results. Indeed, company surveys report there are major organization al roadblocks to effectively using BI tools to deliver the right data and r ight analysis to the right decision-maker at the right place and right time . Data transformation initiatives can fail for many reasons, including the root causes of middle manager resistance, among them:
\n\n Data sharing and use of analytics uncovers deficiencies\n Automation implies eliminations\n Analytics-driven innovation disrupts organizational power relationships, of ten favoring technically savvy, fast movers\n\nTo be successful, data ch ange agendas need to include steps designed to overcome senior management&# 39;s distrust and employees' fear of uncertainties. The emergence of ne w, C-level data officers, all with a stake in data transformation initiativ es, is discussed: the Chief Data Officer (CDO), the Chief Analytics Officer (CAO), the Chief Innovation, and Chief Knowledge Officer positions are add ressed with respect to their roles in leading data transformation initiativ es in their companies. Panelists will discuss real-life use cases where cha nge agents successfully navigated their initiatives through uncharted water s, including:
\n\n Lack of data governance responsibilities\n Cultural resistance\n Stakeholder challenges, including the successful use of off-the-shelf proce ss-aids\n\n DTSTART:20180425T104500 SUMMARY:Management of Change for Data Transformation DTEND:20180425T114459 LOCATION: See Description END:VEVENT END:VCALENDAR