Presentation on theme: "Four Eras of Analytics Thomas H. Davenport, Babson College/MIT/Deloitte/International Institute for Analytics UNC Charlotte Analytics Frontiers Conference."— Presentation transcript:
2 Changing the Way Analytics Are Done Small, structured, static dataBack-office analystsSlow, painstakingInternal decisionsSpreadsheets/OLAP/EDWDescriptive analyticsBig, unstructured, fast-moving dataRise of data scientistsData products in online firmsRise of Hadoop and open sourceVisual analytics“Agile is too slow”Mix of all dataInternal/external products/ decisionsAnalytics a core capabilityMove at speed and scalePredictive and prescriptive analyticsAnalytics embedded, invisible, automatedCognitive technologies“Robotic process automation” for digital tasksAugmentation, not automation1975-?2001-?2013-?2016-?
8 Why Move to Cognitive? Too much data Expensive labor Humans not good decision-makersTedious workPowerful technologies
9 A Smooth Transition from Analytics to Cognitive Traditional AnalyticsCorrelation/RegressionNaturalLanguageProcessingNeuralNetworksLogisticRegressionDeepLearningTextAnalyticsMachineLearningCognitive Technologies
22 Implications for Organizations Take an augmentation perspective from the beginningStart a pilot and develop a platformPick the right cognitive technology for your problemGet good at work design for smart humans and smart machinesGive your people the options and the time to transition to themPut someone in charge of thinking about this
23 Prerequisites for 3.0 and 4.0 Organizations No silos of people, data, or technologyLeaders who get it and are willing to engage and investRelatively few battles between the business and ITA strategy that focuses on services and processes, not just the best productsA willingness to pursue this for the long haul
24 Some Concerns About 4.0We don’t fully understand rapid, automated, interconnected decisions“Flash crash”Power outagesSnowstorms and air transportationNeed to model dynamic interactions of human and machine behaviors