P3 4-gregoris mentzas
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Prof. Gregoris Mentzas, Director, Information Management Unit

Prof. Gregoris Mentzas, Director, Information Management Unit
(National Technical University of Athens) presented "Towards Proactive Enterprise Intelligence" (FInES Workshop at Aalborg)

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P3 4-gregoris mentzas P3 4-gregoris mentzas Presentation Transcript

  • Towards Proactive Enterprise IntelligenceProf. Gregoris MentzasDirector, Information Management UnitNational Technical University of Athenswww.imu.ntua.grgmentzas@mail.ntua.grtwitter: gmentzas FInES Workshop, Future Internet Assembly Aalborg, Denmark, 9th May, 2012
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grEverything generates data Future Internet Assembly, Aalborg, Denmark 9th May, 2012 2
  • Information Management Unit / ICCS of NTUA www.imu.iccs.gr
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grEnterprise ‘Big Data’ Source: McKinsey Global Institute (2011) A 2011 study by MIT found that effective use of data and analytics correlated with a 5 to 6 percent improvement in productivity, profitability & market value.  Erik Brynjolfsson, Lorin M. Hitt, and Heekyung Hellen Kim, “Strength in numbers: How does data-driven decision making affect firm performance?” Social Science Research Network (SSRN), April 2011. Future Internet Assembly, Aalborg, Denmark 9th May, 2012 4
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grProactive enterprise capabilities Ability for early recognition and exploitation of opportunities.  ability to act agilely to changes in demand for a product  respond to an emerging customer need Ability to alter the likelihood that negative outcomes will occur by intervening prior to their occurrence  prevent the loss of a customer to a competitor  initiate measures to mitigate costs of interruptions in processes Future Internet Assembly, Aalborg, Denmark 9th May, 2012 5
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grChallenges for Proactive Enterprise Intelligence Fuzzy Predictive Decision- Analytics making Process Agility Future Internet Assembly, Aalborg, Denmark 9th May, 2012 6
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grChallenges for Proactive Enterprise Intelligence Fuzzy Predictive Decision- Analytics making Process Agility Future Internet Assembly, Aalborg, Denmark 9th May, 2012 7
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grFrom Business Analytics to Predictive Analytics Next generation analytics will expand beyond measuring and describing the past to predicting what is likely to happen, and optimizing what should happen Need for analytic tools that are self-directed  Unlike services triggered by a person, a device or software application and implement continuous intelligence  they run nonstop and incorporate mobile, social and collaborative consumer interactions Future Internet Assembly, Aalborg, Denmark 9th May, 2012 8
  • Information Management Unit / ICCS of NTUA www.imu.iccs.gr Source: Gartner (2012) “Advanced Analytics: Predictive, Collaborative and Pervasive” Feb. 2012 Future Internet Assembly, Aalborg, Denmark 9th May, 2012 9
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grResearch Challenges for Predictive Analytics Future Internet Enterprises need to  be able to adopt data-driven processes in order to comprehend and predict changes in their business environment. Research challenges include:  Big Data and Text Analytics  Social Network mining  Predictive modelling  Machine learning techniques  Processing of structured and unstructured data  Semantic services based on big and linked data Future Internet Assembly, Aalborg, Denmark 9th May, 2012 10
  • Information Management Unit / ICCS of NTUA www.imu.iccs.gr Bothos, E., D. Apostolou, G. Mentzas (2010) Using Social Media to Predict Future Events with Agent-based Markets, IEEE Intelligent Systems, November-December, 2010,May,50-58 Future Internet Assembly, Aalborg, Denmark 9th pp. 2012 11
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grChallenges for Proactive Enterprise Intelligence Fuzzy Predictive Decision- Analytics making Process Agility Future Internet Assembly, Aalborg, Denmark 9th May, 2012 12
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grThe inherent uncertainty of proactive business Predicting business issues cannot lead to exact solutions Uncertainty whether a business situation actually occurred or on the predicted value of a specific information item, increases the need for adopting probabilistic approaches  Augmenting decision-making processes with fuzzy and linguistic approaches Future Internet Assembly, Aalborg, Denmark 9th May, 2012 13
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grResearch Challenge III: Fuzzy Decision Making Research challenges to augment decision-making:  Uncertain data management  Fuzzy Multiple-Criteria Evaluation  Probabilistic multi-criteria decision making  e.g. Hidden Markov processes, Bayesian Belief Networks etc  Statistical inference and learning approaches  e.g. Markov Decision Processes, Markov Learning Networks  Fuzzy Semantic Web techniques  Linguistic modeling techniques Future Internet Assembly, Aalborg, Denmark 9th May, 2012 14
  • Information Management Unit / ICCS of NTUA www.imu.iccs.gr Fuzzy linguistic approaches in service selection Patiniotakis, I., D. Apostolou, G. Mentzas (2011) Fuzzy UTASTAR: A method for discovering utility functions from fuzzy data, Expert Systems with Applications, Vol. 38, 12, Nov-Dec 2011, 15463-15474 Patiniotakis, I., D. et al (2012) Linguistic Multi-criteria Decision Making for Web service Selection, ICCS working paper, 2012 Future Internet Assembly, Aalborg, Denmark 9th May, 2012 15
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grChallenges for Proactive Enterprise Intelligence Fuzzy Predictive Decision- Analytics making Process Agility Future Internet Assembly, Aalborg, Denmark 9th May, 2012 16
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grIntegrating analytics for agile process flows Predictive capability as a mode of operation used to rapidly produce analytical information based on event data from business processes in order to support decision making  Businesses aim to use analytics for business process innovation and differentiation Organizations effective in the integration of predictive analytic capabilities and fuzzy decision making within business processes will be seeing lower costs and greater business impact Future Internet Assembly, Aalborg, Denmark 9th May, 2012 17
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grResearch Challenges for Process Agility Process agility represents a set of techniques and technologies that incorporate BPM, Complex Event Processing, and Artificial Intelligence Research challenges include:  Semantics in event-driven processing  Event stream processing in business processes  Events in human-oriented tasks  Event-driven business process management  Context perception and situational awareness  Situation-driven process adaptation  Goal-oriented event-driven process agility Future Internet Assembly, Aalborg, Denmark 9th May, 2012 18
  • Information Management Unit / ICCS of NTUA www.imu.iccs.gr Process agility in logistics Logistics managers are tapping early capabilities to get knowledge of changing conditions and increase their ability to make proactive route adjustments Patiniotiakis, I., et al (2011) A Framework for Situation-Aware Adaptation of Service-Based Applications, 4th European ServiceWave Conference, Poznan, 26-28 /10/11 Magoutas, B. D. Apostolou, G. Mentzas (2012) An event-driven Framework for Business Awareness Management, ICCS working paper, February 2012
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grChallenges for Proactive Enterprise Intelligence Fuzzy Predictive Decision- Analytics making Process Agility Future Internet Assembly, Aalborg, Denmark 9th May, 2012 20
  • Information Management Unit / ICCS of NTUA www.imu.iccs.grCapabilities of Proactive Enterprise Intelligence Capability to reveal insights and extract - previously hidden – meaningful patterns from structured and unstructured ‘big data’ from a multitude of sources  sensors and actuators embedded in objects  customer transactions  social interactions, GPS trails, etc. Capability to be proactive, i.e. to be able to develop predictions and implement respective actions  recognize possible opportunities or threats  before these actually happen and  trigger appropriate actions Future Internet Assembly, Aalborg, Denmark 9th May, 2012 21
  • Thank you for your attention! http://www.imu.ntua.grContactProf. Gregoris MentzasDirector, Information Management UnitNational Technical University of AthensW: www.imu.ntua.grE: gmentzas@mail.ntua.gr