p3 4-gregoris mentzas

Towards Proactive Enterprise Intelligence

Prof. Gregoris Mentzas Director, Information Management Unit

National Technical University of Athens

www.imu.ntua.gr

[email protected]

twitter: gmentzas

FInES Workshop, Future Internet Assembly Aalborg, Denmark, 9th May, 2012

Information Management Unit / ICCS of NTUA www.imu.iccs.gr

Everything generates data

Future Internet Assembly, Aalborg, Denmark 9th May, 2012 2


Enterprise ‘Big Data’

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.


Source: McKinsey

Global Institute (2011)


Proactive 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



Challenges for Proactive Enterprise Intelligence

Fuzzy Decision-making

Process Agility

Predictive Analytics




Process Agility





From 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



Source: Gartner (2012) “Advanced Analytics: Predictive, Collaborative and Pervasive” Feb. 2012



Research 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




Bothos, E., D. Apostolou, G. Mentzas (2010) Using Social Media to Predict Future Events with Agent-based

Markets, IEEE Intelligent Systems, November-December, 2010, pp. 50-58



Process Agility





The 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


Research 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


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



Process Agility





Integrating 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



Research 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



Process agility in logistics

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

Logistics managers are tapping early capabilities to get knowledge of changing

conditions and increase their ability to make proactive route adjustments



Process Agility





Capabilities 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


Contact

Prof. Gregoris Mentzas

Director, Information Management Unit

National Technical University of Athens

W: www.imu.ntua.gr

E: [email protected]

http://www.imu.ntua.gr

Thank you for your attention!

p3 4-gregoris mentzas

Technology

criteria decision

grresearch

denmark 9th

gregoris mentzasdirector

denmark 9th

denmark 9th

ntua www

ntua www