Claudio Bartolini PhD defense presentation. Ferrara, March 20, 2009

1. Business-driven IT management Claudio Bartolini Supervisor: Prof. Cesare Stefanelli

2. Context and motivation Business-IT alignment IT management is broader than network and system management Dimensions of IT management: People Technology Processes Optimizing for IT metrics is not the same as optimizing for business metrics Successful alignment of business and IT requires a thorough understanding of the impact of IT on business processes and business results, and vice versa

3. Contributions Review of state of the art Decision theoretical framework for business-driven IT management Based on quantitative re-definitions of terms such as business impact, risk, urgency A simple “template” BDIM solution for incident prioritization A complete BDIM solution for organizational redesign of an IT support organization

4. Contributions Review of state of the art Decision theoretical framework for business-driven IT management Based on quantitative re-definitions of terms such as business impact, risk, urgency A simple “template” BDIM solution for incident prioritization A complete BDIM solution for organizational redesign of an IT support organization

5. State of the art Industry COBIT, ITIL, SOX Academia Series of IEEE workshops on business-driven IT management Some early work on service level management, capacity management, security management, incident management, change management Reviews of the state of the art and research directions: Machiraju, Bartolini, and Casati, Technologies for Business–Driven IT Management,in “Extending Web Services Technologies”, Kluwer Academic Moura, Sauve, Bartolini: Research Challenges of Business-driven IT management, Proceedings of IEEE BDIM 2007 Moura, Bartolini, Sauve, Business-driven IT management: Upping the ante of IT, IEEE Communications Magazine 46, n.10, pp. 146-153 Bartolini et al (eds), Business-driven IT management – Information Technology from a business perspective , Proceedings of IEEE BDIM 06-09, vol I-IV, IEEE Press

6. Positioning the work IT ServiceManagement Autonomic Computing IT Governance DecisionSupport Automation

7. Anatomy of a BDIM solution Identify business metrics of interest Select (technical) performance metrics of interest Model relevant entities and business-IT linkage models Validate models and improve if necessary Use the validated model to support decisions concerning IT solution scenarios (step 2) Evaluate gains in business results, compare to business goals

8. Modeling requirements for business-driven IT management Modeling of all aspects of IT: infrastructure, processes and tools, people Modeling (legacy) IT infrastructure Modeling of IT and business processes Modeling human behavior Modeling of financial aspects Modeling of monetizable costs and benefits Modeling of intangible costs and benefits Modeling risk Modeling viewpoints of multiple stakeholders Extensive validation

9. Contributions Review of state of the art Decision theoretical framework for business-driven IT management Based on quantitative re-definitions of terms such as business impact, risk, urgency A simple “template” BDIM solution for incident prioritization A complete BDIM solution for organizational redesign of an IT support organization

10. Decision theoretical framework for BDIM Motivation: ITIL and COBIT use naïve definitions of terms such as impact, cost, risk and urgency to prioritize courses of action Approach: Define a utility function expressing stakeholder’s preferences (e.g. business impact or net cost) Define risk as the variance of the utility function Define urgency as the rate of change in time of utility

11. Contributions Review of state of the art Decision theoretical framework for business-driven IT management Based on constructive re-definitions of terms such as business impact, risk, urgency A simple “template” BDIM solution for incident prioritization A complete BDIM solution for organizational redesign of an IT support organization

12. An approach to BDIM business-IT linkage models Define business objectives information model Based on Business Scorecard and COBIT Define alignment with a business objective is the measure of the likelihood – given the best knowledge about the current situation – that the objective will be met. Apply prediction techniques to estimate likelihood that objectives will be met Choose among options by maximizing alignment with objectives Described in: Bartolini et al., IT Service Management driven by Business Objectives – An Application to Incident Management, In Proc. IEEE NOMS 2006

14. Incident assigned to one priority level

16. Contributions Review of state of the art Decision theoretical framework for business-driven IT management Based on constructive re-definitions of terms such as business impact, risk, urgency A simple “template” BDIM solution for incident prioritization A complete BDIM solution for organizational redesign of an IT support organization

17. A complete BDIM solution for incident management Analysis of the incident management process Metrics for performance evaluation of the IT support organization Optimizing the incident management process through simulation Visualization techniques for guided performance analysis

18. Analysis of the incident management process Described in Barash, Bartolini and Wu, Measuring and Improving the Performance of an IT Support Organization in Managing Service Incidents, in Proc. IEEE BDIM 2007

19. Evaluating performance of the IT support organization Routing between assignment groups Number of reassignments Time to closure after reassignment Number of incidents with largeprocessing time Number of assignment cycles Number of cross-level reassignments Operations within assignment groups Number of incidents treated Number of incidents received vs. number resolved Assignment groups that were bottlenecks Mined logs of real installations to extract values for the metrics, described in Barash, Bartolini and Wu, Measuring and Improving the Performance of an IT Support Organization in Managing Service Incidents, in Proc. IEEE BDIM 2007

20. Optimizing the incident management process through simulation Operator transaction time determined from history assuming a lognormal distribution of work time Support group transition probability determined from history to be equal to the observed transition frequency Incident generation and closure dealt consistently with transition: Incident generation is done through re-sampling of the historic incident pool Incident closure is treated as a transition to the “resolved” state Described in Bartolini, Stefanelli and Tortonesi, “SYMIAN: a Simulation Tool for the Optimization of the IT Incident Management Process”, In proc. IEEE DSOM 2008

21. Incident transitions frequency Used as transition matrix for the incident transition process between workgroups

22. Experiments Is the process really Markovian (memory-less)? We expected to experience some some loss of information due to memory-less-ness assumption Example: the probability of closure of an incident by a support group may be dependent on the age of the ticket Bayesian correction of the default “transition probability equals transition frequency” assumption However, the experiments confirmed that the loss of information is virtually nil

23. Experimental results show high fidelity Incident count Support group Number of incidents Number of reassignments

24. Visualization techniques for guided performance analysis Described in Bartolini, IT Incident Management as a Collaborative Process: a Visualization Tool inspired to Social Networks, In Proc. ACM SIGCHI CollaborateCom 2008

25. Impact of the research Technology transferred into HP products for IT Analytics Patent applications Publications

27. Conclusions Context: Business-driven IT management Contributions: Review of state of the art Decision theoretical framework for business-driven IT management A simple “template” BDIM solution for incident prioritization A complete BDIM solution for organizational redesign of an IT support organization