Presentation on theme: "Scheduling Email communication to reduce Information Overload and Interruptions By Ashish Gupta Ramesh Sharda Robert Greve Manjunath Kamath Oh ! I dream."— Presentation transcript:
Scheduling Email communication to reduce Information Overload and Interruptions By Ashish Gupta Ramesh Sharda Robert Greve Manjunath Kamath Oh ! I dream of an ideal workplace - “an interrupt-free workplace”
1 Objective of the study To improve knowledge worker performance by identifying policies that will :- –Reduce information overload due to emails. –Reduce interruption effect due to emails. To develop a heuristic chart to guide a knowledge worker on email response scheduling. Validate the results of prior research.
2 Prior relevant research on Email Overload & interruptions research First reported by Peter Denning (1982),Later by Hiltz, et. al. (1985), Whittaker, et. al.(1996) and many… According to distraction theory, interruption is “an externally generated, randomly occurring, discrete event that breaks continuity of cognitive focus on a primary task“ (Corragio, 1990; Tétard F. 2000). –Research done HCI is rich but in MS/OR??? Research that looks at the problem of information overload and interruptions simultaneously is scarce. (Speier,et.al.1999, Jackson, et.al., 2003, 2002, 2001), Venolia et.al. (2003)
3 Our approach- SIMULATION Interrupt arrives IL + Interrupt processing Interrupt departs Recall time- RL Pre-processingPost-processing Policies that we are comparing :- Triage: (C1-morning, C1-Afternoon) Scheduled: (C2, C4, C8(jackson, et. al.2003)) Flow (continuous): C Phases of task processing (Miyata & Norman, 1986):- Planning Execution Evaluation
4 Research Model *Utilization: Probability of a knowledge worker being busy (λ/µ) Resource utilization change Task Complexity mix Task Completion time Resource utilization Number of Interruptions per task Interrupt arrival pattern Email Policy
5 Hypothesis Formulation H1: Knowledge worker utilization increases with the increase in the frequency of email hour slots for all levels of task Complexity mix, Resource utilization and Interrupt arrival patterns. H2: The average number of times a simple or complex task gets interrupted increases with the increase in the frequency of email-hour slots, for all levels of Task complexity mix, Resource Utilization and Interrupt arrival patterns. H3: Average completion time for simple or complex tasks increases with the increase in the frequency of email-hour slots, for all levels of Task complexity mix, Resource Utilization and Interrupt arrival patterns.
87 Model Implementation Sn, Cn- new simple & complex task Si, Ci – interrupted simple & complex task E – Email (Interrupt)
8 Statistical analysis of Simulation results Dependent variables % change in utilization # of interruptions per simple task # of interruptions per complex task Average completion time for simple task Average completion time for complex task Effect Policy (P) Workload Level (RU) Task Complexity (TC) Interrupt Arrival Pattern (IAP) P * RU P * TC P * IAP P * RU * IAP P * TC * IAP P * RU * TC P * RU * TC * IAP
12 Contigency framework for Email management ScenarioRankPerformance Measures Worker utilization Avg. no. of interruptions per Simples task Avg. no. of interruptions per Complex task Mean completio n time Simple task Mean completio n time Complex task Mean completio n time Email Scenario 1 R1 (Best) C4 C1A, C1M, C2, C4, J C1MC R2C1A, C1M, C2 C1A, C2CC4C1M, J R3JJJJC4 R4CCCC2C1A R5C1A, CC2 Scenario 6 R1 (Best) C1A, C2, C4 C1A, C2C2C1A, C1M, C2, C4, J C1M, C4C R2C1MC4C1ACJC1M, C4 R3JC1MC4C2, CJ R4CJC1MC1A R5CJC2 R6C
13 Practical implications If other tasks are more important and email communication is secondary ! Check emails 4 times a day with each processing not exceeding 45 min if you want to be most productive. Is timely email processing survival issue for your kind of organization? –Use flow (continuous) policy Use our prescription chart.
14 Future research Perform the study in experimental or field settings. –Use perceived measures of Information overload (NASA-TLX, SWAT) More realistic modeling by incorporating email characteristics More discrete policies Use of other frameworks for task analysis User-interface development Suggestions or comments or Questions????