An Analysis of Response Policies under Different Arrival Patterns By Ashish Gupta Ramesh Sharda An Analysis of Response Policies under Different Arrival Patterns By Ashish Gupta Doctoral Student, Department of Management Science & Information Systems, Oklahoma State University, Stillwater. Ramesh Sharda Regents Professor of Management Science & Information Systems, Director, Institute for Research in Information Systems, Oklahoma State University, Stillwater.

01/06/05ICS Objective of the study To improve individual knowledge worker performance by identifying policies that will :- To improve individual knowledge worker performance by identifying policies that will :- To model work environment by considering various characteristics. Improve response time of s and primary task completion time Reduce number of interruptions Validate the results of prior research.

01/06/05ICS Problem significance 2004 AMA Research on workplace & Productivity 2004 AMA Research on workplace & Productivity On a typical workday, time is spent on is ????? On a typical workday, time is spent on is ????? 0–59 minutes 77.9% 0–59 minutes 77.9% 90 minutes–2 hours 18% 90 minutes–2 hours 18% 2–3 hours 2% 2–3 hours 2% 3–4 hours 2.5% 3–4 hours 2.5% Osterman Research- How often do you Osterman Research- How often do you check your for new messages check your for new messages when at work?

01/06/05ICS Problem significance E-Policy Institute (2004) E-Policy Institute (2004) Annual growth rate= 66 % Annual growth rate= 66 % Corporate Research Corporate Research IBM, Microsoft, Xerox, Ferris, Radicati, etc. IBM, Microsoft, Xerox, Ferris, Radicati, etc. Need for more research in MS/IS that Looks at the problem of information overload and interruptions simultaneously. Looks at the problem of information overload and interruptions simultaneously.

01/06/05ICS Extant Research Overload due to s- First reported by Peter Denning (1982). Most recently reported by Ron Weber (MISQ, Editor-in-Chief 2004) Interruptions due to s- Interruptions due to s- Reported by some- Speier,et.al.1999, Jackson, et.al., 2003, 2002, 2001), Venolia et.al. (2003)

01/06/05ICS Extant Research “The nature of managerial work”, Mintzberg (1976) “The nature of managerial work”, Mintzberg (1976) “Managerial communication pattern”, Ray Panko (1992) “Managerial communication pattern”, Ray Panko (1992) “ as a medium of managerial choice”, M. Markus (1994) “ as a medium of managerial choice”, M. Markus (1994) “You have got (Lots and Lots) of mail” in “The Attention Economy” by Davenport (2001) “You have got (Lots and Lots) of mail” in “The Attention Economy” by Davenport (2001) “The Time Famine: Towards a Sociology of Work Time”, Leslie Perlow (1999) “The Time Famine: Towards a Sociology of Work Time”, Leslie Perlow (1999)

01/06/05ICS Phenomenon of Interruption Interrupt arrives IL + Interrupt processing Interrupt departs Recall time- RL Pre-processingPost-processing Interruptions- 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).

01/06/05ICS Previous Research Model Performance Measures 1. % Increase in utilization 2. Number of interruptions per task. 3. Primary task completion time 4. response time. Task complexity (Pure simple) vs. (more-simple & less-complex) vs. (equal-simple & complex) vs. (less-simple & more-complex) vs. (pure complex) Workload Level Low vs. Medium vs. High Policy Flow vs. Scheduled vs. Triage Only “high” dependency on communication (3 hrs) with exponential arrivals was studied

01/06/05ICS Detailed Research model Performance variables (a) % increase in Utilization (b) Time spent due to interruptions (c) Average response time of s (d) Average completion time of primary task. (e) Total no. of interruptions/ day processing strategies (C1, C2, C4, C8, C) characteristics Processing Time* (Large, Small) Arrival Rate (V. Low, Low, High, V. High) Dependency on communication (Very Low, Low, High, Very High) arrival pattern (Expo, NSPS) Work Environment * Processing time is based on category

01/06/05ICS types s differentiated on the basis of its ‘content’ or the ‘action required by the user’ s differentiated on the basis of its ‘content’ or the ‘action required by the user’ Notation typeDiscrete arrival percentage 1Priority 5% 2Spam5% 3Informative 20% 4 with non-diminishing service time 55% 5 with diminishing service time 15%

01/06/05ICS Policies Dependency on Communication Policy typeVery Low (1 hr) Low (2 hrs) High (3 hrs) Very High (4 hrs) Notation# of hour- slots Triage 8am-9am8am-10am8am-11am8am -12 noon C1 1 Schedule 8am-8:30am 4:30pm- 5pm 8am-9am 4pm-5pm 8am-9:30am 3:30 am to 5:00 pm 8am-10am 3pm- 5pm C2 2 Schedule 8am-8:15am, 11am-11:15am 1pm-1:15pm 4:45pm- 5pm 8am-8:30am, 11am-11;30am 1pm-1:30pm 4:30pm- 5pm 8am-8:45 am, 11am-11:45am, 1 pm - 1:45 pm, 4:15 pm - 5:00 pm 8am-9am 11am pm- 2pm 4pm- 5pm C4 4 Schedule 8am-8:08am 9- 9:08am and so on 8-8:15am 9-9:15am 10-10:15am and so on 8-8:23am 9-9:23am 10-10:23am and so on 8- 8:30am 9- 9:30pm :30pm and so on C8 8 Flow Processed as soon as s arrive Processed as soon as s arrive Processed as soon as s arrive Processed as soon as s arrive C Not Applicable

01/06/05ICS Methodology Discrete event simulation using Arena 8.01 Model Run length= 500 days Model Warm-up time= 50 days No. of replications of each model= scenarios evaluated for 5 different policies. Thus, Total number of simulations models= 16 x 5= 80 Total number of data points generated = 80 x 20 = 1600

01/06/05ICS Scenarios Scenarios (E) dependencyE Arrival patternE processing time 1Very lowTime stationary ExpoSmall 2Very lowTime stationary ExpoLarge 3Very lowNon-Stationary ExpoSmall 4Very lowNon-Stationary ExpoLarge 5LowTime stationary ExpoSmall 6LowTime stationary ExpoLarge 7LowNon-Stationary ExpoSmall 8LowNon-Stationary ExpoLarge 9HighTime stationary ExpoSmall 10HighTime stationary ExpoLarge 11HighNon-Stationary ExpoSmall 12HighNon-Stationary ExpoLarge 13Very HighTime stationary ExpoSmall 14Very HighTime stationary ExpoLarge 15Very HighNon-Stationary ExpoSmall 16Very HighNon-Stationary ExpoLarge

01/06/05ICS Parameters S # Type 4 (E) Process ing time (PT) Type 5 E PT (min) Total PT per day Avg. Arrival Rate Primary Task (P) Arrival Rate /dayE UtilP Util Min (E+P) Util Processing time of (a) Type 1 - Expo(10 min) (b) Type 2 - Expo (0.5 min) (c) Type 3 - Expo (5 min) (d) Primary task- Expo(6 min)

01/06/05ICS Bird’s Eye view of Entire model built using Arena Zoom in follows….

Arena flow Snapshot Preempts the KW when an of type 1 arrives during hrs. Stores remaining processing time in an attribute ‘RT’ 3 3 Releases s of type 2,3,4 on the basis of policy s created based on different schedules that determines whether it is Expo or Non-Stationary Expo and at what rate To record output statistics of each type separately Checks if has been in system for > or < than 24 hrs

01/06/05ICS Arena Primary Task Snapshot Attribute RT is reset to 0 to erase the memory. This makes the attribute RT reusable for recording remaining time interrupted primary task in future. Checks to see if RT>0. If yes, RL and IL are added If no, Primary task is sent next processing stage

01/06/05ICS Model Logic New arrival Ei occurs at time T0, for all i ={n : n = 1.. 5} If i = 1, Step1. released at T0. Step2. If STATE (KW) == IDLE & E1.WIP=0 KW seized; Than, Set RT = Ta = 0; IL = 0, RL = 0; Process E1; Release KW; If STATE (KW) == BUSY & E1.WIP=0 Seize KW; Than, Set RT = Ta; Record IL = Tria (a, b, c), Tb; Process E1; Release KW; Calculate; χ = Tb /( Ta + Tb) for all0 ≤ χ ≤ 1 Calculate; RL = {RT * [χ * *( K-1)] * [ (1- χ)* * ( L-1 ) } / Beta (K,L)

01/06/05ICS Model Logic For K = 2, L = 1; For K = 2, L = 1; Calculate; Calculate; T1 = IL + Tb + RL; Seize KW for time T1; Process Pi Set RT=0; Release KW; If i = 2 || 3 || 4 || 5, Step.3 Release Ei, if {(STATE(dummy) == IDLE_RES && Process WIP == 0 && 5 in 1.WIP == 0 && 5 in 2.WIP == 0 ) || ( STATE(anti dummy) == IDLE_RES && Primary.WIP == 0 && NQ(Hold primary.Queue) == 0 && IL Primary.WIP=0 && RL primary.WIP == 0 ) } = TRUE Else Hold;

01/06/05ICS Model logic- comments If New arrival = Pn Step4. Release if, STATE(kW) == IDLE_RES; Else Hold; //***** Tb- Value added time spent on the task Before interruption Ta- Value added time spent on the task After interruption χ - Fraction of task completed before interruption occurred IL – Interruption Lag RL – Resumption Lag Pi – interrupted primary task Dummy resource- implements hours Anti-dummy resource – implements non- hours *****// *****// Stop;

Results (a) Percent Increase in Utilization

Results (b) Additional Time (min) spent per day due to interruptions

01/06/05ICS Response time results Avg. Response Time = Avg. processing time (Value added) + Avg. wait (Queue) time [fig. c] Avg. Primary Task (PT) Completion Time [fig. d.3] = Avg. PT value added processing time + Avg. PT non-value added processing time due recalling & switching [fig. d.1] + Avg. PT wait (Queue) time [fig. d.2]

Results (c) Wait time i.e. inbox queue and holdup time

Results (d.1) Avg. Additional time spent (wasted) in recalling and switching for processing one primary task

Results (d.2) Average Primary Task Wait Time

Results (d.3) Average Primary Task Completion Time

01/06/05ICS Optimal Policy ?? Previous research found C4 as the optimal policy (no consideration was given to arrival pattern and characteristics). Previous research found C4 as the optimal policy (no consideration was given to arrival pattern and characteristics). Current Research found under varying arrival characteristics- Current Research found under varying arrival characteristics- Optimal policy for primary task completion time - C1 & C2 closely followed by C4. Optimal policy for primary task completion time - C1 & C2 closely followed by C4. Optimal policy for response time – C Optimal policy for response time – C Optimal policy for reducing interruptions- C1& C4 closely followed by C2 Optimal policy for reducing interruptions- C1& C4 closely followed by C2

01/06/05ICS Limitations of the model Assumptions of the model are its limitations Assumptions of the model are its limitations Knowledge worker works strictly according from 8 to 12 and then from 1 to 5pm. Need for relaxing the work-hrs. Knowledge worker works strictly according from 8 to 12 and then from 1 to 5pm. Need for relaxing the work-hrs. Knowledge worker is busy only 90% of the time in a given workday. Knowledge worker is busy only 90% of the time in a given workday. KW is working on interruptible primary task. In reality, not all primary tasks are interruptible. For e.g. group meetings KW is working on interruptible primary task. In reality, not all primary tasks are interruptible. For e.g. group meetings Primary task modeled is interruptible only 3 times. Primary task modeled is interruptible only 3 times. s are not interrupted. s are not interrupted.

01/06/05ICS Limitations & future research Perform the study in field or experimental settings. Perform the study in field or experimental settings. Modeling utility/ life of an . Modeling utility/ life of an . Modeling group knowledge network and at organizational level. Modeling group knowledge network and at organizational level. Modeling by incorporating more doses of reality. Considering other communication media along with . Modeling by incorporating more doses of reality. Considering other communication media along with . Suggestions or comments or Questions????