Using Process Mining to Generate Accurate and Interactive Business Process Maps

被引:0
|
作者
van der Aalst, W. M. P. [1 ]
机构
[1] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands
来源
BUSINESS INFORMATION SYSTEMS WORKSHOPS | 2009年 / 37卷
关键词
WORKFLOW MANAGEMENT; PROCESS MODELS; SUPPORT; INFORMATION; DISCOVERY; SYSTEMS;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
The quality of today's digital maps is very high. This allows for new functionality as illustrated by modern car navigation systems (e.g., TomTom, Garmin, etc.), Google maps, Google Street View, Mashups using geo-tagging (e.g., Panoramio, HousingMaps, etc.), etc. People can seamlessly zoom in and out using the interactive maps in such systems. Moreover, all kinds of information can be projected on these interactive maps (e.g., traffic jams, four-bedroom apartments for sale, etc.). Process models can be seen as the "maps" describing the operational processes of organizations. Unfortunately, accurate and interactive process maps are typically missing when it comes to business process management. Either there are no good maps or the maps are static or outdated. Therefore, we propose to automatically generate business process maps using process mining techniques. By doing this, there is a close connection between these maps and the actual behavior recorded in event logs. This will allow for high-quality process models showing what really happened. Moreover, this will also allow for the projection of dynamic information, e.g., the "traffic jams" in business processes. In fact, the combination of accurate maps, historic information, and information about current process instances, allows for prediction and recommendation. For example, just like TomTom can predict the arrival time at a particular location, process mining techniques can be used to predict when a process instance will finish.
引用
收藏
页码:1 / 14
页数:14
相关论文
共 50 条
  • [1] Mining Context-Dependent and Interactive Business Process Maps Using Execution Patterns
    Li, Jiafei
    Bose, R. P. Jagadeesh Chandra
    van der Aalst, Wil M. P.
    BUSINESS PROCESS MANAGEMENT WORKSHOPS, 2011, 66 : 109 - +
  • [2] Business process analysis using process mining in accommodation industry
    Kwon, Hyukjin
    Kim, Dongsoo
    ICIC Express Letters, Part B: Applications, 2015, 6 (02): : 577 - 583
  • [3] Verification of business process designs using maps
    Sivaraman, E
    Kamath, N
    NEXT WAVE IN COMPUTING, OPTIMIZATION, AND DECISION TECHNOLOGIES, 2005, 29 : 303 - 318
  • [4] Suitability of process maps for business process simulation in business process renovation projects
    Stemberger, MI
    Jaklic, J
    Popovic, A
    SIMULATION IN INDUSTRY, 2004, : 197 - 205
  • [5] Architecting Business Process Maps
    Poels, Geert
    Garcia, Felix
    Ruiz, Francisco
    Piattini, Mario
    COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2020, 17 (01) : 117 - 139
  • [6] Accurate and Transparent Path Prediction Using Process Mining
    Bernard, Gaeel
    Andritsos, Periklis
    ADVANCES IN DATABASES AND INFORMATION SYSTEMS, ADBIS 2019, 2019, 11695 : 235 - 250
  • [7] A Combined Process Mining for Improving Business Process
    Djedovic, Almir
    Zunic, Emir
    Karabegovic, Almir
    PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON SMART SYSTEMS AND TECHNOLOGIES (SST), 2017, : 143 - 148
  • [8] Representing Business Process Flexibility using Concept Maps
    Mejri, Asma
    Ghannouchi, Sonia Ayachi
    Martinho, Ricardo
    INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS/INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT/INTERNATIONAL CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES, CENTERIS/PROJMAN / HCIST 2016, 2016, 100 : 1260 - 1268
  • [9] Supporting business process redesign using cognitive maps
    Kwahk, KY
    Kim, YG
    DECISION SUPPORT SYSTEMS, 1999, 25 (02) : 155 - 178
  • [10] Process Mining for Semantic Business Process Modeling
    Lautenbacher, Florian
    Bauer, Bernhard
    Foerg, Sebastian
    2009 13TH ENTERPRISE DISTRIBUTED OBJECT COMPUTING CONFERENCE WORKSHOPS (EDOCW 2009), 2009, : 45 - 53