Communication-Based Business Process Task Detection - Application in the CRM Context

During the last decades, several research works have been conducted in Business Process Management (BPM) field, and a whole range of tools allowing capturing and managing the business process (BP) has been proposed. However, the current BPM systems leave aside the informal work, which is often based on communication and collaborative tools. In this paper, we introduce the concept of "communication-based manual task" in the BP design. It is a kind of a BP activity which is associated to a set of semantic patterns that enable the qualification of communication content as an achievement of the BP task. This association of semantic patterns with BP activities enables the system to capture informal work, done through communication and collaborative tools such as: email, phone calls, instant messaging, etc. We have implemented and applied the proposal to the customer relationship management (CRM) field in order to respond to the challenges induced by the variety of communication channels. We highlight two main advantages compared to classical CRM approaches. It firstly enables the reconstruction of the customer journeys across the communication channels and secondly identifies all BP actors who are involved in the customer journey; providing by this way a mean to promote collaboration between communication channels teams.

[1]  Jianmin Wang,et al.  Mining process models with non-free-choice constructs , 2007, Data Mining and Knowledge Discovery.

[2]  Ricardo Seguel,et al.  Process Mining Manifesto , 2011, Business Process Management Workshops.

[3]  Jian Pei,et al.  Email mining: tasks, common techniques, and tools , 2013, Knowledge and Information Systems.

[4]  Noël Crespi,et al.  Enterprise Social Systems: The What, the Why, and the How , 2015, 2015 IEEE 17th Conference on Business Informatics.

[5]  Bruce Krulwich,et al.  The ContactFinder Agent: Answering Bulletin Board Questions with Referrals , 1996, AAAI/IAAI, Vol. 1.

[6]  Fernanda B. Viégas,et al.  Visualizing email content: portraying relationships from conversational histories , 2006, CHI.

[7]  Purnima S. Sangle,et al.  Contemporary challenges in CRM technology adoption: a multichannel view , 2014 .

[8]  Yi Zhang,et al.  Graph-based ranking algorithms for e-mail expertise analysis , 2003, DMKD '03.

[9]  Flávia Maria Santoro,et al.  eMail Mining: Knowledge intensive process discovery through e-mails , 2012, Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[10]  Wil M. P. van der Aalst,et al.  Workflow mining: discovering process models from event logs , 2004, IEEE Transactions on Knowledge and Data Engineering.

[11]  Boudewijn F. van Dongen,et al.  Process Mining for Ubiquitous Mobile Systems: An Overview and a Concrete Algorithm , 2004, UMICS.

[12]  Dan I. Moldovan,et al.  Acquisition of semantic patterns for information extraction from corpora , 1993, Proceedings of 9th IEEE Conference on Artificial Intelligence for Applications.

[13]  Dimitrios Gunopulos,et al.  Mining Process Models from Workflow Logs , 1998, EDBT.

[14]  Wil M.P. van der Aalst,et al.  Process mining with the HeuristicsMiner algorithm , 2006 .

[15]  Bo Hu,et al.  Refining Process Models through the Analysis of Informal Work Practice , 2011, BPM.

[16]  Romain Laroche,et al.  Raisonnement sur les incertitudes et apprentissage pour les systèmes de dialogue conventionnels , 2010 .

[17]  Bernardo A. Huberman,et al.  Email as spectroscopy: automated discovery of community structure within organizations , 2003 .

[18]  Paul P. Maglio,et al.  Expertise identification using email communications , 2003, CIKM '03.