Service Analytics and Process Mining

Date: 8 Jun, 9 Jun 2023 | 9am-5.30pm | Classroom Learning

Duration: 2 Days

Course Overview

The use of IT-based systems to capture transactions and all forms of interactions with the customers is prevalent in organisations. However, many organisations are not extracting insights from the service process data. This hinders organisations to better understand the customer experience journey and discover problems/opportunities that lie within the service processes. This course examines the weaknesses of current approaches to monitoring and managing service delivery, and introduces the domain of service analytics. It teaches the use of a process mining software to automate process discovery and to understand process maps derived from service event data. Applications of service analytics and process mining in various industries will be discussed.

This module is part of Professional Certificate in Technology-Enabled Service Innovation and Digital Innovation Leadership

Course Objectives

This course will equip learners with the following competencies:

  • Understand how business analytics methods can be applied to improve service delivery
  • Apply data mining techniques to enhance service processes
  • Learn to use a process mining tool to automate process discovery and seek service process improvements
  • Through the course, learners from various industries that employ IT-based service delivery and support systems will know how to utilise service process data to improve business processes

Who Should Attend

Business Unit Heads, Senior and Middle Managers, Executives


At least a polytechnic diploma

Course Convener

(Click their photos to view their short biographies)

ccccc Oh Lih Bin

Assoc Prof Oh Lih BinAssoc Prof Oh Lih Bin

Course Fees

Singapore Citizens
39 years old or younger
40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants

Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes

Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.

To enquire, email

To register, click Register

Course Code:
TGS-2022014099 (Classroom Learning)
TGS-2022014100 (Synchronous e-learning)

For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:

Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Advanced Computing for Exe (Faculty/Department / Unit)

Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.

Course Fee Breakdown


Singapore Citizens

Singapore Citizens

39 years old or younger

Singapore Citizen

40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants