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DEALING WITH COMPLEXITY – ADVANCED SENSE MAKING WITH GENERATIVE AI

SIM

Course overview

DEALING WITH COMPLEXITY – ADVANCED SENSE MAKING WITH GENERATIVE AI
Categories

AI/Machine Learning

degree award
Provider

SIM

academic level
Course type

Instructor-Led

projected fees
Course fee

(including GST)

Full Fee with GST : $1,635.00

funding subsidy
Funding/Subsidy

SkillsFuture Credit

IBF Funding

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DEALING WITH COMPLEXITY – ADVANCED SENSE MAKING WITH GENERATIVE AI

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Submit an enquiry
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Course Overview

This program is designed to help participants develop practical skills in taking a sense making approach and leverage Generative AI tools to problem solving and making informed decisions. But why sense making? 

This is the process by which people make sense of the data or information associated with the decision to be made or the problem to be solved (Weick, Sutcliffe & Obstfeld, 2005).

Application of Sense Making to Deal with Complexity

Problem statement: How might coworkers at a bank branch redesign their queueing system to improve customer experience? It highlights two main types of queueing systems:

1. Pooled system: Uses generic services with fewer resources, resulting in shorter customer waiting times and higher bank profitability.

2. Dedicated system: Offers specialized services, improving service quality but leading to longer waiting times and lower profitability.

Which system delivers more value to the bank and customer? The choice depends on how bank workers collectively interpret the information and perspectives regarding the system.

Bank coworkers use data to drive innovation through design thinking and agile methods. They analyze market trends and customer data to understand customer needs, pain points or interpret feedback from prototype testing and sales figures from minimum viable products. This understanding is key to developing client-centric services and solutions. 

As digital technologies are disrupting traditional business models in a fast-changing business environment, customer data is evolving at such a fast pace. Hence, gaining deep customer insights or analyzing sales data on minimum viable products is often difficult and complex.

To this end, this two-day program is designed to introduce participants to a practical approach comprising a variety of sense making tools and frameworks that guide them towards making informed and balanced decisions in banking and financial services.


Course benefits

By the end of this course, participants will be able to accomplishing the following through the support and integration of Generative AI tools:

1. Perform analysis on data using System Thinking Theories  

2. Evaluate data to ensure appropriate usage for informed decisions  

3. Make connections and formulate an action plan to manage the challenge in compliance with existing regulations  

4. Reflect and extrapolate possible positive and negative impacts for enhancement and/or alteration


Course outline

Analyse data using System Thinking Theories  

• Introduction to Sense Making

• Types of Information sources 

• Information Analysis (e.g., Data Collection, Data Visualization, Data Exploration, Data Sensing)

• System Thinking Theories (e.g., Interconnectedness, Feedback Loops)

Evaluate data and insights for informed decisions

• Limitation & Impacts of Information Sources 

• Blind spots and Different Viewpoints in decision-making

• Underlying Factors on decision-making (e.g., Cognitive, social and cultural influences)

• Decision Formulation (e.g., Decision matrix, Risk assessment, Cost benefit analysis)

Make connections and formulate an action plan in compliance with regulations  

• Strategy Formulation based on information analysis and evaluation

• Understanding compliance in strategy formulation (e.g., government regulations and internal policies)

Reflect and extrapolate possible impact 

• Extrapolation Techniques for predicting trends and future scenarios

• Reflection on decision-making (E.g., Learning from others, feedback, anticipate future trends, assess impact)


The Generative AI tools to be demonstrated in the classroom include ChatGPT, Claude, Gemini, Copilot, and Perplexity.*


Duration

2 Days

Who should attend?

Level 4 - Managers
Level 5 - Senior Managers & Directors

Programme leader

Course fee

Certification:

1. fulfilled 75% class attendance and 

2. attained a competency (100%) for the assessment 


Programme Fees

Full Course Fee: $1635 (inclusive of 9% GST)


Nett Fee (after IBF funding) *:

Individual = $585 (SC above 40 yo)/ $885 (SC below 40 yo & PR)

Corporate Sponsor = $585 (SC above 40 yo)/ $885 (SC below 40 yo & PR) (Applicable to FINANCIAL SECTOR only)

This IBF-STS scheme is available for both self-sponsored and company-sponsored individuals; and only available to locals employed in the financial sector, and/or financial institutions or Fintech firms certified by Singapore FinTech Association (SFA)


For Self Sponsored Participants:

SkillsFuture Credit is applicable for Singapore Citizens aged 25 years old and above only

Inclusive of 9% GST (GST is based on Full Course Fee)

*Terms and conditions apply


Programme Executive In Charge : Patricia Lee

Telephone : 62489447

Email : patricialee@sim.edu.sg

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