"Cracking the Code: How Business Analysts Use AI for Root Cause Analysis" 🤖🔍

Jan 1
4 min read

In the dynamic world of business analysis, identifying the root cause of a problem is a fundamental skill. But with the sheer volume of data in today’s business landscape, manual methods often fall short. Enter Artificial Intelligence (AI)—a game-changing tool that empowers Business Analysts (BAs) to perform faster, more accurate, and actionable Root Cause Analysis (RCA).

This blog explores how BAs can leverage AI tools to uncover the “why” behind business issues, complete with a step-by-step approach, practical applications, and examples from the Finance and Supply Chain Management domains.

What is Root Cause Analysis (RCA)?

Root Cause Analysis is the process of identifying the fundamental reasons behind a problem or issue. Instead of addressing symptoms, RCA focuses on solving the underlying cause to prevent recurrence.

Traditional RCA Challenges:
- Time-intensive manual data collection.
- Human bias in analyzing data patterns.
- Difficulty in handling large datasets.

AI’s Role in RCA :With AI, BAs can quickly analyze vast datasets, detect patterns, and uncover hidden insights that point to the root cause. This eliminates guesswork and accelerates problem resolution.

Step-by-Step Cadence for Using AI in RCA

1. Define the Problem Clearly ✍️

The first step is identifying and framing the issue.

BA’s Role:
- Engage stakeholders to understand the problem’s impact on business goals.
- Document the issue in a Problem Statement format.

Example :In a Finance domain project, the company notices that monthly revenue is consistently falling short of projections.

2. Gather and Prepare Data 📊

AI tools require clean, relevant data to deliver accurate results.

BA’s Role:
- Collaborate with Data Engineers to extract data from relevant systems (e.g., ERP, CRM).
- Validate data accuracy and format it for AI processing.

Example Tools:

ETL tools like Alteryx or Talend.
Data platforms like Tableau Prep or Power Query.

3. Input Data into AI Tools 🤖

Leverage AI-powered tools to analyze data and identify root causes.

Popular Tools:
- Power BI with AI visualizations.
- Tableau with AI extensions.
- Google AI or Azure AI for anomaly detection.

BA’s Role:

Configure the tool to focus on key variables (e.g., time period, region, customer segments).
Use machine learning algorithms to identify patterns and anomalies.

Example :In a Supply Chain project, AI detects a spike in shipping delays correlated with a particular vendor.

4. Analyze AI-Generated Insights 🔎

AI tools generate a range of insights, but it’s up to the BA to interpret them effectively.

BA’s Role:
- Prioritize findings based on business impact.
- Use visualizations to present complex data in an understandable format.

Example Insight :AI identifies that late payments from clients in the Finance domain stem from unclear invoicing processes, not economic conditions as initially suspected.

5. Validate Findings with Stakeholders 🤝

Ensure that AI-driven insights align with stakeholder observations and business context.

BA’s Role:
- Conduct stakeholder workshops to discuss findings.
- Validate root causes through cross-functional collaboration.

Example :In a Supply Chain project, the BA confirms with the operations team that vendor delays are caused by outdated contract terms.

6. Propose and Implement Solutions 💡

With the root cause identified, the BA can recommend actionable solutions.

BA’s Role:
- Develop a Change Management Plan for implementing solutions.
- Collaborate with teams to track improvements using AI-based dashboards.

Example :To resolve late payments, the BA automates the invoicing process using AI-driven chatbots that notify clients of upcoming due dates.

Case Study 1: Finance Domain

Scenario :A retail company’s finance department reports a 10% drop in quarterly revenue.

Approach Using AI:

Extracted financial transaction data for analysis.
Used Google AI to detect anomalies, discovering that a particular product category had unexpected refunds.
Root Cause: A recent system update caused pricing errors, leading to overcharges and subsequent refunds.
Solution: Fixed pricing algorithms and implemented automated alerts for future discrepancies.

Case Study 2: Supply Chain Management

Scenario :A manufacturing company experiences frequent production delays.

Approach Using AI:

AI tools analyzed supplier performance data and inventory levels.
Identified that Vendor A consistently delayed deliveries due to capacity issues.
Root Cause: Lack of alignment between the vendor’s production schedule and the company’s demand forecast.
Solution: Established real-time demand sharing with the vendor using an AI-integrated platform, reducing delays by 30%.

Benefits of AI in RCA for Business Analysts

Speed and Efficiency ⚡: AI accelerates data analysis, delivering insights in minutes instead of days.
Accuracy 🎯: Machine learning eliminates human bias, improving result reliability.
Scalability 📈: Handle large datasets with ease, uncovering insights that manual methods might miss.
Visualization 🖼️: AI tools create intuitive visualizations, making it easier to communicate findings.
Predictive Insights 🔮: AI doesn’t just identify root causes—it predicts future issues, enabling proactive solutions.

Conclusion: Why AI-Powered RCA is a Must-Have Skill for BAs

For Business Analysts, mastering AI-powered RCA is more than a trend—it’s a necessity. By combining traditional analytical skills with cutting-edge AI tools, BAs can deliver insights that drive meaningful business improvements. Whether you’re working in Finance, Supply Chain, or any other domain, the ability to leverage AI for RCA sets you apart as an indispensable asset.

Explore Our Courses at JVMH Infotech

Want to learn how to integrate AI into your Business Analyst toolkit? At JVMH Infotech, our programs provide hands-on training in tools and techniques to make you future-ready:

🎓 Business Analyst Job Mentorship Program
🎓 Scrum Product Owner Job Mentorship Program
🎓 Project Manager Job Mentorship Program
🎓 Banking and Financial Markets Domain Training
🎓 US Healthcare Domain Training
🎓 Supply Chain Management Domain Training
🎓 Scrum Developer Certification
🎓 Lean Six Sigma Black Belt Certification

✨ Exciting Update: JVMH Infotech is proud to be an Endorsed Education Provider (EEP) with the International Institute of Business Analysis (IIBA), ensuring our courses meet global standards and equip you for success in any domain.