Generative AI Manufacturing Industry

The ability to make informed decisions quickly is a cornerstone of any Organization’s success. However, there’s a challenge that Business Users are facing- Data Deprivation. This issue arises from an overreliance on software teams or IT teams and the lengthy development cycles required to obtain Data Insights.


Business Users or Decision Makers in the Manufacturing Industry often have to wait weeks or months, to get Dashboards and Reports that can help their Decision Making.


In this blog, I will take you on a journey to explore a Case Study that highlights the widespread issue in the Manufacturing Industry with a solution to overcome problems. I will delve deeper into the Problems Faced, present the AI-driven Innovative Solutions that have emerged, and reveal the significant Return On Investment (ROI) achieved.

Statement of Problems: Data Deprived Decisions

Just imagine, where Business Users have brilliant ideas and strategies, yet they find themselves helpless just because of constant reliance on Software Teams to access the Data Insights. 

This is a harsh reality that many Business Users have faced. Their heavy reliance on Software Teams, combined with Long Development Cycles, Creates a Significant Time Lag between the need for Data and its Actual Availability.

For manufacturing businesses, this delay can be a serious hurdle. This means that important decisions related to operations, sales, finance, and overall strategy are taken with incomplete information or, worse, are postponed. Such a situation can hinder growth, efficiency, and competitiveness, threatening the very existence of the enterprise.

Problems faced by Business Users

  • Data Silos hinder comprehensive Analysis: 

When Data is stored in isolated systems, it becomes difficult to gain a holistic view, impeding effective Analysis and Decision-Making.


  • Integrating Data from multiple sources is complex: 

Combining Data from different platforms and formats is complex, often requiring significant time and effort.


  • Poor Data Quality leads to inaccurate insights: 

Inaccurate or incomplete Data may result in incorrect conclusions, which may adversely affect decision outcomes.


  • Managing vast Data Volumes is overwhelming: 

The sheer Volume of Data generated in Manufacturing can overwhelm systems and slow down analysis processes.


  • Data security is a constant concern: 

Protecting sensitive Manufacturing Data from breaches and unauthorized access is an ongoing challenge.


  • Legacy systems hinder modern analytics: 

Outdated technology can limit the adoption of advanced analytics tools, hindering efficiency and innovation.


  • Skilled Data Analysts are in short supply: 

Finding professionals with expertise in Coding for Data Analytics can be challenging.


  • Data Analytics tools can be costly: 

Investing in the software can strain manufacturing budgets.


  • Achieving Real-Time Analytics is challenging: 

Processing Data in Real-Time to make immediate Decisions requires advanced technology and planning.


  • Incomplete Information for Operations: 

Manufacturing decisions made with incomplete Data can lead to inefficiencies in production processes.


  • Delayed Sales Strategies: 

Lack of timely Insights hampers sales strategies, potentially causing missed opportunities and reduced revenue.


  • Threat to Business Survival: 

Persistent delays in decision-making can pose a significant risk to the long-term existence of Manufacturing Enterprises.

PolusAi’s Innovative Solution: Generative AI-driven Conversatix BI Implementation

Manufacturing Industry

A ray of hope in the Manufacturing Industry emerged in the form of PolusAI and its revolutionary AI-driven Conversational BI implementation. This innovative solution has fundamentally changed the way Business Users and Decision Makers interact with Data.

With PolusAI’s Generative AI capabilities even individuals without any IT background can have a Conversation with SAP HANA Application Data and use AI-powered dashboards. Result? Instant data analysis and the ability to create dynamic dashboards without the need to write a single line of code.

Let’s now delve deeper into how PolusAI’s AI-driven solution have catalyzed positive change across various aspects of Manufacturing Industry Operations.

CEO’s Dashboards

Comparative Analysis of Revenue and Collection Trends: With the CEO Dashboard, Business Users can get valuable insight into revenue trends, enabling them to make informed decisions about collection strategies and financial planning.


Improved Operational Efficiencies: Daily and monthly yield analysis with utilization percentage metrics empowers Users to rapidly fine-tune operational processes, ensuring optimal resource allocation and increased productivity.


Production Cost Optimization: Monthly analysis of conversion costs provides a detailed understanding of expenses, facilitating cost-effective production strategies and improving the bottom line.


Inventory Management: The dashboard provides accurate Data on stock levels including Finished Goods (FG), Work-In-Progress (WIP), and Raw Materials (RM). This accuracy in inventory management can lead to significant cost savings.


Sales & Marketing Dashboards

Increased Sales Managers’ Performance: By providing access to Real-Time Sales Data, Sales and Marketing Dashboards enhance the performance of Sales Managers who can make timely adjustments to strategies based on actual performance.


Improved Orders and Collections: Target vs. Actual comparison helps Organizations streamline their order management processes, ensuring quick collections and efficient cash flow management.


Orders Profitability Decisions: Through detailed analysis of Customer Transactions (CTS) and Net Sales Revenue (NSR), companies can make Data-Driven Decisions about the profitability of individual orders.


Identification of Market Trends: The dashboard allows businesses to identify market trends through daily, weekly, and monthly sales analysis, enabling them to adapt their strategies to changing market dynamics.

CFO/Financial Dashboards

Fast and Accurate Expense Tracking: Monthly cash flow statements provide an immediate overview of expenses, helping financial teams make timely and informed decisions.


Cost Optimization: Detailed monthly analysis of conversion costs helps organizations identify areas where cost optimization is possible, thereby improving profitability.


Freight Cost Reduction: Freight analysis for each transporter and city enables organizations to optimize their transportation costs, thereby reducing overall costs.


Accounts Receivables Management: Instant tracking of accounts receivable, including outstanding, overdue, and legal case amounts, enables finance teams to proactively manage cash flow and collections.

Operations Dashboards

Runrate Analysis: Runrate analysis for each step of the manufacturing process provides valuable insight into production efficiency and performance.


Manufacturing Yield Analysis: Product-wise and step-wise yield analysis ensures that manufacturing processes are optimized for maximum output and quality.

Reduced Downtime: Accurate downtime details, categorized by stage and department, help organizations minimize production downtime and increase overall efficiency.

Production Planning: Stage-wise tracking of Work-in-Progress (WIP) and Finished Goods (FG) enables instant and accurate production planning, reducing lead times and improving customer satisfaction.

Return on Investment (ROI)

Manufacturing Industries

The most important aspect of this transformational journey – Return On Investment. PolusAI’s Generative AI-driven Conversational BI implementation has sparked a remarkable change in the way Data is used across all Manufacturing Departments. This change can be explained in three key points:


Data-driven decisions: The era of Data scarcity is a thing of the past. With PolusAI, Industry now makes Data-Driven Decisions across all aspects of Manufacturing, from Operations to Sales, Finance, and Beyond. This has resulted in a more informed and strategic approach to business management.


Transforming Data into Actionable Insight: Data is undeniably valuable, but its true potential lies in the Insights it provides. PolusAI has enabled businesses to transform Data into Insights, allowing them to not only increase revenues but also reduce operating costs. This has empowered organizations to make better choices that directly impact their bottom line.


10x Faster and Economical: Perhaps the most impressive aspect of PolusAI’s Generative AI-driven Conversatix BI solution is its Speed and Cost-Effectiveness. Turnaround time for Data Insights has been reduced by 10x, enabling businesses to respond faster to changing market dynamics and internal challenges. 

Remarkably, this transformation has been achieved without the need for complex and expensive Data Analytics Platforms.


With PolusAI’s Generative AI-driven Conversatix BI, the problems associated with the lack of Data and resulting dependence on software teams have been effectively addressed. The result in the Manufacturing Industry where Data-Driven Decisions are the norm, Data is transformed into Insights, and the time required for Data Insight is reduced.

Manufacturing companies that adopt such innovative solutions not only survive but thrive in today’s competitive arena. PolusAI has proven that with the right tools, Data can become a powerful driver of growth, efficiency, and profitability. As technology advances, it is imperative for businesses to adapt and take advantage of Data-Driven Decision-Making opportunities.

Apoorva Verma

Apoorva is a passionate and driven individual who accidentally found her interest in Business Intelligence and Data Analysis while studying Travel and Tourism. Despite her first love for being Content Writer and Blogger, she now creates compelling content on NLP-driven decision-making and a No-Code Data Platform that influences businesses. Her commitment to making Data accessible and Democratized for everyone has led her to work with NewFangled Vision on NLP-based Conversational Driven Data Analysis.

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