While nearly half of all companies use some sort of ERP, many are falling short in their quest for full data transparency. The ubiquity of ERP softwares is increasing, and is projected to grow by a CAGR of 8.85% by 2028. So how should companies and users make the most of their ever-growing ERPs to stay on top of the market? 

The Shortcomings of ERP’s

Below are a couple reasons your ERP may be falling short: 

• Static Reporting: Many ERP systems offer predefined reports and dashboards that may not adapt well to changing business needs. They can be inflexible and often require manual adjustments to extract meaningful insights. 

• Data Integration Challenges: ERPs can struggle with integrating data from disparate sources. This can lead to fragmented data sets that are difficult to analyze comprehensively. 

• Limited Advanced Analytics: Traditional ERP systems may lack sophisticated analytics capabilities like predictive modeling, machine learning, or advanced statistical analysis. They are often designed for transaction processing rather than in-depth data exploration. 

• Performance and Scalability Issues: As the volume of data grows, ERP systems might experience performance issues. Large datasets can slow down query times and hinder real-time analysis. 

• User Expertise: Effective use of ERP analytics often requires specialized knowledge. Users without a background in data analysis might find it challenging to derive actionable insights. 

AI Fills In The Gaps

Companies are now turning to AI to address these shortfalls, with AI addressing all of the shortcomings of traditional ERP systems through embedding, augmented analytics, voice to text, and more.  

Here are a couple ways AI is supercharging ERP systems:  

• Enhanced Data Processing: AI and machine learning algorithms can process vast amounts of data quickly and efficiently. They can handle complex queries and provide insights in real time, surpassing the capabilities of traditional ERP systems. 

• Advanced Analytics and Predictive Modeling: AI can perform advanced analytics, including predictive modeling and trend analysis. This helps businesses anticipate future outcomes, identify potential issues before they arise, and make data-driven decisions. 

• Automated Data Integration: AI-driven tools can automate the integration of data from various sources, creating a unified view that’s easier to analyze. This improves data quality and reduces the time spent on manual data preparation. 

• Natural Language Processing (NLP): AI can use NLP to allow users to interact with data in a more intuitive way. For example, users can ask questions in natural language and receive insights or reports generated by AI, making data analysis more accessible. 

• Anomaly Detection: AI can identify patterns and detect anomalies in data that might not be immediately apparent through traditional ERP analytics. This helps in spotting errors, fraud, or unusual trends early. 

• Customization and Personalization: AI can provide personalized analytics based on user roles and needs, offering tailored insights and recommendations. This ensures that each user gets relevant information without the need for deep technical expertise. 

• Scalability: AI tools are designed to scale with growing data volumes. They can adapt to increasing complexity without significant performance degradation, ensuring that analytics remains effective as your business grows. 

It’s All In The Numbers

Implementing AI into an ERP is a must for modern businesses, and leads to outstanding ROI when used properly; benefits can include a 90% reduction in reporting time, 10% reduction in costs, and a 55% reduction in decision cycle time. Overall, AI greatly decreases reporting time and cuts costs. 

ConverSight can embed Athena in your ERP software, providing the visibility needed for full data transparency. Request a demo today and see how you can take advantage of generative AI for end-to-end visibility into your supply chain.