At Engleman Associates, Inc. (EAI), we’ve guided over 1,000 ERP projects since 1996, always prioritizing the buyer’s perspective. In our latest ERP Now video, “Can AI Help You Choose the Right ERP?”, we explore how artificial intelligence can assist in selecting or optimizing an ERP system—and where it falls short.
AI can be a useful starting point when quality data is available. For instance, it can identify ERP systems commonly used by specific industries or highlight problematic vendor contract terms when prompted correctly (see full list below of ways AI greatly helps). However, the ERP landscape is complex, with challenges like vendor misinformation, biased analyst reports, and unclear buyer requirements. These abstract variances limit AI’s ability to provide tailored, reliable recommendations.
Successful ERP selection still demands skilled buyer-seller interaction to define functional scope, rigorously test critical features, negotiate favorable terms, and choose implementers with proven expertise. At EAI, we specialize in navigating these complexities to deliver solutions that align with your business needs.
Watch the full video below to learn more about leveraging AI effectively in your ERP journey and discover practical insights from our decades of experience.
For additional resources, explore our ERP Now video series linked in the video description. Stay informed and contact EAI for expert guidance on your next ERP project.
How AI Helps
AI significantly enhances EAI ERP advisory services by providing deep insights and accelerating key activities in ERP selection and implementation control. Effective use of AI requires precise, informed queries, with results typically validated and augmented by tactical follow-up queries, and by other information sources. Below are the key areas where AI is applied in EAI ERP advisory services:
- Generating Long List ERP Candidates: AI rapidly identifies potential ERP systems (or other business applications) based on client size, industry requirements, and system capabilities, creating an initial pool of candidate ERP. The results are cross referenced to the EAI ERP database and a final long list is generated.
- Developing Functional Requirements for ERP Selection and Planning: AI assists in defining detailed, relevant functional requirements to screen ERP candidates and support pre-implementation planning, which can greatly improve alignment with business objectives.
- Identifying and Screening ERP Resellers, Implementers, and Consultants: AI locates and evaluates ERP resellers, implementers, and independent consultants with specific ERP expertise, streamlining the selection of qualified partners.
- Enhancing ERP Access Cost Control: AI helps articulate clear cost control objectives to vendors, facilitating negotiations and reducing barriers to achieving cost-effective ERP access and implementation. This again is highly dependent on proper AI inquiries.
- Highlighting and Addressing Commercial Terms Conflicts: AI identifies default commercial terms in ERP contracts that conflict with objectives for buyer cost and commercial control, proposing precise language to address these issues. These objectives are designed by EAI, place appropriate and firm control in the hands of buyers, and this approach makes vendors directly confront various conflicts.
- Accelerating Implementer Onboarding with Company Insights: AI leverages selected data from company discovery to quickly familiarize implementer personnel with the client’s operations, reducing the need for extensive new business process interviews.
- Streamlining Business Process Discovery and Metrics Design: AI organizes and makes visible critical insights from the business process discovery phase, supporting effective business process and metrics design during ERP implementation.