We Know Business Knowledge Data: Over 90% of Revenue-Generating Data Is Wasted After ERP Go-Live
Implementing an ERP system like SAP S/4, NetSuite, Salesforce, or Workday is a monumental task for any organization, involving countless hours of intense workshops, deep collaboration with external consultants, and the focused input of internal Subject Matter Experts (SMEs). Yet, after the ERP go-live, a critical problem emerges: over 90% of the valuable, revenue-generating knowledge captured during the process is lost.
This lost knowledge is not just about technical configurations. It includes key business insights, workflow optimizations, and strategic decisions that were discussed and refined through collaboration between internal teams and external experts. Once the implementation is complete, external consultants move on to their next projects, and internal SMEs return to their regular duties. This leaves an enormous gap in the company’s ability to leverage the full potential of its ERP system for sustained growth and efficiency.
The Hidden Cost of Wasted Knowledge
What happens to the knowledge gathered from workshops, consultant discussions, and SMEs after go-live? Too often, this information is either poorly documented or forgotten. In fact, organizations typically lose access to over 90% of the knowledge accumulated during implementation a huge loss, given the investment in both time and financial resources.
The problem lies in the fact that most ERP implementations focus heavily on getting the system live but fail to create mechanisms for retaining and utilizing the broader, more nuanced business knowledge that was shared. This loss of knowledge limits an organization’s ability to fully optimize its ERP system for revenue growth, cost-saving initiatives, and operational improvements.
Capturing Knowledge Before It’s Too Late
To prevent this waste, it's crucial to capture knowledge during the ERP implementation process itself. By systematically converting the discussions, insights, and decisions made by consultants and SMEs into permanent, AI-ready knowledge datasets, you can create a lasting asset that continues to deliver value long after the system is live.
These AI-ready datasets allow your organization to:
- Retain Expertise: The knowledge imparted by external consultants and internal SMEs doesn’t walk out the door with them. It becomes a permanent asset that can be revisited and leveraged in future system upgrades, optimizations, and strategic decisions.
- Drive Continuous Improvement: Capturing this knowledge provides an ongoing resource for refining business processes, improving workflows, and identifying new opportunities for automation or revenue generation within your ERP system.
- Enhance Strategic Decision-Making: With the right AI-driven tools, you can use the captured knowledge to run predictive models, identify trends, and make better-informed decisions based on the data and insights gathered during the implementation phase.
Building AI-Ready Knowledge Datasets
To effectively capture this knowledge, you need more than just documentation; you need structured, AI-ready datasets that are designed to grow and evolve with your organization’s needs. During the ERP implementation process, key steps include:
- Engage Consultants and SMEs as Data Sources: From day one, external consultants and internal SMEs should be recognized as key knowledge contributors. Workshops and meetings should be structured to capture insights, not just deliverables.
- Why Traditional Tools Fail to Capture Knowledge: Existing tools like Help Desk, Learning Management Systems (LMS), and Knowledge Management Systems (KMS) aren’t designed to capture and structure the deep business knowledge shared during the ERP implementation process. These systems primarily serve transactional or operational functions and fail to fully encapsulate the strategic insights shared during high-level ERP decision-making. As a result, the critical knowledge remains hidden or is entirely lost, leading to inefficiencies when it could otherwise provide a long-term competitive advantage.
- Reimagine Your Tech Stack for Knowledge Extraction: To address this gap, organizations must reimagine their tech stack and implement AI-powered tools capable of extracting, structuring, and categorizing the insights generated during ERP workshops, project plans, and strategic discussions. These AI-driven solutions capture knowledge from every touchpoint—employees, external consultants, and even from typically overlooked "dark" data sources, such as informal conversations or ad hoc documents. With AI tools designed for knowledge extraction, we ensure that no critical data is wasted, and that every piece of information can be leveraged post-go-live to drive continuous improvements.
- Reimagine Your Tech Stack with a Unified Knowledge Data Source: Instead of relying on fragmented systems and isolated data storage, organizations should build a centralized, AI-ready knowledge repository. This repository should include best practices, lessons learned, process changes, and strategic recommendations, all organized in one location. A unified data source enables easier access and ensures that every piece of knowledge can be utilized for ongoing refinement. This new approach to your tech stack doesn’t just preserve knowledge but also makes it actionable for future ERP optimizations, ensuring your organization continues to benefit from the investments made during the ERP implementation.
- Transform Wasted Data Into Permanent, AI-Ready Assets: To avoid the common pitfall of lost knowledge after ERP go-live, it’s crucial to create AI-ready datasets during the implementation process. By capturing and converting insights into structured data, businesses can ensure long-term use and prevent the wastage of revenue-generating information. These AI-ready datasets become the foundation for future strategic decisions, process improvements, and even potential AI-driven automation opportunities. In doing so, organizations can turn ERP implementations into ongoing profit centers, driving efficiency, innovation, and continuous business growth. The data you once considered transient becomes a permanent asset that fuels your company’s future success.
- Use AI Tools for Knowledge Extraction: Leveraging AI-powered tools to capture, structure, and categorize the insights from workshops, project plans, and conversations ensures that critical knowledge is preserved and easily accessible post-go-live.
- Create a Centralized Knowledge Repository: Build a central repository of AI-ready data that includes best practices, lessons learned, process changes, and strategic recommendations. This repository will serve as the foundation for continuous learning and improvement.
The Long-Term Value of Knowledge Datasets
By converting this untapped knowledge into AI-ready datasets, your organization gains a permanent resource that enhances the value of the ERP system. This resource not only helps prevent the common post-go-live knowledge drain but also provides the foundation for:
- Faster Problem Resolution: With access to a detailed knowledge base, teams can troubleshoot and resolve issues faster, minimizing downtime and improving system efficiency.
- Employee Empowerment: Internal teams can quickly learn from the captured insights, reducing dependency on external consultants for future improvements and upgrades.
- Scalable Growth: As your business grows, the AI-ready knowledge datasets evolve with it, offering the flexibility to scale operations, refine processes, and explore new opportunities for innovation.
Unlock the Full Potential of ERP Knowledge
The true value of an ERP system isn’t just in the software itself—it’s in the knowledge gathered along the way. Capturing and converting this knowledge into a permanent, AI-ready dataset transforms an ERP implementation from a one-time event into a long-term strategic asset. Don’t let over 90% of your revenue-generating data slip away after go-live. Embrace a smarter approach to capturing, structuring, and leveraging this knowledge to ensure sustained business growth and success.
