Webinar Review – SmartShift to ServiceNow 

Last week, we hosted an insightful webinar discussing how businesses can improve their output of chatbots by tweaking their data input. Our colleague led the session, addressing common challenges in this specific use case and how to overcome them can be optimized. This review gives you a short overview of what was discussed. 

Gain a General Overview

Many businesses struggle with fragmented data stored across multiple platforms, which can slow decision-making and lead to inefficiencies. The webinar emphasized understanding the current state of your knowledge base and evaluating its use. 

This helps identify key areas for improvement, ensuring that your knowledge systems align with your business needs. 

Locate Data Issues 

Once you have an overview, the next step is to locate data issues. Common challenges include: 

• Information scattered over landscape 
• Increased effort in implementation & maintenance 
• Limited applicability due to inconsistent data structure 
• Risk of wrong / irrelevant answers due to missing context and governance 
• Limited machine readability 
• Wrong / incomplete answers due to long articles  
• Limit applicability due to high number of data formats (esp. images) 
• Inaccurate information 
• Unreliable outputs due to outdated / incomplete information 
• Slow, irrelevant answers and hallucination due to stale content

Tools like avato TRIDOC Monitor can identify where issues occur in your knowledge base.  

Identify Root Causes 

Identifying the root causes of data issues is crucial for long-term solutions. Several common factors contribute to chatbot challenges: 

• Lack of integration post-acquisitions: New knowledge systems are often not properly integrated into existing ones. 
• Silo mentality: Departments operating in isolation prevent efficient knowledge sharing. 
• KM is not prioritized in IT globalization: As organizations scale globally, KM systems are often neglected, leading to disconnected data. 
• Time pressure in creation and maintenance: Task overload results in shallow reviews and low-quality content for AI. 
• Knowledge landscape not made for AI: The systems were originally built for human users, not designed with AI integration. 
• No global knowledge governance: A lack of governance causes inconsistencies and outdated information. 

Recognizing these root causes is necessary to address knowledge gaps and implement effective solutions. 

Fix the Root Causes, Resolve the Issues 

After identifying the root causes, it’s time to fix the issues. Solutions include: 

• Migrate to a unified knowledge hub: Consolidating knowledge into a single platform like e.g. ServiceNow helps eliminate silos and ensures consistency. 
• Implement knowledge governance: Set up centralized governance to maintain content quality, implement guidelines, and provide support for content creators. 
• Restructure content for AI: Make content machine-readable and ensure that it’s accessible in various formats. 
• Monitor and improve continuously 

By addressing these issues, businesses can optimize their knowledge management system, improve AI capabilities, and create a more efficient chatbot that answers reliable. 

Imprint:

Date: April 2025
Contact: marketing@avato.net

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