What Is Knowledge Management in Utilities?
Knowledge management (KM) in utilities refers to the processes and tools used to capture, organize, share, and utilize information and expertise across the organization. This includes everything from maintenance records and engineering standards to customer service best practices and regulatory guidelines.
In the utilities sector—where workforce turnover, regulatory compliance, and infrastructure complexity pose constant challenges—effective KM ensures:
- Continuity of expertise amid retirements and labor shortage
- Improved decision-making with analytic insights and reasoning
- Content management efficiency by reducing duplicate work and avoiding errors
- Enhanced safety and compliance with robust content management and workflow capabilities
- Improved operational performance with fast and easy access to trusted answers
Utilities that lack a formal KM strategy risk knowledge chaos, process inefficiencies, and increased operational risk.
Knowledge Management Challenges in Utilities
Despite its importance, KM in utilities faces several hurdles:
- Knowledge capture and retention: As baby boomers exit the workforce, utilities are having a hard time capturing and retaining their knowledge. Moreover, they are faced with the daunting task of replacing them since this is not an industry sought after by next-gen workers. This calls for more automation, powered by AI and knowledge.
- Knowledge fragmentation: Information is often scattered across departments, systems, or even paper records, making it difficult to access or integrate.
- Organizational silos: Engineering, operations, IT, field service, and contact center customer service often work in silos, limiting cross-functional knowledge sharing.
- Outdated technology: Legacy systems are failing—48% of consumers said they could not find answers to their questions on utilities’ apps and websites, according to a J.D. Power survey.
How AI Can Help
- Knowledge automation: AI tools can extract insights from maintenance logs, emails, reports, and sensor data, turning unstructured content into searchable knowledge assets. Moreover, AI can help automate the knowledge management process end to end from sourcing to creation to publishing and optimization.
- Analytic insights: By analyzing historical data, AI helps utilities anticipate equipment failures, optimize field service and equipment maintenance, and improve planning.
- Knowledge transfer: AI can identify knowledge gaps and recommend learning resources to upskill new employees faster.
- Assist frontline employees: Most customer service reps and field technicians are not tenured and often need proactive, dynamic knowledge pushed to them during their conversations or when they are deployed to the field. AI can guide them to the right answers and through “next best steps” to resolution with reasoning.
By integrating AI into KM processes, utilities can ensure knowledge is not only preserved but proactively used to drive better outcomes.
Best Practices in Knowledge Management for Utilities
To implement an effective KM strategy, utilities should follow these best practices:
- Establish a KM framework: Define clear goals, roles, and processes for knowledge creation, curation, and sharing.
- Invest in a centralized knowledge hub: Source and centralize trusted knowledge through a central hub which should be a single source of truth.
- Encourage a knowledge-sharing culture: Incentivize collaboration and recognize contributions to shared knowledge resources.
- Leverage AI and automation: Use AI to index content, enable smart search, and surface insights in context.
- Integrate with daily workflows: Push contextual knowledge to employees in the flow of their day-to-day work processes.
- Measure impact: Track metrics specific to the business functions—First-Contact Resolution and Speed-to-Competency, for example, in the context of contact centers and the reduction of unwarranted truck rolls or field engineer visits, for example, in the context of field service.
Success stories in knowledge management for utilities
Fortune 500 utility client serves consumers across six states in the US. Having to handle a broad range of customer queries across website authentication, troubleshooting, billing, Covid-19 issues, and others, its contact center agents were struggling to find answers to customer questions in their CRM system and SharePoint. With NLP search, AI guidance, and personalization capabilities in the eGain AI Knowledge Hub™, integrated with their SAP CRM and SharePoint systems, agents are now able to find fast, accurate answers 90% of the time! Managers also report great author, admin, and operational experiences beyond the agent experience.
Major UK utility, serving over a million households, aimed to slash agent training costs and reduce unwarranted engineer callouts with more effective problem resolution from their contact centers. With search and AI guidance capabilities in the eGain Knowledge Hub, the utility was able to slash agent training time by 50% and engineer callouts by 25%, while improving First-Contact Resolution (FCR) by 60%, all within the first nine months of deployment!
Conclusion
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