What is Knowledge Management in Manufacturing?

Knowledge Management in Manufacturing defined

Knowledge management in manufacturing is defined as the process of discovering, sourcing, creating, curating, publishing, and optimizing knowledge in the manufacturing sector. Effective knowledge management (KM) is crucial for global competitiveness, quality, and productivity. However, many manufacturers face significant challenges in capturing, sharing, and utilizing knowledge effectively and efficiently.

Types of knowledge in manufacturing

Knowledge is a broad concept that covers many types of information and knowhow. Here are some examples for the manufacturing sector:

Data

What is the volume pricing for Product X?
When can I expect my shipment?

Insights

What demographics are the top buyers of Product X?
What market segments return our products the most?
What is the MTBF (Mean Time Between Failure) of Product Y that uses components bought from Supplier A versus Supplier B?
What places should I drill for oil?

Policies

Returns
Warranties
Discount policy
Refund policy

Procedures

Returns processing
Product registration
Machine set up

Expertise

Diagnostics and troubleshooting
What parts and tools should I take to fix problem X at customer site Y?
Product advice

Knowledge management in manufacturing: Challenges

Manufacturers encounter several obstacles in managing knowledge:

The Silver Tsunami: As baby boomers retire in droves, information and expertise built over decades of experience walks out the door. Moreover, industries such as manufacturing, field service, and construction are not popular among the next generation of workers, underscoring the dire need to capture knowledge from departing employees and publish it across the enterprise.
Organizational and Content Silos: Deloitte’s research indicates that 55% of organizations identify organizational silos—people, process, and content—as a significant barrier to effective knowledge management.
Technology lag: The manufacturing sector lags behind others in adopting knowledge management technologies, according to a BenchmarkPortal cross-industry survey of over 400 contact centers. Moreover, a substantial part of knowledge in this sector tends to be complex and tacit, requiring modern KM systems to capture and disseminate it.

How AI Can Help

Historically, knowledge management has been a resource-intensive undertaking, but the AI revolution changes everything! A centralized knowledge hub, paired with AI, can:

Automate knowledge: AI can help automate the KM process end to end—discover most frequently asked questions, source trusted content, create, curate, publish, and optimize knowledge, accelerating time to value.
Leverage data: ML can identify patterns and insights from large sets of data.
Improve decision-making: AI can deliver insights and guide managers to better situational decisions.
Assist frontline employees at the “moment of truth”: 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.

Knowledge management in manufacturing:
Best practices for success

Invest in Modern KM Tools

Adopt AI-powered platforms that automate knowledge management with the backing of trusted knowledge unified in a central hub.

Ensure adoption

Train employees—contact center agents, field service agents, and others—to use the KM tool rather than hunt for answers.

Partner with proven vendors

KM is more than just technology. Getting quick business value requires domain expertise which many vendors lack.

Measure and manage

Make sure to measure usage and operational metrics impacted by AI knowledge. AI can also help extract insights from raw user feedback for continuous knowledge improvement.

Foster Knowledge-sharing culture

Encourage knowledge sharing among employees through incentives, gamification, and evangelism.

Knowledge management in manufacturing: Success stories

eGain’s manufacturing clientele includes the who is who of manufacturing companies. Here are examples of their at-scale success, powered by the eGain AI Knowledge Hub™.

Goodyear, the leading tire manufacturer, provides modern digital customer service to millions of consumers, retail stores, and OEM clients with consistent and unified knowledge and AI-backed self-service and agent-assisted service across chatbots, secure messaging, live chat, and email.
A-dec, the leader in dental office equipment manufacturing, elevated customer service for its channel partners, doubling dealer self-service adoption, improving contact center agent experience, and boosting sales, all powered by the eGain Knowledge Hub
Virgin Mobile, a leading handset manufacturer and mobile carrier, achieved a 23% improvement in customer service quality and a 19% increase in First-Contact Resolution, while reducing unwarranted handset exchanges by 38% through better problem resolution in their contact center with AI and knowledge guidance for agents.

Knowledge management in manufacturing: Conclusion

Modern AI knowledge management platforms—like eGain’s—make KM easy for manufacturing companies by combining the power of AI and knowledge management.

To help manufacturing organizations experience the benefits of KM, eGain offers the Innovation in 30 Days program: a unique, no-cost, no-risk production pilot with expert-led setup and support. We also offer our agentic AI technology free of charge for qualified non-profit and government organizations for 6 months. These are proven paths that many public sector clients have used to transform their service operations risk-free.