When Knowledge Lives Only in Their Heads: Training and AI Readiness in Local Government

When Knowledge Lives Only in Their Heads: Training and AI Readiness in Local Government

What happens when a city of 50,000 people runs a 311 call center with nine agents covering 77 services — and most of that knowledge lives only in people's heads? Parker Skophammer, Director of Finance and Administrative Services for the City of Mankato, Minnesota, joins Katie to talk about what it actually takes to build a training foundation in local government — and why it matters more than most leaders realize. Parker and the City of Mankato partnered with B-Lynk to document processes, build out eLearning courses, and create video-based training for their 311 agents. What started as an onboarding challenge became a longer-term strategy to protect institutional knowledge, reduce ramp time, and lay the groundwork for smarter operations going forward. --- WHAT YOU'LL LEARN - What a 311 call center is and why the City of Mankato built one - How undocumented knowledge becomes a real organizational risk — and what to do about it - Why onboarding time dropped from 10 weeks to 6 weeks with structured training - What role eLearning and video content played in getting 311 agents up to speed - How municipalities are thinking about AI — and why governance has to come first - Three AI use cases Parker is watching closely in local government - What every city leader should do right now to protect the long-term health of their organization --- KEY TAKEAWAYS - Institutional knowledge is an organizational liability. When processes live only in people's heads, attrition becomes a crisis. Documenting and structuring that knowledge is the first step toward sustainability. - Onboarding time is a measurable win. The City of Mankato cut new agent ramp time from 10 weeks to 6 — a direct result of structured eLearning and video training built with B-Lynk. - Training isn't a one-and-done event. Ongoing curriculum and knowledge testing for existing staff is just as important as onboarding. You can't assume knowledge sticks if you're not measuring it. - For municipalities, AI governance has to lead. Data security, council buy-in, and community readiness all matter before ROI even enters the conversation. - Documentation is your AI foundation. You can't build a smart knowledge base or future AI workflow on top of undocumented processes. Getting information out of people's heads and into structured content is step one.

Is Your AI Ready? How SmartScore and Tresic Are Closing the Gap with Kevin Nethercot

In this episode of Train to Gain, Katie Merrill sits down with Kevin Nethercott, CEO of Tresic, to explore what happens when AI meets the full volume of an organization’s conversation data — and what becomes possible when that intelligence is actually put to work. Kevin shares how Tresic’s Intelligence Cloud captures and analyzes 100% of customer conversations, surfacing upsell opportunities, compliance signals, and churn risks that most organizations never see. The conversation also digs into the natural connection between Tresic’s data and B-Lynk’s SmartScore AI readiness product — and how the two work together to help organizations confidently move toward AI-enabled customer experiences. What you’ll hear in this episode * Kevin’s origin story and how Tresic came out of stealth in January * What “intelligence actioned” means — and why it’s different from traditional analytics * Why most companies only review 1–2% of their calls and what it’s costing them * How Tresic’s 16 vertical packs deliver industry-specific intelligence * The connection between real conversation data and AI readiness * How B-Lynk’s SmartScore uses Tresic data to assess documentation confidence * What the first 60 days with Tresic looks like — and why you can’t unsee the data Key takeaways * Reviewing only a fraction of calls leaves upsell opportunities, compliance issues, and churn signals completely invisible * Acting on conversation intelligence — not just reporting on it — is what drives real business change * AI readiness requires clean, accurate documentation, and real call data is the best source for identifying gaps * The combination of conversation intelligence and targeted training creates a continuous improvement cycle * AI levels the playing field — what differentiates organizations is how they engage the human side of it

B-Lynk + Sunset Learning Institute: Powering Contact Center Adoption

EPISODE OVERVIEW In this episode of Train to Gain, Erin and Katie are joined by Nate Mengel and Pete Brown from Sunset Learning Institute to discuss the evolution of contact centers—from on-premise systems to the cloud—and why training has become the most critical driver of adoption, customer success, and long-term business outcomes. Drawing from decades of experience across contact center technology, software development, and training, the conversation explores how education empowers users, reduces risk, and ensures organizations realize the full value of their technology investments. KEY TOPICS COVERED THE EVOLUTION OF CONTACT CENTERS 1. Contact centers have evolved dramatically since the first implementation in 1965. 2. 3. Early systems were complex, on-premise deployments focused primarily on technology. 4. 5. The shift to cloud solutions changed the model—making it easier for customers to adopt, but also easier for them to leave if value isn’t realized quickly. 6. WHY TRAINING MATTERS MORE IN THE CLOUD ERA 1. Cloud solutions shift risk from the vendor to a shared responsibility between vendor and customer. 2. Customer retention now depends on adoption and ongoing value—not just implementation. 3. Training has evolved from a technical step into a critical business function that directly impacts customer success and renewals. REAL-WORLD PERSPECTIVE FROM THE FRONT LINES 1. Nate Mengel shared his experience as a contact center agent during the early days of dial-up internet. 2. Contact center environments are high-pressure, and technology changes can add significant stress if users aren’t properly supported. 3. Training that focuses on empowering users—not just introducing new tools—makes transitions smoother and more successful. THE BUSINESS IMPACT OF TRAINING AND EDUCATION 1. Successful deployments depend on educating all stakeholders, including: 2. Agents 3. Supervisors 4. IT teams 5. Business leaders 6. Training ensures users understand reporting, workflows, and capabilities critical to business operations. 7. Poor training can lead to frustration, poor performance, and ultimately customer churn. TRAINING AS A DRIVER OF ADOPTION AND OUTCOMES 1. Training should not be treated as a checkbox or one-time event. 2. Instead, it should function as an ongoing education engine that: 3. Drives adoption 4. Improves customer satisfaction 5. Supports long-term business outcomes 6. Organizations that invest in education see better results, stronger adoption, and higher customer retention. THE POWER OF PARTNERSHIP The partnership between B-Lynk and Sunset Learning Institute combines: 1. Administrator training 2. End-user training 3. Strategic education programs 4. This comprehensive approach supports the full spectrum of users—from IT teams to front-line agents. 5. The goal is to help vendors, partners, and customers achieve better adoption and stronger business outcomes.

Training as a Growth Strategy with Travis Burris

In this episode of Train to Gain, the team welcomes Travis Burris, VP of Global Channels and Alliances at NuWave, to explore the realities that emerge after a solution is sold and implemented. Together, they discuss how adoption, training, and enablement directly influence customer satisfaction, channel success, and long-term revenue. From shifting industry dynamics to the growing importance of end-user experience, the conversation highlights why delivering technology is only part of the equation — ensuring customers know how to use it is what drives real value. What you’ll hear in this episode 1. An overview of NuWave’s channel strategy and industry focus 2. 3. The challenges organizations face with post-deployment adoption 4. 5. Why end users play a critical role in product success 6. 7. The connection between training, profitability, and renewals 8. 9. Supporting partners and carriers with scalable enablement resources 10. 11. How forward-thinking partnerships strengthen competitive positioning 12. Key takeaways 1. Adoption gaps remain a major industry challenge as organizations transition to modern communication platforms 2. 3. End-user experience impacts satisfaction, retention, and revenue 4. 5. Training and enablement aren’t add-ons — they are strategic differentiators 6. 7. Providing a complete lifecycle experience builds trust and drives renewals 8. 9. Channel partners benefit from resources that extend beyond technical delivery

Right Answers, Right Now: AI in Self-Service Support

Customer expectations have changed—and waiting for answers is no longer acceptable. In this episode of Trained to Gain, Erin Raitt and Katie Merrill explore how self-service support is being re-architected for the AI era, and why delivering real-time, accurate answers starts long before AI is ever turned on. They discuss the evolution from static PDFs and traditional knowledge bases to conversational, AI-powered experiences—and why strong, well-structured documentation is still the foundation that makes it all work. If your AI can’t solve the problem in the moment, this episode explains why—and what to do about it. In this episode, you’ll learn: 1. Why customers want right answers right now, not more content 2. How self-service support expectations have shifted in an AI-driven world 3. Why AI is only as effective as the knowledge behind it 4. The role documentation plays in delivering fast, contextual answers 5. What it takes to prepare your support experience for AI 6. Why maintaining and evolving your knowledge is an ongoing process This conversation is a must-listen for anyone focused on customer experience, adoption, and building support systems that actually solve problems—at speed. 🎧 Tune in to learn how AI-ready knowledge leads to AI-delivered outcomes.