For this episode, Cindy and Joy connect with Rajesh Hariharan, Chief Delivery Officer, and Daniel Vachoo, Director of Commercial Operations, of Dechen Consulting Group, an IT consulting firm headquartered in Farmington Hills, Michigan.

The conversation moves beyond AI headlines to examine the practical work behind adoption: connecting systems, preparing data, improving processes, earning employee trust, and keeping human judgment central to business decisions.

Segment 1: Opening Discussion – AI Opportunities and Manufacturing Concerns

Cindy and Joy introduce the opportunities and questions surrounding artificial intelligence in manufacturing.

1. How can manufacturers identify an AI partner who understands both the technology and the realities of manufacturing?

2. What concerns arise around older systems, data quality, employee adoption, cybersecurity, and implementation costs?

3. How can companies preserve the valuable knowledge experienced employees carry as they approach retirement?

4. What should manufacturers consider when deciding whether an AI solution is the right fit for their organization?

Segment 2: Meet Dechen Consulting Group – Moving Beyond the AI Hype

Rajesh and Daniel introduce their backgrounds, Dechen Consulting Group’s work, and the distinction between experimenting with AI and achieving meaningful business results.

1. What does Dechen Consulting Group do, and how does its work support automotive and manufacturing organizations?

2. How have Rajesh’s enterprise-technology experience and Daniel’s consulting and healthcare-AI background shaped their approach?

3. Where does the excitement surrounding AI differ from what manufacturers are implementing and scaling?

4. Why must AI adoption address processes, workforce trust, and fragmented data—not just technology?

Segment 3: ERP and the Shop Floor – From Systems of Record to Systems of Action

Cindy asks how manufacturers can build on existing ERP systems while bringing more timely information and intelligence into daily operations.

1. How can AI complement an ERP system rather than simply replace it?

2. What can manufacturers learn by examining the manual processes employees use alongside their enterprise systems?

3. How can production planning account for changing priorities, tooling constraints, labor availability, and shop-floor conditions?

4. What does the progression from visibility to prediction, recommendation, and action look like?

5. Where do governance and human oversight belong when AI begins triggering workflows or supporting transactions?

Segment 4: Getting Started – Data, Integration, and Realistic Timelines

The discussion turns to implementation, including why modernization requires more than selecting software or purchasing licenses.

1. What determines the timeline for an AI initiative?

2. Why is starting with a focused pilot, validating results, and expanding from there a useful approach?

3. How do disconnected ERP systems, spreadsheets, and other data sources complicate implementation?

4. Why are data cleansing, integration, and change management often underestimated?

5. How does a co-development approach combine the manufacturer’s business knowledge with a technology partner’s expertise?

6. Why does moving an inefficient process onto a new platform fall short of meaningful modernization?

Segment 5: Preserving Knowledge and Bringing Employees Along

Joy and Cindy explore how manufacturers can capture operational experience while addressing employee concerns about AI and job security.

1. How can businesses capture the context and judgment behind decisions—not just the information stored in their systems?

2. What happens when an AI recommendation fails to account for an experienced employee’s feedback?

3. How can individual shop-floor knowledge become organizational knowledge that supports future decisions?

4. How should employers respond to fears that AI will diminish employees’ value or eliminate their roles?

5. What helps employees understand how AI can support their work and become part of a trusted workflow?

Segment 6: Closing Discussion

Cindy and Joy recap the conversation and its central themes: practical AI adoption, reliable data, employee involvement, and preserving the experience that keeps manufacturing operations moving.

AI in Manufacturing: Technology, Processes, and People

What does it take to turn artificial intelligence from a promising idea into a useful part of a manufacturing business? Rajesh Hariharan and Daniel Vachoo of Dechen Consulting Group join Faces of Manufacturing to examine the systems, processes, and people behind that transition.

The conversation explores how AI can complement existing ERP systems, bring together fragmented information, and help manufacturers move from understanding what happened to anticipating what could happen next. Production planning provides an example of how better-connected information can support decisions about capacity, scheduling, material availability, and customer deliveries.

The guests also discuss the work that can be overlooked when companies focus primarily on technology: cleaning and integrating data, redesigning processes, establishing governance, and involving employees throughout implementation. Rather than treating AI as an overnight solution, they emphasize focused initiatives, continuous feedback, and results that can be validated before expanding.

At the center of the discussion is the knowledge held by experienced employees. Capturing that expertise requires more than transferring information into a database. It means understanding business rules, operational context, and the human judgment behind everyday decisions.

For Michigan manufacturers considering their next steps, the episode returns to a central message: meaningful modernization depends on people adopting and helping shape the technology—not simply having access to it.

Faces of Manufacturing highlights the people, leadership, and workplace cultures shaping Michigan’s manufacturing sector.

Learn more about Dechen Consulting Group: https://dechen.com/