Q1. Could you start by giving us a brief overview of your professional background, mainly focusing on your expertise in the industry? 

My work has largely been around driving business change and strategic initiatives in the heavy equipment and mining aftermarket. I’ve been closely involved in manufacturing operations, supply chain improvement, sourcing, and digital service delivery. I’ve led quality and performance improvement efforts, rolled out digital initiatives using data and connected systems, and helped grow parts and service businesses in a steady, sustainable way. I focus on turning strategy into practical action that improves reliability, delivers real value to customers, and strengthens competitive position.

Q2. Which segments within the digital aftermarket ecosystem for mining equipment present the highest growth potential?

Key growth areas:

Predictive maintenance and equipment analytics: Tools that track how machines are performing and flag issues early, helping avoid unexpected breakdowns and reduce maintenance costs.

Connected parts marketplaces and digital buying tools: Platforms that make parts easier to find and order, improve visibility into stock levels, and speed up service response.

Fleet telematics and remote monitoring: Systems that bring equipment data into one place, allowing operators to manage usage, performance, and uptime more effectively.

Service platforms with built-in intelligence: Tools that simplify diagnostics, reduce manual effort in repairs, and help technicians document and share practical know-how.

These areas are gaining momentum as operators focus more on keeping equipment running, using data to guide service decisions, and improving transparency across the aftermarket.

Q3. How do you foresee the role of CRM systems evolving with AI in parts sales and customer support for mining equipment over the next 3-5 years?

CRM systems are no longer just places to store customer data. They’re becoming day-to-day tools that help teams stay ahead of customer needs—flagging parts opportunities before demand peaks, directing service requests to the right people, and helping technicians resolve issues faster with better information.

Customer engagement is also getting more focused. By tailoring outreach to how equipment is actually used and maintained, companies can have more relevant conversations that build trust, improve retention, and increase parts and service uptake.

At the same time, CRM platforms are being connected to parts catalogs, inventory, and warranty systems. This gives service and sales teams a clear, real-time view of pricing, availability, and delivery, making it easier to respond quickly and accurately.

Over time, CRM will sit at the center of a more connected landscape, working closely with ERP systems, connected equipment, and digital commerce tools. The result is smoother service across channels and a much clearer understanding of the customer from first sale through ongoing support.

Q4. What emerging technologies or data analytics capabilities should one watch that could disrupt or further enhance aftermarket operations in mining equipment?

Digital twins and simulation platforms: Virtual representations of equipment used to support planning, forecasting, and more effective maintenance decisions.

Edge analytics and lightweight on-device models: Local processing that detects issues in real time, even in environments with limited or unreliable connectivity.

Augmented reality support tools: Applications that guide field technicians through installation, diagnostics, and assembly with clear, step-by-step instructions.

Together, these technologies help make aftermarket service more dependable, quicker to respond, and more precise in execution.

Q5. How has the integration of AI and IoT transformed predictive maintenance and inventory management in the mining equipment aftermarket so far? What key metrics demonstrate this impact?

AI and IoT have shifted maintenance from reacting to problems to predicting them:

In practice, organizations that have adopted predictive approaches often report meaningful reductions in unplanned downtime—sometimes by 30–50%—along with comparable improvements in maintenance costs and asset utilization.

The same insights also improve parts planning. When maintenance needs are clearer, teams can stock what’s actually required, reducing excess inventory while still meeting service needs.

Performance is typically tracked through

• Reduction in unplanned downtime
• Maintenance cost savings
• Improvements in overall equipment effectiveness (OEE)

Q6. For strategic commodities in aftermarket mining parts, which procurement options have proven most effective at optimizing pricing volatility?

Some useful strategies are:

Vendor-Managed Inventory (VMI): In vendor-managed inventory arrangements, suppliers hold and replenish critical stock, helping smooth pricing and avoid shortages.

Long-Term Framework Agreements: Add further stability by locking in prices and volume commitments, reducing exposure to swings in raw material and freight costs.

Digital Procurement Platforms: They enable buyers to gain real-time visibility into pricing and alternatives, enabling more flexible sourcing decisions and better cost control.

Consignment Models: Another useful lever, with suppliers retaining ownership of parts at the customer site until they are actually used, making it easier to respond to shifts in demand.

Using a mix of these strategies helps organizations control costs and stay ready to meet service needs.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

A practical question to ask:

How do you use real-time data and predictive analytics in your aftermarket operations to boost revenue and reduce service costs? What KPIs show it’s working?

This question focuses on digital progress, being competitive, and tracking real business results—key areas for success in aftermarket services.