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Revolutionizing customer operations for Ascendum through Generative AI and Salesforce integration.

GenAI for Service Excellence

SALESFORCE

AI AND GEN AI SOLUTIONS

Overview

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As an Engagement Manager at McKinsey, I led the design and development of the first Generative AI solutions for Ascendum, a global leader in the Energy & Materials sector. The goal was to transform how field mechanics interact with technical data, reducing equipment downtime and streamlining customer operations by integrating cutting-edge AI directly into their Salesforce ecosystem.

Impact

The pilot solution was implemented in just four weeks, delivering immediate operational improvements:

  • + 10% Improvement in first-time resolution rates

  • Instant access to critical repair data, cutting diagnosis time from 30 minutes to seconds

  • Estimated savings of $5k+ per hour in recouped downtime for Ascendum’s customers

  • Established the blueprint for GenAI deployment across the broader organization

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Approach

Our strategy focused on moving beyond a "proof of concept" to a production-ready tool that mechanics actually trusted. We followed a three-pillared methodology

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We didn't just build for the sake of AI. We evaluated over 30 potential GenAI use cases against a matrix of "Value vs. Feasibility." Reducing "Time to Resolution" for field mechanics emerged as the highest ROI opportunity, directly addressing the multi-thousand-dollar-per-hour cost of machinery downtime

  • Technical development was executed in an intensive 5-week agile sprint

  • Knowledge Retrieval: We utilized RAG (Retrieval-Augmented Generation) to ground the AI in Ascendum’s proprietary technical manuals.

  • Field Validation: I led weekly feedback loops with actual mechanics. This ensured the AI didn't just provide "answers," but provided safe, actionable instructions that accounted for environmental factors on a construction site

  • Agile Product Ownership: Managing the backlog between QuantumBlack engineers and Ascendum stakeholders

  • Design Thinking for GenAI: Developing new frameworks and capabilities to translate field observations into the GenAI solution's experience.

  • Value Engineering: Calculating the precise financial impact of downtime reduction to justify the AI investment

  • Implementing guardrails to safeguarding GenAI models

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Public references

To learn more about the project, refer to these links:
 

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