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The AI in Business Podcast

Leveraging the Democratization of Data to Solve Workforce Challenges in Field Services - with Scot Burdette of ABB

Thu Jun 13 2024
AI in BusinessField Service TeamsHeavy Machinery SpaceData DemocratizationSubject Matter ExpertiseTools for Data AnalysisMetrics for Heavy IndustryQuality, Cost, and Speed

Description

This episode explores the unique challenges faced by field service teams in heavy machinery space and how AI can address workforce challenges and retain subject matter expertise. It discusses material shortages, remote locations, data democratization, retaining subject matter expertise, tools for data analysis, metrics for heavy industry and field services, and the balance between quality, cost, and speed. The episode concludes by highlighting the importance of data insights, subject matter expertise, and customer satisfaction in leveraging AI in these industries.

Insights

Data democratization is a double-edged sword

While there is a growing demand for better access to data and tools for analysis, it is important to balance access with proper interpretation and decision-making. Data governance and privacy are crucial considerations.

Retaining subject matter expertise is a challenge

The fear of losing jobs to AI can hinder the sharing of knowledge and expertise. Gatekeeping is important to protect data, but it should not create unnecessary bottlenecks or hinder access.

Quality should be the top priority

In heavy industry and field services, delivering high-quality products or services is essential for customer satisfaction. While speed and cost are important, they should not compromise quality.

Chapters

  1. Introduction
  2. Challenges in Heavy Machinery Space
  3. Democratization of Data
  4. Retaining Subject Matter Expertise
  5. Tools for Data Analysis
  6. Metrics for Heavy Industry and Field Services
  7. Balancing Quality, Cost, and Speed
  8. Conclusion
Summary
Transcript

Introduction

00:07 - 01:11

  • Welcome everyone to the AI in Business podcast. I'm Matthew DeMello, senior editor here at Emerge Technology Research. Today's guest is Scott Perdet, Global Division CIO for measurement and analytics at ABB. ABB is an electrical equipment manufacturer based in Sweden that specializes in industrial automation, robotics, as well as power generation, transmission, and distribution.
  • Scott joins us on the program to talk about the unique challenges to field service teams that are making AI increasingly relevant in B2B workflows with many parallels to the developments we've seen in their B2C counterpart.
  • Throughout the episode Scott lays out a vision for the future of AI and field services, particularly for addressing workforce challenges and retaining subject matter expertise in the organization through retirement waves and talent shortages.

Challenges in Heavy Machinery Space

01:39 - 04:07

  • For companies operating in the heavy machinery space, there are several big trends and challenges that define the C-suite. These include recovering from material shortages, dealing with remote locations, and managing multiple visits and interactions with customers.
  • The remote locations of large enterprise operations pose a challenge for delivering, commissioning, and servicing specialized equipment. Understanding the equipment and having the right tools and spare parts for maintenance in remote locations is crucial.
  • Material issues have also caused problems for production and delivery of essential equipment and spare parts. This is a top concern for C-suite executives.

Democratization of Data

05:05 - 06:35

  • The availability of data insights has become increasingly important for businesses. There is a growing demand for better access and tools to analyze data and improve business performance.
  • However, there is a balance between providing access to data and ensuring proper interpretation and decision-making. The challenge is to provide access without creating bottlenecks or compromising data governance.
  • Data privacy is also a concern as data flows everywhere. While heavy industry may not face the same privacy issues as banking or healthcare, it is still important to protect data and ensure proper governance.

Retaining Subject Matter Expertise

06:36 - 07:48

  • One of the challenges in leveraging AI in heavy manufacturing is the fear of subject matter experts losing their jobs. There is a need to balance access to data with the need for expertise and interpretation.
  • Gatekeeping is important to protect data and ensure proper use, but it should not hinder access or create unnecessary bottlenecks. The goal is to make informed decisions based on data while maintaining quality and expertise.

Tools for Data Analysis

08:11 - 09:14

  • Tools play a crucial role in manipulating and analyzing data. It is important to provide tools that help users make quick and informed decisions based on data insights.
  • Cloud storage, self-service BI applications, and reporting tools are some of the tools available for analyzing data. However, proper governance is necessary to avoid issues and conflicting outcomes.

Metrics for Heavy Industry and Field Services

09:35 - 11:12

  • The metrics for heavy industry and field services are similar to those in manufacturing, such as predictive maintenance, on-time delivery, and inventory management.
  • In addition to these foundational metrics, speed and quality are also important. Speed of manufacturing and delivery, along with insights and visibility for customers, contribute to overall success.

Balancing Quality, Cost, and Speed

11:38 - 12:50

  • When it comes to prioritizing quality, cost, and speed, quality is the top priority. Delivering high-quality products or services is essential for customer satisfaction.
  • While speed and cost are important, they should not compromise quality. It is a delicate balance, but without quality, the other factors lose their significance.

Conclusion

14:28 - 15:04

  • The episode highlights the challenges and trends in heavy industry and field services. It emphasizes the importance of data insights, tools for analysis, and the need to balance access with governance.
  • Retaining subject matter expertise and prioritizing quality are key considerations in leveraging AI in these industries. The metrics for success include speed, visibility, and customer satisfaction.
  • Overall, the future of AI in heavy industry and field services looks promising, but it requires careful navigation of challenges and a focus on delivering value to customers.
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