Building an inclusive data culture at Powell Industries

The industry leader in electrical manufacturing paves the way for AI with a unified, inclusive data culture and strategy.
March 28, 2024

Known for their expertise in designing and producing electrical systems for big-league industrial clients, Powell is redefining what’s possible when leveraging data, teamwork and advanced analytics: better processes, higher product quality and strategic innovation.

In the latest episode of the “Data Drip” podcast, Ajay Bidani, Data and Insights Manager at Powell Industries dives into the challenges and triumphs of data democratization and the importance of data readiness for AI. 

Data democratization is central to Bidani’s strategy at Powell Industries. As a data leader there for 17 years, he’s helped Powell evolve from specialized, independent data teams to data proficiency across all departments. He’s actively involved in enabling data analysis and decision-making for every one of Powell’s 2,300+ employees. This strategic shift produced streamlined workflows that empower teams to analyze data and contribute insights to their specific projects and beyond.

Building such an inclusive data culture is no small task. Every employee needs to be equipped and trained to make data-informed decisions. In many organizations, data efforts often remain isolated, creating silos and duplicative work across departments. Bidani is hyper-aware of this risk and encourages his teams to use data in ways that promote broader adoption.

“Many of us are used to handling data tasks individually, like using Excel,” Bidani says. “While this builds data familiarity, it can result in creating unintentional data silos and repetitive work across the organization.”

Bidani’s tactics rely on developing critical soft skills in data engineering. For 2024, he sees open-mindedness and listening as two of the most important skills for modern data professionals. “Being an expert in a [programming] language may not be the thing that's essential. It's understanding how to design with it. Is the goal to learn the language or is the goal to be successful with the language?” 

Why you can’t data science your way to AI success

In 2024, Bidani’s team is laying the groundwork to support AI and machine learning. He believes that success with AI/ML hinges on a strong and reliable data foundation. 

“Being in manufacturing teaches you that most problems with AI start with data,” Bidani adds. “Do you have enough data? [...] You might try to ‘data science’ your way to a solution, but the only way to articulate how the pieces fit is to actually understand if you have enough data and why it works the way it does.” 

Moving into AI will require significant amounts of data to model an organization and its problems. Unless there’s enough data for the models, he questions whether AI will deliver business value for organizations. 

“All the modeling that you may have put off, AI is not going to be forgiving about the fact that you weren't willing to do that part,” notes Bidani. “You won’t get going with AI without understanding how to train it — like really train it on what your business does.”

Listen to the full episode of the Data Drip podcast with Ajay Bidani, Data and Insights Manager at Powell Industries, here.

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Data insights
Data insights

Building an inclusive data culture at Powell Industries

Building an inclusive data culture at Powell Industries

March 28, 2024
March 28, 2024
Building an inclusive data culture at Powell Industries
The industry leader in electrical manufacturing paves the way for AI with a unified, inclusive data culture and strategy.

Known for their expertise in designing and producing electrical systems for big-league industrial clients, Powell is redefining what’s possible when leveraging data, teamwork and advanced analytics: better processes, higher product quality and strategic innovation.

In the latest episode of the “Data Drip” podcast, Ajay Bidani, Data and Insights Manager at Powell Industries dives into the challenges and triumphs of data democratization and the importance of data readiness for AI. 

Data democratization is central to Bidani’s strategy at Powell Industries. As a data leader there for 17 years, he’s helped Powell evolve from specialized, independent data teams to data proficiency across all departments. He’s actively involved in enabling data analysis and decision-making for every one of Powell’s 2,300+ employees. This strategic shift produced streamlined workflows that empower teams to analyze data and contribute insights to their specific projects and beyond.

Building such an inclusive data culture is no small task. Every employee needs to be equipped and trained to make data-informed decisions. In many organizations, data efforts often remain isolated, creating silos and duplicative work across departments. Bidani is hyper-aware of this risk and encourages his teams to use data in ways that promote broader adoption.

“Many of us are used to handling data tasks individually, like using Excel,” Bidani says. “While this builds data familiarity, it can result in creating unintentional data silos and repetitive work across the organization.”

Bidani’s tactics rely on developing critical soft skills in data engineering. For 2024, he sees open-mindedness and listening as two of the most important skills for modern data professionals. “Being an expert in a [programming] language may not be the thing that's essential. It's understanding how to design with it. Is the goal to learn the language or is the goal to be successful with the language?” 

Why you can’t data science your way to AI success

In 2024, Bidani’s team is laying the groundwork to support AI and machine learning. He believes that success with AI/ML hinges on a strong and reliable data foundation. 

“Being in manufacturing teaches you that most problems with AI start with data,” Bidani adds. “Do you have enough data? [...] You might try to ‘data science’ your way to a solution, but the only way to articulate how the pieces fit is to actually understand if you have enough data and why it works the way it does.” 

Moving into AI will require significant amounts of data to model an organization and its problems. Unless there’s enough data for the models, he questions whether AI will deliver business value for organizations. 

“All the modeling that you may have put off, AI is not going to be forgiving about the fact that you weren't willing to do that part,” notes Bidani. “You won’t get going with AI without understanding how to train it — like really train it on what your business does.”

Listen to the full episode of the Data Drip podcast with Ajay Bidani, Data and Insights Manager at Powell Industries, here.

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