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Dan Everett, Owner, Insightful Research

Describe your career to date

I started my career in data and analytics in 1997 working with tools to migrate data from AS400 midrange servers to relational databases on Unix servers. Over the years my data roles have included technical support, database administration, pre-sales, product management, and marketing.  

I have acquired many skills along the way such as data and process modeling, data discovery and cataloging, data quality and governance, data privacy and protection, data visualization, master data management, business process management, and value chain analysis.  

Around the time I started my data career, my oldest son was diagnosed with autism which started me on a journey to understand how the brain processes information and makes decisions. Over the years I realized the things I had learned about the brain to help my son, could be used by organizations to decrease resistance to change, increase employee engagement, and improve objective evaluation of facts. Now my passion is helping people understand how the brain’s information processing systems influence behavior.  

Data and analytics leaders consistently report people and behavior as their biggest challenge to success. Using neuroscience and behavioral psychology I have created frameworks, methods, and workshops to help organizations turn people into their biggest opportunity for data and analytics success.  

In my workshops, I focus on the practical application of neuroscience principles. For instance, how to get stakeholder buy-in for data and analytics initiatives. This includes funding from leadership teams, operational support from business management, and commitment from frontline employees to execute required tasks. 

What challenges do you see for data in the year ahead that will have an impact on you and on the industry as a whole?  

One of the biggest challenges I see is that around half of employees and consumers do not trust that artificial intelligence (AI) will be used responsibly. As an industry we must address this fundamental trust gap to realize AI’s full potential. Trust is critical for getting employees to adopt the changes needed to integrate AI into operational processes and activities.  

Employees also need skill development and guidance to help them trust in their ability to use new tools such as generative AI. And broader use of generative AI will increase the risk of corporate reputation and consumer trust being negatively impacted by hallucinations. 

How do you see data literacy developing across a) your network and b) the data industry generally? 

What I see within my network and what I believe is needed on a broader scale is greater focus on improving business outcomes using data. This requires a strategy and objectives that address fundamental business needs, such as managing revenue, costs, and risks, and then working backwards to data and analytics needs to fulfill the business needs.  

I would like to see more emphasis on developing organizational understanding of business value chains and data’s role in improving the outputs of those value chains. Ultimately creating a culture where the combination of technical skill and business understanding drives better business performance. 

How do you see the industry preparing for AI adoption and change management? 

AI adoption will require change management across people, process, and technology. For me, the most important preparation we can make is to address the trust gap people currently have around responsible use of AI.  

I believe companies can benefit from refining their culture, values, and policies to demonstrate commitment to using AI not merely as a tool for increasing productivity, but as a means for generating value for everyone in society. I also think understanding and addressing the psychological impact AI may be having on employees’ sense of fairness, worth, and autonomy will be crucial for AI adoption. 

Dan Everett
has been included in:
  • 100 Influencers 2024 (USA)