Ken Elliott, Co-founder & Chief Data & Analytics Officer, Provision Analytics

Ken Elliott is Co-founder and Chief Data & Analytics Officer at Provision Analytics, an advisory services firm helping clients harness the power of data and artificial intelligence. Ken has been recognized by DataIQ as one of the “100 Most Influential people in Data” and by AIMS Research as one of the “100 Top Leaders in Artificial Intelligence”. He has been delivering data and analytic solutions for over 30 years. Prior to Provision Analytics, Ken was the Chief Data & Analytics Officer at Waste Management, Vice President of Analytics at UnitedHealthcare, led Global Analytics at Hewlett Packard Enterprise Services, and was Vice President of Analytic Solutions as SPSS Inc (now IBM).

Recently, in an exclusive interview with Digital First Magazine, Ken shared his insights on the impact of AI on data science, his professional journey, significant career milestones, pearls of wisdom, and much more. The following excerpts are taken from the interview.

Do you think that data science is perceived to be more important than ever before? And what has been the impact of AI on data science?

Yes, data science is truly more important than ever.  Not only because of the exponentially growing amount of data to analyze, but labor shortages in many industries are driving the need for automation in both front-office and back-office business processes.  And, when these processes require automated or semi-automated decisions, companies are turning to data science to create more intelligent, scalable, accurate, and secure applications.

The advent of Generative AI capabilities, like ChatGPT, is adding exponential demand on data science.  Specifically, the “science” part. GenAI solutions are deceptively simple and seemly accurate at face value.  However, we are beginning to see the critical need for disciplined scientific methods to reduce bias, ensure accuracy, and rapidly identify unintended outcomes.  The ‘science’ will help companies avoid regulatory and ethical issues while improving outcomes for their business and society.

What can leaders do to promote a data driven decision-making culture in their organizations?

To become a data-driven organization, companies must first have a true desire to do so.  Having a passion to be data-driven implies that the company (1) understands the value of data and sees it as a corporate asset, (2) has a clear understanding of how data can improve business processes and/or create new revenue opportunities, (3) has committed to a vision and implemented policies and practices that integrate data stewardship throughout their ways of working.

Leaders looking to promote a data-driven culture should start by proving the value of data and analytics through quick wins and promoting the success of those cases as part of a well-planned Data Literacy campaign. Rince and repeat.

Ken, please tell us about your past work experiences, career growth journey, and your long-term vision.

I began my career at a statistical software company called SPSS Inc. (now part of IBM). There, I had the privilege to build the global professional services function delivering data and analytics solutions to companies across numerous industries. From there I ‘went to the dark side’ and joined the “IT” within HP Inc. delivering data and analytics to all business functions of the then $300B company. I then joined the ‘operations’ organization of United Healthcare to deliver data and analytics supporting the business functions directly. Most recently, I was Chief Data and Analytics Officer at an environmental services company (Waste Management).

This combination of experience has given me broad exposure across multiple industries and from various perspectives including software development, consulting services, business operations, and IT delivery management.

Admittedly, I did not plan this. I wish I could say I had. It was all dumb luck. My advice to aspiring data scientists (or anyone) is don’t overthink it.  Follow your passion and enjoy the journey. You’ll only have it all figured out when you’re done.

As the Co-founder, what are your top two priorities at Provision Analytics?

The mission of Provision Analytics is to help companies navigate and accelerate their journey to becoming data-driven and maximizing their use of AI. Our focus is on helping companies become self-sufficient along their data maturity journey in a way that aligns with their corporate strategy.

The hot topic now is the safe, ethical, and impactful use of Generative AI.  We are seeing a dramatic rise up the ‘hype cycle’ which will be followed by an equally dramatic fall through the ‘trough of disillusionment’.  Our goal is to use our experience in data, analytics, and digital transformation to help companies chart a straight course through this cycle and emerge as industry leaders in the new age of AI.

What are your thoughts about ChatGPT? Do you feel that data science jobs may become obsolete or can the AI chatbot help data scientists in diligent tasks?

Generative AI models, like ChatGPT, will have a dramatic impact on the productivity of software programming in general – including data science.  However, this will not eliminate the need for data scientists. In fact, it will have the opposite effect.  These new systems will require more scientists to address the increased demand.

Data scientists are too burdened with data wrangling and code development.  I am optimistic that accelerators in each of these domains will allow data scientists to focus more on business problems and crafting innovative approaches to solving the more challenging aspects of bias, ethics, accuracy, and transparency.

What key personality traits are common among successful data scientists?

The best data scientists are more focused on achieving business outcomes than writing elegant code. Sometimes, simple solutions are the most appropriate.  Great data scientists look for the best path to achieve the optimal business outcome.  Too often, young data scientists focus more on building the next cool thing and hope it adds value, versus realizing that only things that add value are cool.

As far as personality traits, I would say Curiosity, Outcome Orientation, Fearless (fail fast and learn), and for all of us – caring.

Are there still hurdles chief data officers have to overcome in their roles or are CDOs now accepted in parts of the organizational hierarchy?

The role of Chief Data Officer is emerging.  Companies either don’t have one, have one but struggle, or have a well-established CDO function.  The hurdles are mostly with the middle group.  These CDOs are appointed, but they are spending too much time clarifying or justifying their role.

It is ironic that we’ve accepted Chief Finance Officers to oversee our finances, Chief People Officers to oversee our people, Chief Operating Officers to oversee our operations, Chief Legal Officers to oversee our legal affairs, but are struggling with the appointment of Chief Data Officers to oversee our data.

I believe this is due to three primary issues. First, data is still not understood and often viewed as an “IT” thing.  It must be seen as a business asset. Second, data is pervasive across all business functions, both in its production and its use.  As a result, ownership is ambiguous and shared. Finally, data tells a story. As an executive, if I relinquish data to another executive, it might not tell the story I believe. Given that most of it is bad anyway, I don’t trust losing control of my story.

Once a company realizes that data is a share corporate ‘asset’ that needs governance, management, and monetization, a CDO can be of tremendous value as a trusted corporate steward.

What has been your most career-defining moment that you are proud of?

It has been an exciting career with many amazing things to celebrate.  I expect many more to come.  But, so far, the thing I am most proud of is seeing my team prosper.  At HP we were encouraged to manage talent and proactively rotate and/or move up to top talent.  My team was often poached for future leaders. That made me very proud.  It is an outcome I aspire to in every organization I am a part of.

What is the best career advice you’ve received and how have you sought to put this into practice?

I distinctly remember the day, early in my career, when I screwed up a project which led to a delay in a customer delivery date. My boss and I met with the customer to explain. I was panicking and sure I was going to be fired after the meeting.  Instead, my boss took accountability and never blamed me.  Instead, we met the next day to walk through the project and worked together to find out how the miss happened and what process we could put into place to help ‘others’ avoid this outcome in the future.

It was my first lesson in being a caring leader, and also embracing failure fast and learn mindset.

What are your passions outside of work?

My wife and I have two children who have graduated and are on to their careers. My greatest joy is getting together as a family, hanging out, playing games, or enjoying a movie. We also enjoy sailing. At least once a year you’ll find us on a catamaran in the BVIs. On a personal level I enjoy making music and creating art.

What advice would you offer others looking to build their careers as data scientists?

Find a company that has a warm culture and a cause you believe in.  Make sure your manager is finding ways to help you grow.  You are in demand, so don’t accept anything less.  Focus more on business outcomes than the complexity of your code. Devote time to personal learning – perhaps join a Kaggle competition or two.  Have fun. And, be prepared to give back by mentoring others.

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