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Jordan Morrow
Data & AI Literacy, Storytelling, Strategy | Author | Creator | Award Winning | 3x DataIQ 100 Winner | Owner & Founder | Public Speaking
Jordan Morrow is a prominent figure in the field of data literacy, currently serving as the Senior Vice President of Data & AI Transformation at AgileOne. He is also the founder and CEO of Bodhi Data and has been instrumental in developing one of the world's first data literacy programs, earning him the title of the "Godfather of Data Literacy" due to his pioneering contributions in this area.124
Professional Background
Morrow has an extensive background in data and analytics, having previously worked with major organizations such as American Express and Qlik. His career is marked by a commitment to educating individuals and organizations on how to effectively utilize data and analytics for decision-making. He has authored three influential books: Be Data Literate, Be Data Driven, and Be Data Analytical, which focus on enhancing data literacy skills.125
Contributions and Recognition
In addition to his roles at AgileOne and Bodhi Data, Morrow serves as the Chair of the Advisory Board for The Data Literacy Project, where he promotes global initiatives aimed at improving data literacy across various sectors. He frequently speaks at international conferences, sharing insights on data-driven strategies and AI applications.14 His efforts have garnered multiple accolades, including recognition as a top data influencer by various organizations.23
Personal Life
Jordan Morrow resides near Salt Lake City, Utah, where he balances his professional pursuits with personal interests, including fitness, mountain adventures, and spending time with his five children.15
Highlights
Specialization vs Generalization
Early in my career, I was interested or looking at different areas of the company I worked for. I am one who is interested in different topics. I would apply or look at different roles. This didn't fly well with the group I was hired into.
The group I was hired into was one that was maybe what can be considered an old school area, it is an established area, and it is one that you can get a certificate in.
I was told to focus in. If I remember it right, the theme would be I needed to focus in and not be exploring other areas or bounce around. Essentially, I was told to specialize and to just focus in.
Now, I still get interested in different things and yes, I am more specialized in on data and AI, but those areas have different areas within. So, is it only specialize or is it a combination of the two?
I would say specialize in something/s but also gather general knowledge within other areas. For example, if you are a marketing manager, helping yourself would be how to utilize AI well in your role. Your specialty is marketing and your general knowledge is AI.
Data and AI literacy is a thing to be thinking of here. You don't need to specialize fully as a data or AI professional, but what about gaining the ability to read, work with, analyze, and communicate with data and AI within your area of specialization.
What can you do to get rolling with your general knowledge you want to learn about? Second, what about finding areas and specialization in different areas of data and AI as well as your career specialization?
Overall, gain knowledge and develop. Learn, don't waste the time.
What about those I use to work with? I think I am on the same level or advanced past some or all of them, maybe less 1 that I know of, in my career. I am not in the field I started in, I did bounce out. I potentially had an opportunity for a promotion within an area but I didn't want it, so I didn't go for it. I don't know if I would be where I am today if I had gone for it.
Take the time to be yourself, lead, and grow.
Stay nerdy and be you, my friends!!
#dataliteracy #data #AI #AIstrategy #AILiteracy

OK, OK, I have found the magic bullet...and its name is....AI!!
Wait, it isn't the magic bullet you say? Why?
OK, I hope people don't think AI is a magic solution that is going to solve all your problems right now...It isn't there.
Have you invested or used AI and it isn't giving you results you like? Why could that be?
One issue could be your data itself...How is the data feeding your AI?
If you don't have a good data, quality data, you may have something giving you poor results. So, as you invest in AI ensure you aren't just buying a tool but setting yourself up for success by doing what some may deem the unsexy work: data cleaning and managing it well.
Here are some things you can do:
- Take time to evaluate your data landscape. Evaluate and find where gaps are, where things are going in a poor direction.
- Set a plan in place to clean the data and put process in place to help issues not to pop up again.
- Set in place an iteration time period, maybe quarterly. Take time then to evaluate the data and ensure old problems haven't popped back up and/or new ones appeared.
- Test and evaluate results.
- Oh, and learn more about AI and its needs, tools that exist, and what things your organization need to succeed.
One final note and learn from George Firican: have a data governance program or put one in place.
Stay nerdy, my friends.
#dataliteracy #datamanagement #datagovernance #datastrategy #AI #AILiteracy #AIstrategy
Meme Credit: Mimirs Well Substack

