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049 - CxO & Digital Transformation Focus: (10) Reasons Users Can’t or Won’t Use Your Team’s ML/AI-Driven Software and Analytics Applications
Join the Free Webinar Related to this Episode
I'm taking questions and going into depth about how to address the challenges in this episode of Experiencing Data on Oct 9, 2020. 30 Mins + Q/A time. Replay will also be available.
Register Now
Welcome back for another solo episode of Experiencing Data. Today, I am primarily focusing on addressing the non-digital natives out there who are trying to use AI/ML in innovative ways, whether through custom software applications and data products, or as a means to add new forms of predictive intelligence to existing digital experiences.
Many non-digital native companies today tend to approach software as a technical “thing” that needs to get built, and neglect to consider the humans who will actually use it — resulting in a lack of business or organizational value emerging. While my focus will be on the design and user experience aspects that tend to impede adoption and the realization of business value, I will also talk about some organizational blockers related to how intelligent software is created that can also derail a successful digital transformation efforts.
These aren’t the only 10 non-technical reasons an intelligent application or decision support solution might fail, but they are 10 that you can and should be addressing—now—if the success of your technology is dependent on the humans in the loop actually adopting your software, and changing their current behavior.
Links
- Want to address these issues? Learn about my Self-Guided Video Course and Instructor-Led Seminar
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By Brian T. O’Neill from Designing for Analytics
5
3939 ratings
Join the Free Webinar Related to this Episode
I'm taking questions and going into depth about how to address the challenges in this episode of Experiencing Data on Oct 9, 2020. 30 Mins + Q/A time. Replay will also be available.
Register Now
Welcome back for another solo episode of Experiencing Data. Today, I am primarily focusing on addressing the non-digital natives out there who are trying to use AI/ML in innovative ways, whether through custom software applications and data products, or as a means to add new forms of predictive intelligence to existing digital experiences.
Many non-digital native companies today tend to approach software as a technical “thing” that needs to get built, and neglect to consider the humans who will actually use it — resulting in a lack of business or organizational value emerging. While my focus will be on the design and user experience aspects that tend to impede adoption and the realization of business value, I will also talk about some organizational blockers related to how intelligent software is created that can also derail a successful digital transformation efforts.
These aren’t the only 10 non-technical reasons an intelligent application or decision support solution might fail, but they are 10 that you can and should be addressing—now—if the success of your technology is dependent on the humans in the loop actually adopting your software, and changing their current behavior.
Links
- Want to address these issues? Learn about my Self-Guided Video Course and Instructor-Led Seminar
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