41 Min.
Technically Right, Effectively Wrong: Why 85% Data Science Projects Fail Tech Entrepreneur on a Mission Podcast
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- Technologie
This podcast interview focuses on a key aspect to drive product innovation and that is mastering human centered design. My guest is Brian T. O’Neill, founder and principal of Designing for Analytics.
Brian T. O'Neill is a designer, advisor, and founder of Designing for Analytics, an independent consultancy which helps organizations design innovate innovative products powered by data science and analytics. For over 20 years, he has worked with companies including DellEMC, Global Strategy Group, Tripadvisor, Fidelity, JP Morgan Chase, ETrade and several SAAS startups. He has spoken internationally, giving talks at O'Reilly Strata, Enterprise Data World, the International Institute for Analytics Symposium, Predictive Analytics World, and Boston College. Brian also hosts the 5-star podcast, Experiencing Data, where he reveals the strategies and activities that product, data science and analytics leaders are using to deliver valuable experiences around data. In addition to consulting, Brian is also a professional percussionist and has performed at Carnegie Hall and The Kennedy Center.
What triggered me to invite Brian to my podcast was one of his quotes about the fact that 85% of AI, analytics, and big data projects fail. That’s why we explore why this is the case, and what needs to be done different in order to be successful – creating software products that people find worth making a remark about.
Here are some of his quotes:
I started to see really, really bad survey results over 10 plus years. What I'm specifically talking about here is the success rate for delivering data projects.
The theme here is the success rate on launching successful data initiatives hovered around 10 to 25%. So that means there’s failure rates up in the 75% plus.
My general feeling was: There's a lack of a focus on the human aspect of analytics and data science projects and products right now. We're trying to use the data science and analytics hammer, and we're looking for stuff to hit. But no one's really aware why do we need holes? Who needs a hole? And where do they need the hole? Instead, it's just hit nails wherever we can and hope that someone maybe needs a hole there.
During this interview, you will learn three things:
That a first step in succeeding data projects is to stop forgetting about the value of fun and engaging with people.
Why it is key to define the owner of value creation in your team – i.e. someone that owns the problem and the accountability for analytics and data science solutions to product value.
That we have lost the humanity aspect in solution design – and a way to fix that and get some real wins is to spend time developing soft skills
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This podcast interview focuses on a key aspect to drive product innovation and that is mastering human centered design. My guest is Brian T. O’Neill, founder and principal of Designing for Analytics.
Brian T. O'Neill is a designer, advisor, and founder of Designing for Analytics, an independent consultancy which helps organizations design innovate innovative products powered by data science and analytics. For over 20 years, he has worked with companies including DellEMC, Global Strategy Group, Tripadvisor, Fidelity, JP Morgan Chase, ETrade and several SAAS startups. He has spoken internationally, giving talks at O'Reilly Strata, Enterprise Data World, the International Institute for Analytics Symposium, Predictive Analytics World, and Boston College. Brian also hosts the 5-star podcast, Experiencing Data, where he reveals the strategies and activities that product, data science and analytics leaders are using to deliver valuable experiences around data. In addition to consulting, Brian is also a professional percussionist and has performed at Carnegie Hall and The Kennedy Center.
What triggered me to invite Brian to my podcast was one of his quotes about the fact that 85% of AI, analytics, and big data projects fail. That’s why we explore why this is the case, and what needs to be done different in order to be successful – creating software products that people find worth making a remark about.
Here are some of his quotes:
I started to see really, really bad survey results over 10 plus years. What I'm specifically talking about here is the success rate for delivering data projects.
The theme here is the success rate on launching successful data initiatives hovered around 10 to 25%. So that means there’s failure rates up in the 75% plus.
My general feeling was: There's a lack of a focus on the human aspect of analytics and data science projects and products right now. We're trying to use the data science and analytics hammer, and we're looking for stuff to hit. But no one's really aware why do we need holes? Who needs a hole? And where do they need the hole? Instead, it's just hit nails wherever we can and hope that someone maybe needs a hole there.
During this interview, you will learn three things:
That a first step in succeeding data projects is to stop forgetting about the value of fun and engaging with people.
Why it is key to define the owner of value creation in your team – i.e. someone that owns the problem and the accountability for analytics and data science solutions to product value.
That we have lost the humanity aspect in solution design – and a way to fix that and get some real wins is to spend time developing soft skills
See acast.com/privacy for privacy and opt-out information.
Learn more about your ad choices. Visit megaphone.fm/adchoices
41 Min.