Earlier today, I attended a LinkedIn Event hosted by Evalueserve. I came across it by accident, but I am glad that I did.
Titled “Revolutionize Your BI: Digital Transformation Stories from the Real World,” the panel included Whirlpool’s Gowri Namboodiri, Caterpillar‘s Ben Newman, and Coyote Logistics‘ Director, Supply Chain Engineering & Analytics Jay Zaleski. The moderator was Evaluserve’s Vice President, Gabriel Keeler.
Not long after I signed in, I posted the following question:
“I noted that Gowri Namboodiri said that her team led with ascertaining the collective KPIs before introducing BI technology. Is that right?” Gowri’s answer starts at the 18:24 mark of the video replay.
I then asked a follow-up question: “Were there conflicting KPIs with different departments?” All three panelists answered this question to close the session, starting at the 31:47 mark of the video replay. Not surprisingly, all three said yes, there were KPI conflicts.
Revisiting A Case Study
The excerpt from the following post prompted me to ask the questions I did: Are you chasing solutions or solving problems?
“When organizations make the mistake of leading with technology, they are bending their people and processes around an equation-based model approach in which the tech is the driver for success.
When you lead with people and process understanding – an agent-based model, technology moves from a functional driver to a problem-solving tool that streamlines and delivers efficiencies and tangible results.”
While you can read the post’s case study specifics, the suggestion is straightforward – technology, no matter how advanced – including AI, has never, nor will it ever, overcome “siloed thinking.” Once again, the case study provides a compelling example of why you should never lead with AI.
There Is No BI Without The “I”
KPI conflicts will undermine any real opportunity to not only gain meaningful intelligence but also hinder individual and collective stakeholder success. KPI alignment has to be in place before an AI solution is introduced. Otherwise, you will experience the age-old “garbage in-garbage out scenario.”
As you ponder the validity of the above statement, here are just three of many statistics that you should know:
- According to Gartner, 70-80% of enterprise business intelligence initiatives fail.
- A BI project will fail if you don’t fully understand who will be using the solution and what they’re trying to accomplish. “A BI project is likely to fail if the businesses are not interviewed correctly to gather requirements,” says Kippen.
- Data Science methods have influenced business decisions since their introduction to the world. But only a few people know that most data science projects fail and never make it to production. According to Venture Beat, about 87% of data science projects are never deployed.
Today’s Post Takeaway
Stepping Out From Behind The Technology: I have often talked about the importance of service provider leadership stepping out from behind their company’s logo. What I emphasize is that the critical play is not the tech but the expertise behind the tech – the market expertise and experience to leverage tech to solve a problem.
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Procurement Insights
When it comes to BI and AI, A should always follow B!
Posted on April 19, 2024
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Earlier today, I attended a LinkedIn Event hosted by Evalueserve. I came across it by accident, but I am glad that I did.
Titled “Revolutionize Your BI: Digital Transformation Stories from the Real World,” the panel included Whirlpool’s Gowri Namboodiri, Caterpillar‘s Ben Newman, and Coyote Logistics‘ Director, Supply Chain Engineering & Analytics Jay Zaleski. The moderator was Evaluserve’s Vice President, Gabriel Keeler.
Not long after I signed in, I posted the following question:
“I noted that Gowri Namboodiri said that her team led with ascertaining the collective KPIs before introducing BI technology. Is that right?” Gowri’s answer starts at the 18:24 mark of the video replay.
I then asked a follow-up question: “Were there conflicting KPIs with different departments?” All three panelists answered this question to close the session, starting at the 31:47 mark of the video replay. Not surprisingly, all three said yes, there were KPI conflicts.
Revisiting A Case Study
The excerpt from the following post prompted me to ask the questions I did: Are you chasing solutions or solving problems?
“When organizations make the mistake of leading with technology, they are bending their people and processes around an equation-based model approach in which the tech is the driver for success.
When you lead with people and process understanding – an agent-based model, technology moves from a functional driver to a problem-solving tool that streamlines and delivers efficiencies and tangible results.”
While you can read the post’s case study specifics, the suggestion is straightforward – technology, no matter how advanced – including AI, has never, nor will it ever, overcome “siloed thinking.” Once again, the case study provides a compelling example of why you should never lead with AI.
There Is No BI Without The “I”
KPI conflicts will undermine any real opportunity to not only gain meaningful intelligence but also hinder individual and collective stakeholder success. KPI alignment has to be in place before an AI solution is introduced. Otherwise, you will experience the age-old “garbage in-garbage out scenario.”
As you ponder the validity of the above statement, here are just three of many statistics that you should know:
Today’s Post Takeaway
Stepping Out From Behind The Technology: I have often talked about the importance of service provider leadership stepping out from behind their company’s logo. What I emphasize is that the critical play is not the tech but the expertise behind the tech – the market expertise and experience to leverage tech to solve a problem.
30
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