Robert Welborn's guest appearances

Robert Welborn

CX Network

SSONext

B2BiQ

PEX Network | Process Excellence Network

Steve Kato-Spyrou

Edda Blumenstein

Deborah Kops

Anil Bhavnani

Jack Cheng

Alexander Hubel

Deepak Subbarao

Ayanna Howard

Chris Gilmore

Martin Felder

Delphine Bernard

Adrian Terry

Pamela Wolfe

Dmitry Popov

Hendrik Boehmer

OwlTail

Robert Welborn is the Director, Data &amp; Data Science for General Motors. As he sees it, global corporate enterprise has- for the most part, seen data as a luxury, “we'll get to reporting when we get to reporting, we'll upsell, we'll monetize.” Not that monetizing is a bad thing, but Robert’s point is that we haven’t been using data as the ultimate element of decision-making. Sure- data-driven decision-making has occurred, but not to the extent of managing enterprise existence. The global pandemic had a particular effect on Robert’s company. For over 100 years General Motors manufactured motor vehicles. Then on April 8th, 2020- General Motors became a ventilator manufacturer. What used to be a fun data dance that Robert and his team would do privately suddenly became precision choreographed ballet of the highest order with every decision-maker involved. “What we had used as a luxury before suddenly was driving everything. We're having conversations with our suppliers, with the UAW and with the plants showing them through data what we're going to do next.” And the data told them just what to do. Robert and his team were seeing vehicle-level data as the pandemic burst across the globe and made it’s way to the East Coast of the United States. “The data is saying we can shut down. And the data that we're getting from the state of New York in specific is saying that we, if we were doing anything right now- we should be building ventilators. If there's anything that we would do, we should build insulators and we should build masks.”

Robert Welborn is the Director, Data &amp; Data Science for General Motors. As he sees it, global corporate enterprise has- for the most part, seen data as a luxury, “we'll get to reporting when we get to reporting, we'll upsell, we'll monetize.” Not that monetizing is a bad thing, but Robert’s point is that we haven’t been using data as the ultimate element of decision-making. Sure- data-driven decision-making has occurred, but not to the extent of managing enterprise existence. The global pandemic had a particular effect on Robert’s company. For over 100 years General Motors manufactured motor vehicles. Then on April 8th, 2020- General Motors became a ventilator manufacturer. What used to be a fun data dance that Robert and his team would do privately suddenly became precision choreographed ballet of the highest order with every decision-maker involved. “What we had used as a luxury before suddenly was driving everything. We're having conversations with our suppliers, with the UAW and with the plants showing them through data what we're going to do next.” And the data told them just what to do. Robert and his team were seeing vehicle-level data as the pandemic burst across the globe and made it’s way to the East Coast of the United States. “The data is saying we can shut down. And the data that we're getting from the state of New York in specific is saying that we, if we were doing anything right now- we should be building ventilators. If there's anything that we would do, we should build insulators and we should build masks.”

Robert Welborn, GM

Celonis

Robert Welborn returns to take us through his interesting recent past.  Also, join our Celonis Podcast Mini Series guest JP Thomsen by visiting  celonis.com/celosphere-live, available on-demand.    

Robert Welborn returns to take us through his interesting recent past.  Also, join our Celonis Podcast Mini Series guest JP Thomsen by visiting <a href="http://celonis.com/celosphere-live%22%20%5Ct%20%22_blank" rel="nofollow" target="_blank"> celonis.com/celosphere-live</a>, available on-demand.

Robert Welborn & Celonis Podcast Mini Series

Robert Welborn joins us again for the second part of autonomous vehicle myths. During this discussion, Robert compares the vast and critical differences between the capabilities of today’s math and the necessity of developing tomorrow’s math before fully autonomous vehicles are a safe, mainstream option. He parses out the weakness in today’s autonomous vehicles. For example, converting visual information into digital information and then trying to extract features from that before making a decision off of those inputs. As one could imagine, and as Robert so vividly depicts, there are issues—namely safety—in expecting a computing system to respond quickly and correctly to the infinite numbers of inputs it may receive. Robert closes the discussion with a few viable ways of progressing the technology.

Robert Welborn joins us again for the second part of autonomous vehicle myths. During this discussion, Robert compares the vast and critical differences between the capabilities of today’s math and the necessity of developing tomorrow’s math before fully autonomous vehicles are a safe, mainstream option. He parses out the weakness in today’s autonomous vehicles. For example, converting visual information into digital information and then trying to extract features from that before making a decision off of those inputs. As one could imagine, and as Robert so vividly depicts, there are issues—namely safety—in expecting a computing system to respond quickly and correctly to the infinite numbers of inputs it may receive. Robert closes the discussion with a few viable ways of progressing the technology.

PEX: Robert Welborn, (Myths Part 2)

Ep. 143: Robert Welborn, (Myths Part 2)

Robert Welborn discusses common myths surrounding autonomous vehicles. He starts with three TV shows that have skewed perception around AVs. Next, he sets expectations around the maturity model of AVs by describing the stages as childhood, adolescence, and adulthood. Today’s data presents itself in three-dimensional forms, and Robert is realistic about the struggles and opportunities within this new model of data. It is the engineers behind AVs who are tasked with making things work, and Robert spends some time pulling back the curtain on their trials and tribulations. Finally, Robert recognizes that the elasticity and compatibility of all of the elements at play in autonomous vehicles have a tendency to be overestimated. 

Robert Welborn discusses common myths surrounding autonomous vehicles. He starts with three TV shows that have skewed perception around AVs. Next, he sets expectations around the maturity model of AVs by describing the stages as childhood, adolescence, and adulthood. Today’s data presents itself in three-dimensional forms, and Robert is realistic about the struggles and opportunities within this new model of data. It is the engineers behind AVs who are tasked with making things work, and Robert spends some time pulling back the curtain on their trials and tribulations. Finally, Robert recognizes that the elasticity and compatibility of all of the elements at play in autonomous vehicles have a tendency to be overestimated.

CX: Robert Welborn, (Myths Part 1)

Robert Welborn discusses five common myths surrounding autonomous vehicles in this discussion. He starts with three TV shows that have skewed perception around AVs. Next, he sets expectations around the maturity model of AVs by describing the stages as childhood, adolescence, and adulthood. Today’s data presents itself in three-dimensional forms, and Robert gives time to the struggles and opportunities within this new model of data. It is the engineers behind AVs who are tasked with making things work, and Robert spends some time pulling back the curtain on their trials and tribulations. Finally, Robert recognizes that the elasticity and compatibility of all of the elements at play in autonomous vehicles have a tendency to be overestimated. 

Robert Welborn discusses five common myths surrounding autonomous vehicles in this discussion. He starts with three TV shows that have skewed perception around AVs. Next, he sets expectations around the maturity model of AVs by describing the stages as childhood, adolescence, and adulthood. Today’s data presents itself in three-dimensional forms, and Robert gives time to the struggles and opportunities within this new model of data. It is the engineers behind AVs who are tasked with making things work, and Robert spends some time pulling back the curtain on their trials and tribulations. Finally, Robert recognizes that the elasticity and compatibility of all of the elements at play in autonomous vehicles have a tendency to be overestimated.