際際滷shows by User: ltwalt / http://www.slideshare.net/images/logo.gif 際際滷shows by User: ltwalt / Tue, 15 May 2018 15:39:53 GMT 際際滷Share feed for 際際滷shows by User: ltwalt Challenges in Implementing Analytical Solution /slideshow/challenges-in-implementing-analytical-solution-97178661/97178661 rta-implementinganaltyics-180515153953
We have all attended presentations either telling how great an analytical solution performed or how to successfully implement a solution or technique. It isn't a surprise to seasoned analytical professionals that most analytical projects are not successfully implemented. Unfortunately, due to selection bias, these projects are seldom presented. Medicine has a long history of using morbidity and mortality briefs to learn and advance the profession. These briefs share stories on negative outcomes and the events and decisions that led to those outcomes. This presentation uses the morbidity and mortality model and will take examples from analysis performed from the desert of Iraq, to the South China Sea, to the ice of the St. Louis Blue's Scottrade Center hockey rink to share negative outcomes and the lessons to be learned.]]>
We have all attended presentations either telling how great an analytical solution performed or how to successfully implement a solution or technique. It isn't a surprise to seasoned analytical professionals that most analytical projects are not successfully implemented. Unfortunately, due to selection bias, these projects are seldom presented. Medicine has a long history of using morbidity and mortality briefs to learn and advance the profession. These briefs share stories on negative outcomes and the events and decisions that led to those outcomes. This presentation uses the morbidity and mortality model and will take examples from analysis performed from the desert of Iraq, to the South China Sea, to the ice of the St. Louis Blue's Scottrade Center hockey rink to share negative outcomes and the lessons to be learned.]]> Tue, 15 May 2018 15:39:53 GMT /slideshow/challenges-in-implementing-analytical-solution-97178661/97178661 ltwalt@slideshare.net(ltwalt) Challenges in Implementing Analytical Solution ltwalt We have all attended presentations either telling how great an analytical solution performed or how to successfully implement a solution or technique. It isn't a surprise to seasoned analytical professionals that most analytical projects are not successfully implemented. Unfortunately, due to selection bias, these projects are seldom presented. Medicine has a long history of using morbidity and mortality briefs to learn and advance the profession. These briefs share stories on negative outcomes and the events and decisions that led to those outcomes. This presentation uses the morbidity and mortality model and will take examples from analysis performed from the desert of Iraq, to the South China Sea, to the ice of the St. Louis Blue's Scottrade Center hockey rink to share negative outcomes and the lessons to be learned. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/rta-implementinganaltyics-180515153953-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> We have all attended presentations either telling how great an analytical solution performed or how to successfully implement a solution or technique. It isn&#39;t a surprise to seasoned analytical professionals that most analytical projects are not successfully implemented. Unfortunately, due to selection bias, these projects are seldom presented. Medicine has a long history of using morbidity and mortality briefs to learn and advance the profession. These briefs share stories on negative outcomes and the events and decisions that led to those outcomes. This presentation uses the morbidity and mortality model and will take examples from analysis performed from the desert of Iraq, to the South China Sea, to the ice of the St. Louis Blue&#39;s Scottrade Center hockey rink to share negative outcomes and the lessons to be learned.
Challenges in Implementing Analytical Solution from Walt DeGrange
]]> 80 6 https://cdn.slidesharecdn.com/ss_thumbnails/rta-implementinganaltyics-180515153953-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Day in the Life Analytics Professional /slideshow/day-in-the-life-analytics-professional/73146776 dayinthelife-analyticsprofessional-170314194120
This brief is an overview of a typical day in the life of an Analytics Professional. Also, covers the challenges and skills that are often overlooked in the industry. This was presented at the 2017 UNCW Cameron School of Business - Business Week and the 2018 RTA Analytics Forward Conference.]]>
This brief is an overview of a typical day in the life of an Analytics Professional. Also, covers the challenges and skills that are often overlooked in the industry. This was presented at the 2017 UNCW Cameron School of Business - Business Week and the 2018 RTA Analytics Forward Conference.]]> Tue, 14 Mar 2017 19:41:20 GMT /slideshow/day-in-the-life-analytics-professional/73146776 ltwalt@slideshare.net(ltwalt) Day in the Life Analytics Professional ltwalt This brief is an overview of a typical day in the life of an Analytics Professional. Also, covers the challenges and skills that are often overlooked in the industry. This was presented at the 2017 UNCW Cameron School of Business - Business Week and the 2018 RTA Analytics Forward Conference. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dayinthelife-analyticsprofessional-170314194120-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This brief is an overview of a typical day in the life of an Analytics Professional. Also, covers the challenges and skills that are often overlooked in the industry. This was presented at the 2017 UNCW Cameron School of Business - Business Week and the 2018 RTA Analytics Forward Conference.
Day in the Life Analytics Professional from Walt DeGrange
]]> 263 5 https://cdn.slidesharecdn.com/ss_thumbnails/dayinthelife-analyticsprofessional-170314194120-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 160128 RTA Meetup.com Sports Analytics SIG Brief /slideshow/160128-rta-meetupcom-sports-analytics-sig-brief/57624071 160128-rtameetupsportsanalyticssigbrief-160128212321
Presentation for the Sports Analytics Research Triangle Analytics Special Interest Group kick-off meeting held on Thursday, January 28, 2016. ]]>
Presentation for the Sports Analytics Research Triangle Analytics Special Interest Group kick-off meeting held on Thursday, January 28, 2016. ]]> Thu, 28 Jan 2016 21:23:21 GMT /slideshow/160128-rta-meetupcom-sports-analytics-sig-brief/57624071 ltwalt@slideshare.net(ltwalt) 160128 RTA Meetup.com Sports Analytics SIG Brief ltwalt Presentation for the Sports Analytics Research Triangle Analytics Special Interest Group kick-off meeting held on Thursday, January 28, 2016. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/160128-rtameetupsportsanalyticssigbrief-160128212321-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation for the Sports Analytics Research Triangle Analytics Special Interest Group kick-off meeting held on Thursday, January 28, 2016.
160128 RTA Meetup.com Sports Analytics SIG Brief from Walt DeGrange
]]> 239 8 https://cdn.slidesharecdn.com/ss_thumbnails/160128-rtameetupsportsanalyticssigbrief-160128212321-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Replenishment at Sea Planner (RASP) Implementation Brief 2012 MORS Symposium /slideshow/rasp-implementation-brief-2012-mors-symposium/13152500 raspimplementationbrief2012morssymposium-120531144629-phpapp02
We have all been there. Spend months developing the perfect optimal scheduling model by defining the problem, collecting the data, refining the model, enhancing the user interface and including customer feedback and then finally deploying the model. After all this work the customer does not use the model and reverts back to legacy practices. What went wrong? This brief uses a recent Naval Postgraduate School / Military Sealift Command project (Replenishment at Sea Planner, RASP) as an example. In development for the past two years, the RASP model optimally schedules Combat Logistics Force (CLF) ships to replenish customer ships considering time and distance, customer commodity levels, and CLF fuel usage. Using this example, the brief walks through the pitfalls and possible solutions to the two step innovation process; invention and adoption. The invention side covers techniques to accelerate the development and the adoption solutions cover the range of soft-skills and relationship building that are required for integration and sustainment of a new practice. ]]>
We have all been there. Spend months developing the perfect optimal scheduling model by defining the problem, collecting the data, refining the model, enhancing the user interface and including customer feedback and then finally deploying the model. After all this work the customer does not use the model and reverts back to legacy practices. What went wrong? This brief uses a recent Naval Postgraduate School / Military Sealift Command project (Replenishment at Sea Planner, RASP) as an example. In development for the past two years, the RASP model optimally schedules Combat Logistics Force (CLF) ships to replenish customer ships considering time and distance, customer commodity levels, and CLF fuel usage. Using this example, the brief walks through the pitfalls and possible solutions to the two step innovation process; invention and adoption. The invention side covers techniques to accelerate the development and the adoption solutions cover the range of soft-skills and relationship building that are required for integration and sustainment of a new practice. ]]> Thu, 31 May 2012 14:46:27 GMT /slideshow/rasp-implementation-brief-2012-mors-symposium/13152500 ltwalt@slideshare.net(ltwalt) Replenishment at Sea Planner (RASP) Implementation Brief 2012 MORS Symposium ltwalt We have all been there. Spend months developing the perfect optimal scheduling model by defining the problem, collecting the data, refining the model, enhancing the user interface and including customer feedback and then finally deploying the model. After all this work the customer does not use the model and reverts back to legacy practices. What went wrong? This brief uses a recent Naval Postgraduate School / Military Sealift Command project (Replenishment at Sea Planner, RASP) as an example. In development for the past two years, the RASP model optimally schedules Combat Logistics Force (CLF) ships to replenish customer ships considering time and distance, customer commodity levels, and CLF fuel usage. Using this example, the brief walks through the pitfalls and possible solutions to the two step innovation process; invention and adoption. The invention side covers techniques to accelerate the development and the adoption solutions cover the range of soft-skills and relationship building that are required for integration and sustainment of a new practice. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/raspimplementationbrief2012morssymposium-120531144629-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> We have all been there. Spend months developing the perfect optimal scheduling model by defining the problem, collecting the data, refining the model, enhancing the user interface and including customer feedback and then finally deploying the model. After all this work the customer does not use the model and reverts back to legacy practices. What went wrong? This brief uses a recent Naval Postgraduate School / Military Sealift Command project (Replenishment at Sea Planner, RASP) as an example. In development for the past two years, the RASP model optimally schedules Combat Logistics Force (CLF) ships to replenish customer ships considering time and distance, customer commodity levels, and CLF fuel usage. Using this example, the brief walks through the pitfalls and possible solutions to the two step innovation process; invention and adoption. The invention side covers techniques to accelerate the development and the adoption solutions cover the range of soft-skills and relationship building that are required for integration and sustainment of a new practice.
Replenishment at Sea Planner (RASP) Implementation Brief 2012 MORS Symposium from Walt DeGrange
]]> 650 4 https://cdn.slidesharecdn.com/ss_thumbnails/raspimplementationbrief2012morssymposium-120531144629-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-ltwalt-48x48.jpg?cb=1526397072 Operations Research Analyst with experience in sports analytics, ERP implementation, supply network optimization, logistics planning and integrated logistics support. https://www.linkedin.com/in/waltdegrange https://cdn.slidesharecdn.com/ss_thumbnails/rta-implementinganaltyics-180515153953-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/challenges-in-implementing-analytical-solution-97178661/97178661 Challenges in Implemen... https://cdn.slidesharecdn.com/ss_thumbnails/dayinthelife-analyticsprofessional-170314194120-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/day-in-the-life-analytics-professional/73146776 Day in the Life Analyt... https://cdn.slidesharecdn.com/ss_thumbnails/160128-rtameetupsportsanalyticssigbrief-160128212321-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/160128-rta-meetupcom-sports-analytics-sig-brief/57624071 160128 RTA Meetup.co...