Advancing the Data-Driven Organization
Thursday, September 23 & Friday, September 24, 2021
Virtual Event
We are now more than ten years into the revolution of big data, business analytics, and increasingly, the application of Artificial Intelligence. The emphasis of this year's Business Analytics Innovation Summit is on analytics in action! Even if you do not think your organization is that far along, you are probably thinking seriously about impending changes! More than half of senior executives in a 2020 Deloitte survey thought that AI would transform their industries within at least 1-3 years, and three-quarters within 3-5 years. Our speakers will present case studies with real examples of organizations that are effectively leveraging analytics and AI tools to bring about changes in business processes and achieve data-driven benefits!
First up on Thursday is Chris Deniziak, from Clear Process Solutions, who will examine how Heinen's Fine Foods has launched a comprehensive effort to bring data into a wide variety of decisions, with top-down and widespread support. The case study examines bridging the gap between square zero and square one, which can be the most difficult step to take.
Our remaining two speakers on Thursday will delve into key elements to support the application of machine learning to business decisions. Chris McPherson of 1848 Ventures will speak about the critical importance of designing the acquisition of rich data that can lead to truly meaningful outcomes from models. This case study involves a novel approach for scheduling labor at restaurants. Pat Thontirawong of Data Revenue GmbH will explain his firm's solutions for managing numerous models using their implementation at an automaker as a case study. Both “digital representation design” and “MLOps” are crucial elements in large scale model deployment.
On Friday we present two longer case studies, both of which integrate a variety of analytical approaches to create comprehensive solutions to critical business problems. Mark Wells of Optiyol, LLC will speak about Beymen, a high-end retailer in Turkey that had to pivot to an e-commerce approach during the pandemic. It is using machine learning, optimization, and big data approaches from analytics firm Optiyol to deploy its own delivery force with optimal delivery routes and much more. Allison Rajakumar will speak about a way of life at Lubrizol – a suite of tools and everything that goes with them -- that has transformed their product development functions.
Program
Thursday, September 23, 2021
11:30 am - 11:35 am
Program Welcome
Abdou Ayoub, Managing Director – Paragon Shift
11:35 am - 12:00 pm
Step Back to Step Forward: The Journey to Data Informed Decision Making
Chris Deniziak, Data Strategist/ Data Architect, Clear Process Solutions
12:00 pm - 12:30 pm
Digital Exhaust – The Sludge Holding Back Your Analytics Engine
Chris McPherson, Venture Builder, Data Science Strategy, 1848 Ventures
12:30 pm - 1:00 pm
MLOps: Automate your Machine Learning Pipeline without a Headache
Pat Thontirawong, Senior Machine Learning Engineer, Data Revenue GmbH
1:00 pm - 1:15 pm
Closing Remarks
Friday, September 24, 2021
11:30 am - 11:35 am
Program Welcome
Abdou Ayoub, Managing Director – Paragon Shift
11:35 am - 12:15 pm
A Pandemic Lesson for Normal Operations: Combining Optimization and Machine Learning Algorithms to Improve Delivery Performance at Lower Cost
Mark Wells, Vice President for Customer Innovation and Value, Optiyol Ozan Gözbaşı, Co–Founder and CEO, Optiyol
12:15 pm - 1:00 pm
A Data Analytics Journey in Specialty Chemicals at Lubrizol
Allison Rajakumar, Sr. Manager, Statistics & Data Analytics, Lubrizol
1:00pm - 1:15 pm
Closing Remarks
Presentations
Chris Deniziak, Data Strategist/ Data Architect, Clear Process Solutions
Step Back to Step Forward: The Journey to Data Informed Decision Making
Heinen's Grocery Store, like many other organizations, was experiencing challenges with disparate data sources, lack of alignment on key KPIs, lack of speed making decisions and making decisions that weren't data informed. Through a rigorous interview process, CPS uncovered key organization themes that would enable the creation of a robust digital transformation roadmap. By focusing on the foundation of data and analytics, Heinen's is laying the groundwork for data-informed decision making and continued success as a 4th generation family business.
Chris Deniziak leads the data and analytics practice at Clear Process Solutions. Chris has more than 10 years of experience in the data and analytics field, with the majority being spent in consulting. He has worked with many clients in a vast number of industries ranging from manufacturing and consumer packaged goods to energy. Chris is passionate about ensuring companies are getting the right solution by starting with a strategy in mind before trying to implement any type of data and analytics solutions. By doing this he can deliver the solution his clients need rather than just appeasing their initial idea. Chris has a bachelor's degree in Management Information Systems from The Pennsylvania State University and a master's degree in Competitive Intelligence Systems from Robert Morris University.
Chris McPherson, Venture Builder, Data Science Strategy, 1848 Ventures
Digital Exhaust – The Sludge Holding Back Your Analytics Engine
If data truly is the new oil,
then many analytics and AI initiatives are given 'sludge' in the form of 'digital exhaust, ' data collected in service of transactional processes and repurposed. This supply-side approach to data often fails to provide a meaningful digital representation of the phenomena your analytics team leverages in automating, predicting, prescribing, or understanding. Through the lens of LineUp.ai, a business built by 1848 Ventures, Chris makes a case for a demand-side data strategy that puts business' decisions and their objectives at the center of a design process called the Digital Representation Design.
Chris is passionate about developing new products with learning algorithms at their core, intrapreneurially and entrepreneurially. At 1848 Ventures, Chris focuses on building ventures that leverage data to support the decisions small businesses make under pronounced uncertainty and risk. He enjoys camping with his wife and two daughters, loves to drive, and is currently developing a clutter detecting computer vision system that controls access to the treat jar. Chris has a bachelor's degree in Information Systems Management from the University of Â鶹ÊÓƵAPKand a master's degree in Information and Data Science from the University of California Berkeley.
Pat Thontirawong, Senior Machine Learning Engineer, Data Revenue GmbH
MLOps: Automate your Machine Learning Pipeline without a Headache
Deploying a machine learning model and its data processing pipeline are not easy. The talk will cover how data scientists can use MLOps to address the deployment problem. We will cover how to create an automated machine learning training and deployment pipeline and present a case study on how an automaker can integrate MLOps tools into their machine learning deployment.
Pat Thontirawong is a senior machine learning engineer at Data Revenue GmbH. He works with many data science teams in automakers, medical research, and energy trading companies to create end-to-end machine learning processes. He holds a Ph.D. in finance and a master's degree in software engineering. Pat believes that without a good development and deployment processes in place, machine learning algorithms alone cannot deliver values as promised.
Mark Wells, Vice President for Customer Innovation and Value, Optiyol
Ozan Gözbaşı, Co-Founder and CEO, Optiyol
A Pandemic Lesson for Normal Operations: Combining Optimization and Machine Learning Algorithms to Improve Delivery Performance at Lower Cost
For Beymen, a world-class player in Turkey's luxury retail sector, lockdowns
in response to the pandemic caused a decline in store visits, but with a surge in online sales. Traditionally, the company outsourced e-commerce deliveries to parcel delivery companies. This time, however, service levels deteriorated as all delivery companies struggled simultaneously with both an increase in demand and also a labor shortage. Beymen's commitment to delight its loyal customers led to the formation of its own delivery organization to reduce delivery lead times and improve visibility. Optimization, heuristics, and machine learning techniques were combined to forecast demand, right-size the fleet, allocate orders to vehicles, and determine the best delivery sequences, while tracking orders in real-time, leading to a 35% reduction in cost per delivery and a 40% decrease in lead times.
(Arnold) Mark Wells currently serves as Vice President for Customer Innovation and Value for Optiyol, LLC. Mark previously held positions as a Major Customer Executive at Blue Yonder (a Panasonic company), Director of Supply Chain Innovation at Incorta, and Vice President of Business Development at an advanced analytics cloud startup, as well as various roles across other firms, including IBM, SAP, Oracle, End-to-End Analytics, and SmartOps (acquired by SAP). Over his career, Mark has had the opportunity to consult with the management of leading global supply chains in the chemicals, medical devices, consumer goods, high tech, and retail industries. He has led projects in multiple areas of process improvement, network design, forecasting, inventory planning, order fulfillment and warehousing, cost-to-serve analysis, and more. Mark is the publisher and author of the Supply Chain Action blog. He holds an MBA from Drexel University.
Ozan Gözbaşı is Co-Founder and CEO of Optiyol, which builds solutions for route optimization and execution for last-mile and long-haul transportation. Prior to Optiyol, Ozan worked as an Algorithm Design Engineer at SmartOps (acquired by SAP) to develop enterprise-grade software for multi-stage inventory planning and optimization. He also served as a management consultant at a mobile telecommunications operator for sales channel optimization and at a large consumer durable goods manufacturer for pricing analytics. He led the Advanced Analytics and Operations Research team at P1M1 focusing on ATM operations for the banks. Ozan received his M.Sc. degree in Operations Research and Ph.D. degree in Industrial Engineering from Georgia Institute of Technology where his dissertation focused on Radiation Treatment Planning for Cancer Patients in collaboration with Emory University. He has more than 15 years of experience in algorithm design for large-scale optimization problems.
Allison Rajakumar, Sr. Manager, Statistics & Data Analytics, Lubrizol
A Data Analytics Journey in Specialty Chemicals at Lubrizol
At Lubrizol, data analytics has played an important role in facilitating product development and deployment for over two decades. This is the journey from our early data analytics approaches to the sophisticated integrated system in place today. This includes a discussion of the activities and processes required for maintaining a highly utilized system, which generates predictions for over 15,000 formulated materials monthly. In addition, this presentation will highlight current challenges and the plans for evolving our data analytics systems for the future.
Allison Rajakumar is a manager in the Statistics and Data Analytics department at Lubrizol. She has over 15 years of experience in data science as both a statistician and manager at Lubrizol. In her role, she is responsible for ensuring they have the right people, skills, and processes to deliver data analytics systems and statistical consulting services in order to improve efficiency and facilitate innovation across the business. She holds a bachelor's degree in Mathematics from Cleveland State University and a master's degree in Applied Statistics from The Ohio State University. Allison grew up in Northeast Ohio and currently lives there with her husband and their two sons.
Sponsorship Opportunities
Every sponsorship is 100% tax–deductible and will help provide scholarship funds to our deserving Analytics and Information Systems students.
Premier Sponsor, $5,000
- Companies recognized as "Premier Sponsor" throughout the event, on event website, and in all related media
- 30–second commercial spot to be played throughout event
- Opportunity to provide short welcome address to all event attendees
- Large logo featured prominently throughout event and on event website
- Company is verbally recognized through the event
- Medium logo included on emails sent to registrants
- Unlimited access to all sessions on September 23 & 24
Gold Sponsor, $2,500
- Sponsor a Session – prerecorded introduction of speaker and logo featured prominently before & after presentation
- Medium logo featured throughout the event and on event website
- Company is verbally recognized throughout the event
- Small logo included on emails sent to registrants
- Unlimited access to all sessions on September 23 & 24
Blue Sponsor, $1,000
- Unlimited Blue sponsorships available
- Small logo featured throughout the event and on event website
- Company is verbally recognized throughout the event
- Name included on the email sent to registrants
- Unlimited access to all sessions on September 23 & 24
To become a sponsor, please and select your sponsorship or contact Cynthia Sheeks, Director Development, at csheeks@uakron.edu or (330) 972–8641
Current Sponsors
Premier Sponsor
Gold Sponsor
Blue Sponsor
About CITA
The Center for Information Technologies and Analytics (CITA) is a multi–disciplinary Center within the College of Business. CITA was created in 2000 with the mission to teach students and develop faculty in the principles and practices of the related disciplines of Information Technology. CITA accomplishes its mission by providing scholarships, mentoring, internships & co-op opportunities to students in the information systems and business analytics disciplines, providing resources to conduct research to faculty, and conducting several outreach activities that promote IT and analytics among local companies.
CITA is made up of an advisory board of Information Technology leaders from the Northeast Ohio region and the College of Business faculty, staff and students. For further information, visit the Center for Information Technologies and Analytics (CITA) website.