PSI Webinar: What’s the big deal with big data and will it have a big impact on me?

Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh

Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides

Dr Joachim Schwarz

Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour.  A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money. 

About the Presenter

Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.



PhD Todd Sanger

Abstract

Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations.  At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing.  This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.

Looking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI.  The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making.  However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly. 

This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts.  In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.

About the Presenter

Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry.  Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry.  Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product.  In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R.  Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium.  Richard is an active member of the committee of the RSS Data Science Section.  Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.