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BEGIN:VEVENT
DESCRIPTION:Time: \;15:00 - 16:30 UK Time\nPresenters: \;Dr Joachim
Schwarz\, PhD Todd Sanger and Richard Pugh\n\nPresentations:\n1. 'Looking
over the Fence' by Richard Pugh - Click here \;to view the slides\n2.
'The Use of Predictive Modelling in Customer Relationship Management' by
Joachim Schwarz - Click here \;to view the slides\n3. 'Moving from R&a
mp\;D to Sales and Marketing: the business analytics experience of a stati
stician at Lilly' by Todd Sanger - Click here \;to view the slides\n\n
Dr Joachim Schwarz\n\nAbstract\nPredictive Modelling in the field of Custo
mer Relationship Management\nThe webinar focusses on one main problem of e
very customer relationship management department: How to identify those cu
stomers\, which are more likely to e.g. terminate their customer relations
hip 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 app
roach and\, last but not least\, its specific potential to generate or to
save money. \;\n\nAbout the Presenter\n\nDr Joachim Schwarz\, studied
mathematics at the Georg August University in Gö\;ttingen and at Trini
ty College in Dublin. He did his PhD in business administration at the pri
vate university of Witten / Herdecke\, and afterwards\, he has more than n
ine 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 bu
siness mathematics and statistics at the FOM university of applied science
s in Bonn.\n\n\n\nPhD Todd Sanger\n\nAbstract\n\nMoving from R&\;D to S
ales and Marketing: the business analytics experience of a statistician at
Lilly\nTypically\, pharmaceutical companies invest more money on sales an
d 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 Marketi
ng. \; This talk will describe the types of issues we encounter and th
e statistical techniques we use to tackle these issues.\nAbout the Present
er\n\nResearch Fellow\, Advanced Analytics at Eli Lilly and Company\n\n\n\
n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nRichard Pugh\n\nAbstract\n\nLooking over th
e fence: What does Data Science mean outside of life sciences and what can
we learn?\nThe last 10 years have seen significant growth in companies in
vesting in Big Data\, Data Science\, Machine Learning and AI. \; The k
ey 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 adopt
ion of data-driven approaches can vary significantly. \;\nThis present
ation will look at core concepts of data science\, such as the 3 Vs of dat
a\, and how different industries have looked to implement these concepts.&
nbsp\; In particular\, we will look at possible opportunities for the phar
maceutical sector to adapt successful approaches from other industries.\nA
bout the Presenter\n\nRichard 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-fo
unded Mango Solutions to focus on the application of analytics to solve bu
siness challenges using technologies such as SAS\, S-PLUS and R. \; Ri
chard is heavily involved in the R community\, co-authoring the book &ldqu
o\;R in 24 Hours&rdquo\;\, and was the first President of the R Consortium
. \; Richard is an active member of the committee of the RSS Data Scie
nce Section. \; Today\, Richard spends much of his time advising clien
ts across a variety of industries on data-driven approaches\, and is a reg
ular speaker at analytic conferences.\n\n\n\n \n \n R
egistration\n \n \n PSI Member\n Free&
nbsp\;\n \n \n Non-member\n £\;20
(plus VAT) \; \;\n \n \n\n\nTo access the recording\, p
lease visit the Video-on-Demand Library.\n\n\n\n\n\n\n\n\n\n \n
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ber\n Free\n \n \n Non-Member\n
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DTEND:20180322T163000Z
DTSTAMP:20240328T161339Z
DTSTART:20180322T150000Z
LOCATION:
SEQUENCE:0
SUMMARY:PSI Webinar: What’s the big deal with big data and will it have a b
ig impact on me?
UID:RFCALITEM638472392192423966
X-ALT-DESC;FMTTYPE=text/html:Time: \;15:00 - 16:30 UK
Time Moving from R&\;D to Sales
and Marketing: the business analytics experience of a statistician at Lil
ly
\nPresenters: \;Dr Joachim Schwarz\, PhD To
dd Sanger and Richard Pugh
\n
\nPresentations:<
br />\n1. 'Looking over the Fence' by Richard Pugh - Click here \;to view the slides
\n2. 'The Use of Predictive Modelling in Customer Relationship Managemen
t' by Joachim Schwarz - Click here \;to view the slides
\n3. 'Moving from R&\
;D to Sales and Marketing: the business analytics experience of a statisti
cian at Lilly' by Todd Sanger - Click here \;to view the slides
\n
\nDr
Joachim Schwarz
\n
\nAbstract
\n
Predictive Modelling in the field of Customer Relationship Man
agement
\nThe webinar focusses on one main problem of e
very customer relationship management department: How to identify those cu
stomers\, which are more likely to e.g. terminate their customer relations
hip 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 app
roach and\, last but not least\, its specific potential to generate or to
save money. \;
\n
\nAbout the Prese
nter
\n
\nDr Joachim
Schwarz\, studied mathematics at the Georg August University in Gö\;tt
ingen and at Trinity College in Dublin. He did his PhD in business adminis
tration 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 fo
cus on data mining and predictive modelling. Since winter term 2013\, he i
s professor for business mathematics and statistics at the FOM university
of applied sciences in Bonn.
\n
\n
\n
\nPhD To
dd Sanger
\n
\nAbstract
\n\n
\nTypically\,
pharmaceutical companies invest more money on sales and marketing than the
y do on R&\;D\, yet very few statisticians work to support sales and ma
rketing organizations. \; At Lilly\, we created a group of statisticia
ns to support analytical problems in Sales and Marketing. \; This talk
will describe the types of issues we encounter and the statistical techni
ques we use to tackle these issues.
\n
\n
span>Research Fellow\, Advanced Analytics at Eli Lilly and Company
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\nAbstract
\n
\n
Looking over the fence: What does Data Science mean outs
ide of life sciences and what can we learn?
\nThe last 10 years
have seen significant growth in companies investing in Big Data\, Data Sci
ence\, Machine Learning and AI. \; The key driver for organisations in
vesting in these initiatives is to generate insight from data that can be
used to drive better decision making. \; However\, as each industry ha
s 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 i ndustries have looked to implement these concepts. \; In particular\, we will look at possible opportunities for the pharmaceutical sector to ad apt successful approaches from other industries.
\nAbout the
Presenter
\n
\n
R egistration | \n|
PSI Membe r | \nFree \;< /td>\n |
Non-member | \n£\;20 (plus VAT)&n bsp\; \; | \n
&nbs p\; | \n \; | \n
 \; | \n \; | \n
 \; | \n \; | \n
Re gistration | \n|
PSI Member< /td>\n | Free | \n
Non-Member | \n