[fg-arc] IEEE EDOC conference 2016 - Keynote speakers announced!

[EDOC conference 2016]

We apologize if you receive this message more than once.

---
We are happy to inform you that the program for the keynotes is 
available at the conference web site: http://tinyurl.com/edoc16-keynotes

More information:
============================================================
IEEE EDOC 2016 - The 20th IEEE International EDOC Conference
============================================================

EDOC 2016 - Vienna, Austria
September 05-09, 2016
http://edoc2016.univie.ac.at/
http://twitter.com/ieee_edoc

IEEE EDOC 2016 is the twentieth conference in a series that provides the 
key forum for researchers and practitioners in the field of enterprise 
computing. EDOC conferences address the full range of models, 
methodologies, and engineering technologies contributing to intra- and 
inter-enterprise application systems. Since 1997, EDOC has brought 
together leading computer scientists, IT decision makers, enterprise 
architects, solution designers, and practitioners to discuss enterprise 
computing challenges, models and solutions from the perspectives of 
academia, industry, and government. The EDOC conference series 
emphasizes a holistic view on enterprise applications engineering and 
management, fostering integrated approaches that address and relate 
business models, business processes, people and technology.

EDOC 2016 welcomes high quality scientific submissions as well as 
experience papers on enterprise computing from industry. The main theme 
of EDOC 2016 is ”Enabling innovative business models in the enterprise 
of the future” and seeks to explore innovative approaches synthesizing 
concepts of (1) data science, (2) enterprise computing and (3) social 
computing.


Keynotes
======


    Technologies for Happiness - and their Impact on Enterprise
    Application Architectures

*Fabio Casati*

University of Trento


      Abstract

Technology has profoundly changed all aspects of our personal and 
professional lives, and is continuing to do so at an ever increasing 
pace. Most of these changes help us be more efficient, effective and 
flexible. What is still unclear is whether this change has made us 
happier, that is, if it has improved our quality of life or whether it 
has made it more hectic and stressful.Pursuing happiness is considered a 
goal worthy in its own right, and happiness has a wide range of "side" 
benefits as well: happier individuals are healthier, more social, more 
giving, more collaborative, and so on. It is therefore not surprising 
that research on happiness has intensified in recent years, with the 
rise of scientific fields such as positive psychology that studies how 
we can live more fulfilling lives. This talk is about positive 
technology, that is, technology that can directly contribute to people's 
happiness. I'll start by presenting what science today considers as 
important determinants of happiness, both as adults and as we age, and 
how it can be "measured". We'll then discuss how technology can affect 
these determinants and what are the potential and the key ingredients of 
positive technology as a science. Finally, we'll assess the impact 
positive technologies can have on enterprises, by enabling employees to 
become more effective at what they do and more capable of living in a 
constantly and sometimes "disruptively" changing environment.


      Speakers's Bio

Fabio Casati is professor of social informatics and senator at the 
University of Trento. Until 2006, he was technical lead for the research 
program on business process intelligence in Hewlett-Packard USA, where 
he contributed to several HP commercial products in the area of web 
services and business process management. He then moved to academia, 
where he started a research line on technologies for happiness, 
delivering results that have a direct impact on people’s life. The 
research results are available atlifeparticipation.org 
<http://lifeparticipation.org/>.

------------------------------------------------------------------------


  Enterprise Computing in the Context of Networked Business Paradigms

*Paul Grefen*

Eindhoven University of Technology


      Abstract

In recent years, we have seen the emergence of new business paradigms 
that highlight the importance of business network thinking. These 
business paradigms stress the idea that business thinking should not be 
based primarily on an intra-organizational focus, but rather on the 
relationships with business organizations, such as collaborators or 
customers. For example, the service-dominant paradigm is centered at 
networked co-creation of value for customers through services. The 
recent outcome economy paradigm revolves around facilitating measurable 
business results for customers. Combining these paradigms with the 
concept of agile business leads to dynamic business networks as a first 
order citizen in business engineering. These developments have a strong 
impact on the domain of enterprise computing: on the one hand, it 
requires an outside-in engineering to complement the traditional 
inside-out approach; on the other hand, it requires a decoupling of 
strategic resource-based design from tactic value-based design. In this 
presentation, networked business paradigms are illustrated and their 
impact on enterprise computing is explored.


      Speakers's Bio

Paul Grefen is a full professor in the School of Industrial Engineering 
at Eindhoven University of Technology since 2003. He chaired the 
Information Systems subdepartment from 2006 to 2014. Currently, he is 
the research director of the School. He received his Ph.D. in 1992 from 
the University of Twente and held assistant and associate professor 
positions in the Computer Science Department. He was a visiting 
researcher at Stanford University in 1994. He has been involved in 
various European research projects as well as various projects within 
the Netherlands. He is an editor of the International Journal of 
Cooperative Information Systems. He is an editor and author of the books 
on the WIDE and CrossWork projects, and has authored books on workflow 
management, electronic business and service-dominant business 
engineering. He is a member of the Executive Board of the European 
Supply Chain Forum. His current research covers architectural design of 
business information systems, inter-organizational business process 
management, and service-oriented business design and support. He teaches 
at the MSc, PDEng and PhD levels at TU/e and at the executive level for 
TIAS business school.

------------------------------------------------------------------------


  The Role of Big Data and Data Science within Digitization at Allianz Group

*Andreas Braun*

Global Data & Analytics at Allianz SE


      Abstract

By Big Data Analytics we understand new technologies and methods that go 
beyond how we previously handled data and analytics. One the data side, 
for instance, extremely large data sets can be stored and processed, 
even real-time, and at reasonable cost. This is largely applied also to 
unstructured data, for example internet and clickstreams, bank and 
credit card transactions, and GPS/ geospatial data. On the analytical 
side, methods are no longer limited to on hard-coded (business) rules or 
statistics, but leverage artificial intelligence (AI) and particularly 
Machine Learning (ML). Big Data platforms recognize recurring patterns 
and act context-aware to transform the data mentioned before into more 
meaningful actionable insights. In the aforementioned scenarios ML not 
only typically delivers better results than statistical approaches or 
rule-based systems in particular, they can also be implemented 
dynamically and adaptive; they are intelligent in a way. As a further 
key element, ML allows predictions based on what has been learnt so 
far—hence the term predictive analytics. The application of Big Data 
today is manifold and of growing importance. However, we believe that 
Big Data's most tangible and immediate impact in the domain of business 
is in customer and consumer analytics. This area has been summarized as 
the Digital Consumer Journey Analytics. Such journeys are constructed 
from people's movement and navigational patterns in both the virtual and 
physical world. While individual data points are at first not very 
expressive nor rich of content, and are seen for themselves also 
anonymous in a way, the picture created by continuous collection of 
ubiquitous data and their history allows to unveil almost any identity 
profile [7]. This is typically used for profiling, predictions, and 
segmentations. For example, web pathways can be used to derive a 
socio-economic customer profile to predict interest, purchasing intent, 
or churn. Comprehensive consumer profiles can be cataloged and used for 
marketing purposes. The creation of such insight became only possible 
through the use of Big Data technologies and analytics: first of all, 
because of the sheer amount of data and their history being used; 
secondly, because online ML allows for the continuous improvement and 
fine tuning of initial profiles and models so that they increasingly 
correlate ever better with reality and the real life situation of an 
actual person—eventually down to the segment of one. The broader context 
beyond a single individual, on the other side, allows for various 
marketing relevant predictions: What do people within a category 
typically buy? What are they interested to buy next? When do they go on 
holiday, and where to? What do they spend on the location they have 
travelled to? How to get in touch and address them? etc. The 
entrepreneurial and economic value of such analytics is beyond doubt and 
proven to be immense for businesses. Conveniently enough, various 
different use cases sit on the same data eco system. For example, while 
fraud analytics saves two-digit millions in fraudulent claims, the same 
data is used to “white-flag” uncritical claims to pay customers faster 
and identify unhappy clients. Retention models reduce churn by more than 
20%—compared to the statistical models used previously. Meanwhile, the 
same data are used to improve the conversion rate in direct insurance by 
almost 25%. We argue here that the ability to improve the customer 
experience and innovate the customer journey is the most important 
change on the new data wave. Besides “white-flagging” claims to pay 
customers faster, web-pages can be arranged accordingly to customer 
interest in real-time to optimize usability and minimize navigation 
effort for the customer as customer-relevant information is prioritized. 
Big Data Analytics is used to make better and more relevant offers to 
customers, or to refrain offers in the wrong moment. Customers are 
understood increasingly well so that a customer need can be identified 
in real-time: rebates can be added to product-bundles for specifically 
price-sensitive customer profiles. The customer experience is 
continuously measured and fine-tuned in the background. Customers, in 
turn, will also use technology to protect themselves from unwanted 
advertisements and direct marketing. In the future products and services 
not only will be developed using Big data but also tailored to a 
customer's specific need. Staying in the relevant set of customers will 
be of utmost importance. Hence, we believe the notion of marketing will 
change and broaden and continuously blend into e.g., product service 
design and improvement. While information, IT and Cyber Security is 
discussed since decades the new Big Data-driven challenge will be data 
privacy and ethics. Basically, this means that legacy approached like 
anonymization and personally identifiable information or PII are not 
sufficient any more. The task for marketing hence is to make products 
relevant and trusted in the digital age/ In this paper, we illustrate a 
few successful Big Data Use Cases in Consumer Analytics and discuss 
Privacy by Design as an approach to be trusted.


      Speakers's Bio

Andreas Braun graduated from TU-Munich in Computer Science and 
theoretical medicine and pursued an Accenture-funded doctorate focused 
on software architectures for artificial intelligence. Today, Andreas 
heads up Global Data & Analytics at Allianz SE. In this role, he is 
responsible for the Global Data & Analytics Competence Center at group 
level. This spans big data use cases, governance, data sciences and 
advanced analytics, and the respective technology and architecture. 
Previously, Andreas was Global Head, Business Applications and 
Technology in GfK SE, Germany’s largest market research firm, where he 
was responsible for all customer-facing business software development 
and new technologies, including e.g., Big Data, Hadoop etc. Earlier in 
his career, Andreas was overseeing operations, data analytics, and off 
and near-shoring at TNS Infratest in Germany and Central Eastern Europe; 
in the 1990s, Andreas co-founded a company focusing on image processing, 
which he sold in 2000.


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.uni-paderborn.de/pipermail/fg-arc/attachments/20160307/97f82e48/attachment.html>