Personalized Business Intelligence

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Personalized

Business Intelligence

arcplanet, 2011-03-31

Claus Nagler

Head of Business Intelligence Solutions & Services

Bayer Business Services GmbH

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Agenda

Introduction

Bayer – Company Profile

Personalized Business Intelligence

Arcplan Engage

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BBS-IBS-BI&DM • Claus Nagler • March 2011

Personalized Business Intelligence @ arcplanet 2011 • Page 3

“Efficient communication is a key to progress in all fields

of human endeavor. It has become evident in recent years

that present communication methods are totally inadequate

for future requirements. Information is now being

generated and utilized at an ever-increasing rate because

of the accelerated pace and scope of human activities … .

… Undoubtedly the most formidable communications problem is the

sheer bulk of information that has to be dealt with.”

Business Intelligence

- An ever lasting Challenge?

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Business Intelligence (BI) refers to the systematic use of information

within the company and the outside world (marketplace)

for decisions.

• Increasingly detailed information

• Increasingly comprehensive information

• increasingly updated information

• better automated decision support.

Business needs:

Business Intelligence

- Business needs Information not Data

Fast and secure decisions are

significant contribution to

generate market advantages.

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Agenda

Introduction

Bayer – Company Profile

Personalized Business Intelligence

Arcplan Engage

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2

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Bayer Business Services in the Bayer Group

Service areas

Business areas

Bayer AG

Bayer

HealthCare

Bayer

CropSciene

Bayer

Material-

Science

Currenta

Bayer Technology

Services

Bayer Business

Services

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Engage. Enable. Empower.

Bayer Business Services is the

Bayer Group’s global competence

center for IT and business services.

5,582 employees*

EUR 995.5 million in sales*

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Agenda

Introduction

Bayer – Company Profile

Personalized Business Intelligence

Arcplan Engage

1

2

3

4

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“One of the most crucial problems in communication is that of

channeling a given item of information to those who need to know it.

Present methods of accomplishing this are inadequate and the general

practice is to disseminate information rather broadly to be on the safe side.

… An objective of the Business Intelligence System is to identify related

interests by use of profiles of action points.”

**H.P. Luhn A Business Intelligence System, IBM Journal * October 1958**

Current challenges in BI – the end user’s view

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Typically the needed information has to be

retrieved

More than one source is available and each source is

complex and packed with information like a library

Current challenges in BI – the end user’s view

Perspectives of a user looking for information:

Which report document is the right one

and where can I find it?

Which source is the best for the information needed?

Anything new in the system?

What are the others working with?

Are there other documents carrying information

that should also be considered?

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Hype and reality

 Social media in the enterprise (E2.0)

 Wikis



Agile xxx (Enterprise, BI, …)

 Collaborative Decision Making



„Find“ instead of „Search“

 Web 2.0 and BI

 Web based BI FrontEnds

 MashUps

 Gadgets / Widgets

 Ad hoc reporting



Current interfaces are not personalized

and do not analyze user behavior



Reports are generated by power-users

and may never be used



no rating possibility by end-user



Users spend much time finding relevant

reports due to their large number



Missing exchange of expertise

among end-users



Report search function is insufficient /

nonexistent



Providing users with adequate reports is

time-consuming and expensive

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Innovation Project

Personalized Business Intelligence

Idea: “Business Information Store”

User Interface for reports structured like an internet shop

Product = Report or Information

The innovation is the special combination of functionalities:

1. Recommendation of reports based on Data-Mining methods (like Amazon)

2. Rating functionality of reports

3. Search engine for reports (content specific, like Google)

4. Collaboration

amongst users (Annotations, shared working, …)

5. Connection of external feeds or links & favorites in User Interface

6. Realization as a framework technology

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Personalized Business Intelligence

Modules

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Search – Module :: Concept

Three ways to find information

Classical search:

Google-like search within meta data of reports & Sharepoints

 Search filter by content, time, report type

Visual search: Browsing in a tag cloud with predefined search terms

 People who do not know what to search for, should also be able

to find results

Semantic search: The key element is that the application in context

will try to determine the meaning of the text or other data and then

create connections for the user

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Rating Module :: Concept

 Rating possibility of end-users for information found in the shop

– plus: Rating of ratings

 Tracking of user clicking behavior & usage statistics (average viewing time,

navigation time)

 Evaluation of ratings

– input to personalization

 recommendation of similar rated items ignoring disliked items

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Recommendation Module :: Concept

 Application of two recommendation concepts:

– 1. Collaborative (social filtering): User-similarity

evaluating user profiles and/or similar rated items

“Similar users also viewed following report”

– 2. Content based: Co-occurence of execution of

reports conclude in recommendations for new ones

“Users who viewed this report, also viewed”

 Open issues: What is being tracked in BI (execution,

navigation etc.) and can be used for recommendation?

– Is it possible to load this data into a recommendation

engine (manual or automated)?

– Data privacy

Controller Accounting Controller Accounting

1.

2.

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Recommendation Module :: Concept

 Recommendations have to be helpful, otherwise user acceptance is never gained

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Recommendation Module :: Realization

 A recommender system for

E-Commerce is installed and configured

on test system

 SAP BW Query usage statistics (who

used which query) have been imported

into recommender system and

content-based rules generated

 Also possible to evaluate usage

statistics (top queries, top users etc.)

 Next step: collaborative rule generation

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Social Networking Module :: Concept

Concept:

 Connection of PBI to MySite platform

(based on Sharepoint 2010 technology)

 Basic information about all users is

available

– Personal information has to be

published by user in profile

– Can be accessed through open web

service interface

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Agenda

Introduction

Bayer – Company Profile

Personalized Business Intelligence

Arcplan Engage

1

2

3

4

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Personalized Business Intelligence

Next steps

 Linking Recommender Engine to arcplan Engage

 Loading further BW query information into Sharepoint

 Linking User information on Sharepoint MySite to Personalized BI

 Define concept for implementation of ranking

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Claus Nagler

Head of Business Intelligence Solutions & Services

Bayer Business Services GmbH

E-Mail: [email protected]

Bayer Business Services GmbH

Customer & Sales Service Center

51368 Leverkusen, Germany

E-mail: [email protected]

Internet: www.BayerBBS.com