Business Planning

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18 Νοε 2013 (πριν από 3 χρόνια και 8 μήνες)

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Queens University

Business Intelligence in the
real world


Gareth Diamond


www.pwc.com

PwC

Contents

1.
Recap on last week's lecture

2.
Key Messages

3.
Emerging trends in Business Intelligence

4.
How clients are implementing BI to realise value

5.
Hype versus reality










2

PwC

1. Covered last week




1.
What is Business Intelligence and Analytics?



2.
Why do businesses need BI&A?



In a moment...

3.
Business challenges in implementing BI


4.
BI isn’t new, so what’s different?




3

PwC

2. What is Business Intelligence
and

Analytics?

























Enterprise
Reporting

Scorecards

Mobile BI

Business Process
Modelling

Predictive Analytics

Text Mining

Data
Visualisation

Data Mining

OLAP
Analysis

BI Competency
Centre

Modelling

Alerts and
Notifications

BI Strategy
and
Roadmap

Dashboards

Forecasting



BI&A is the collective term for
strategies, methods and tools that
empower an organisation to unlock
value from their data.




It is the key to an organisation
making better decisions using relevant,
reliable and timely data.



Without it, businesses would make
poor decisions based on gut instinct
alone.

Data Cubes

4

PwC

3. Why do businesses need BI&A?

BI&A provides a solution to key client challenges…





5

New Insights


How can I obtain
insights that can help pinpoint new
revenue
-
generating opportunities and
improve operational efficiencies and
visibility across the organization?

Spreadsheet Reporting


How do I
reduce my reliance on spreadsheets for
forecasting or reporting, and reduce
resources spent on manual reworking of
data?

Increased regulatory pressures


How do I provide the necessary reports
and analysis to meet future regulatory
demands?

Relevant, reliable and timely data


How do I ensure I have the right data at
the right time to improve my decision
-
making capability?

Optimise IT Investment


How do
Optimizing the return on existing
business and IT investments such as data
management, relationship management
and enterprise resource planning
technology.

Single Version of the truth


How do
I get

insights on a comparable basis from
across the organisation, e.g. a global view
of my customer, product or brand.

PwC

6

4. Business Challenges in implementing BI

1.
Unclear Business objectives

2.
Ownership


CFO, CIO?

3.
Business buy
-
in due to previous
failures

4.
Business changes

5.
Lack of Skills


Business


Technical



6.
Requirements are Technology led

7.
Existing technology complexity

8.
Data Quality

9.
Implementation approach

10.
Cost & Return on investment




PwC

7

5. BI isn’t new, so what’s different?

1.
Competitive advantage


what value is first mover advantage?


2.
Rapidly changing external environment e.g.


Market


need to be more competitive and reduce costs


Regulations


increasing post the crash on all businesses


Shareholders


want better performance and transparency


Customers


demanding greater value for money


3.

Information overload
-

‘drowning in data but starved for
knowledge’
(John
Naisbitt
)


4.
Technology investments failing to deliver promised
RoI
;


Lack of business ownership


ERP & Operational/’
silo’d
’ reporting solutions


Data is not managed as a corporate asset







PwC

Key Messages




1.
Business Intelligence, while always important, is now critical to allow
businesses to;


Manage
risk and regulatory
challenges


Drive
operational efficiency


Enhance
value and revenues

2.
Helps businesses overcome the
underlying technological complexity

3.
Increasing volume of data requires businesses to have good
underlying data
management

4.

Businesses are likely to have different levels of
‘maturity’
in the skills and
abilities required to deliver good business intelligence

5.
Implementing BI in a business is not easy and has a number of
business
, and
then,
technology challenges








8

PwC

1. Emerging trends in BI




9

Drill
-
Down Reporting



Data Visualisation

Cloud Computing

SOA (Service Orientated Architecture)

On
-
demand Analytics

Operational Data warehouses

Big Data

SaaS
/
PaaS

Master Data Management

BI Competency Centres

Hardware Analytics

Enterprise Information Integration

Data Quality Bureau

Information Asset Management


Competitive Intelligence

PwC

1. Emerging trends in BI


Data




10

Cloud Computing

Operational Data warehouses

Big Data

Master Data Management

BI Competency Centres

Enterprise Information Integration

Data Quality Bureau

Information Asset Management


PwC

1. Emerging trends in BI


Data




11

Cloud Computing

Operational Data warehouses

Big Data

Master Data Management

BI Competency Centres

Enterprise Information Integration

Data Quality Bureau

Ensuring trusted definition of key
information

Dedicated skills/business function
to support Business intelligence with
business and technology skills

Information Asset Management


Connecting information across the
enterprise

Data sources containing specific
operational data e.g. HR, Finance

A means by which to deliver
technology


renting rather than
owning

A service (internal or external) that
provides DQ capabilities

Utilise ever growing sources and
volumes of data to achieve new insight

Approach to treat Information as an
asset in the same way as £ or staff

PwC

1. Emerging trends in BI


Reporting & Analytics




12

Drill
-
Down Reporting



Data Visualisation

Cloud Computing

On
-
demand Analytics

Operational Data warehouses

Big Data

SaaS
/
PaaS

BI Competency Centres

Hardware Analytics

Competitive Intelligence

PwC

1. Emerging trends in BI


Reporting & Analytics




13

Drill
-
Down Reporting



Data Visualisation

Cloud Computing

On
-
demand Analytics

Operational Data warehouses

Big Data

SaaS
/
PaaS

BI Competency Centres

Hardware Analytics

Software or Platform


as a service

Ability to ‘drill’ down from high level
report/figures to underlying detail

Prebuilt Servers and software
bundles, optimised for analytics

Having Analytics carried out by a 3
rd

party using your Data.

Combining and
presenting Data using
visually rich
techniques so as to
derive new insight

Competitive Intelligence

PwC

2. How clients are implementing BI to realise value




Cubes

Data Mart

Client Data

Analytical
Queries

Reporting &
Analytics
Layer

Operational
Data Store

CRM

Enterprise
Resource Platform

Transaction Data

Other Data

PwC Analytic Team

Data
Management

Data Profiling

Master Data
Management

ETL

Data Quality

Economics

Data Warehousing

Analytics

Document Exports

Operational
Reports

Dashboards

Analytical Services

Business Intelligence Applications

Analytics Applications

Enterprise Information
Platform

BI&A
Platform

Source

Finance

Operations

People

Strategy

Technology

GRC

Output


Business Intelligence Competency Centre

PwC

5. Hype versus Reality




15

This publication has been prepared for general guidance on matters of interest only, and does
not constitute professional advice. You should not act upon the information contained in this
publication without obtaining specific professional advice. No representation or warranty
(express or implied) is given as to the accuracy or completeness of the information contained
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members, employees and agents do not accept or assume any liability, responsibility or duty of
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information contained in this publication or for any decision based on it.


© 2011 PricewaterhouseCoopers LLP. All rights reserved. In this document, “PwC” refers to
PricewaterhouseCoopers LLP which is a member firm of PricewaterhouseCoopers
International Limited, each member firm of which is a separate legal entity.

Business Intelligence and Analytics



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