Data or Process Centric Approach to Decision Making

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Business Intelligence Data or Process Centric
Approach to Decision Making
Dimitar Dimitrov dimitar.d.dimitrov_at_cchbc.com Lead
Business Intelligence/SAP BW Consultant 08.11.200
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Glancing at the Contents

• Introduction to Business Intelligence
• BI approaches for implementation and best
  practices
• Data vs. Process centric BI
• BI as a foundation for CPM and CI
• Questions

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Modern Organizations Decision Making

• Todays e-business environment is brutal and
  uncompromising. Globalization has spawned bigger,
  more powerful competitors. Customers are more
  sophisticated and selective, demanding higher
  levels of service, quality, and customization.
• Companies need pertinent information about
  customers, partners, suppliers and market trends
  in a timely manner and preferred style.
• Business generates and acquires huge amounts of
  data, often hard to use for decision making.
• Departmental reporting and analytical
  applications are not solutions to the problems.

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Business Intelligence
BI is neither a product nor a system. It is an
architecture and a collection of integrated
operational as well as decision-support
applications and databases that provide the
business community easy access to business
data. The processes, tools, and technologies
required to turn data into information and
information into knowledge and plans that drive
effective business activity.
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What is BI about?

• Business Intelligence is processing of the huge
  amounts of data available to the enterprises
  today into a valuable content for the business.
• Business Intelligence allows access, sharing and
  analysis of data by the right people, at the
  right time.
• Business Intelligence is about having single
  version of truth and thus enabling Decision
  Making, Corporate Performance Management and
  Competitive Intelligence.

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BI as Data Refinery
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Business Intelligence
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What is behind a successful BI initiative?

• From Information Technology point of view
• Implement cutting edge technologies like
• Enterprise Data Warehousing and Data Mining.
• Knowledge Management.
• Click-stream and Geospatial analysis.
• Predictive analysis, Forecasting and Balance
  Scorecard preparation.
• Dashboarding and data access from mobile
  devices.
• Provide relevant technical solutions for
  enabling sophisticated analysis of huge data
  volumes with acceptable performance.
• Ensure data integration and quality.

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What is behind a successful BI initiative?

• From Business point of view
• Develop and follow Business Information strategy
  aligned with the Corporate Strategy.
• Focus on business opportunities, goals and
  required information to achieve them.
• Ensure cross organizational support and
  involvement.
• Expect and utilize Project Management
  methodology capable of delivering high-grade
  Intelligence solutions.
• Prepare for organizational, business process and
  cultural change.

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Data-centric BI approach - Architecture
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Data-centric BI approach Analytical Landscape
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Data-centric BI approach - Issues

• BI creates an artificial barrier between
  transactional data and historical data, and it
  does nothing to prevent a tight coupling between
  applications and data.
• People analyze events and make decisions based
  on what happened in the past, what is happening
  right now and what is likely to happen in the
  future. In the normal decision-making process,
  people do not put up artificial barriers between
  these time domains.
• Instead of analyzing the past, the present and
  the future in a seamless way, users are forced to
  move between tools, processes and methodologies.

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Data-centric BI approach - Issues

• BI solution providers limit themselves by asking
  users what they want, rather than asking them
  what they want it for.
• Dealing predominantly with the past, BI is
  relegated to the role of a fancy aggregator of
  historical data rather than a provider of true,
  comprehensive intelligence.
• Enterprise Data Management (EDM) - a common
  response to data governance issues, is a
  heavy-handed solution that may not be sustainable
  for most companies.

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The rise of Process-Centric BI

• BI includes data, rules, documents,
  organizational structures, roles, key performance
  indicators, metrics and process models.
  Originating or linked to business processes,
  these BI units, can provide a common base for
  Business Process Management (BPM) and BI.
• By using a integration of BPM and BI
• Users will be able to relate BI to business
  processes.
• IT architects will be able to relationally link
  data islands together and offer seamless,
  end-to-end process visibility to business users.
• Business analysts will be able to investigate
  and document analytical needs as part of the
  project's requirements-gathering phase, being
  empowered to ask their business customers what
  they want the information for.
• Business users will be able to convey their
  decision-making and analytic needs to IT rather
  than just requesting a compilation of data.

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The rise of Process-Centric BI

• The systemic collaboration between BI and BPM
  can ensure unparalleled support for focused
  decision-making
• users have trust in the quality of data.
• reported metrics are aligned to business
  priorities.
• conclusions derived from the data are logically
  sound and provable.
• information exposes clear courses of action and
  visibility into the business processes.
• This implementation can provide stable
  foundation for integrating both internal and
  external data sources into the relevant business
  process and thus allow full scale
• Corporate Performance Management
• Competitive Intelligence

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The rise of Process-Centric BI

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Thank You! Any Questions? Business Intelligence
Data or Process Centric Approach to Decision
Making
Dimitar Dimitrov dimitar.d.dimitrov_at_cchbc.com Lead
Business Intelligence/SAP BW Consultant 08.11.200
7
Author Name, Date