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                      Business Analytics
                      Tomorrow’s analytics that will change the way we make decisions
                  - Arindam Banerji, Parashar Borkotoky




                  Introduction
                  Enterprises have been extremely patient with their business intelligence (BI) investments over the years. But, two things
                  have changed, Volatility of markets and the need to manage a myriad of data sources along with huge amounts of data
                  means that decision-making has to move beyond gut feel. Second - with a large number of BI initiatives failing to meet
                  stated objectives within reasonable RoI cycles, decision making capabilities must be made available to a large set of users
                  in quick time with investments that are user-centric and not necessarily just focused on scale. Third, organizations today
                  are not satisfied with traditional reporting models that rely on historical data and answer ‘what happened?’ They are
                  increasingly wanting to know:
                  	       • What will happen next?           • What’s the best that can happen?        • What if these trends continue?

                  Finally, the science has changed – Hadoop, Pregel are not the same in their science as traditional OLAP tools – the business
                  decisions they support have also changed. This sea-shift from traditional BI, which we waguely term as Business Analytics,
                  is going to shape how decisions are made and attract significant IT investments.




             www.infosys.com
What are the key trends that are shaping Business Analytics?

     Business                Why is this                                       Examples of metrics/                      Financial
     Driver                  important?                                        changes                                   Impact

                             Executives want to predict the future
                             and not just the past. They want our              Expected GDP Growth
     Predict the                                                                                                         Improve revenue
                             approaches to do through tools/                   Regulatory Environment
     future                                                                                                              predictability
                             consulting, what they used to do                  Consumer Spend Trend
                             through gut feel


                                                                               Appropriate visualization for end
                             Expand the number of users – 8-10% of             use models                                Improve Productivity
     Consumerization
                             users use BI today                                                                          of users
                                                                               Device enablement



     Disruptive              Big Data, In-Memory, Analytics as a               OPEX Centric business case                Reduce Cost of
     Technologies            service, Unstructured data                        Faster, Cheaper Functionality             Initiatives


                                                                                                                         Improve speed and
     Transformational        BI Transformation like ERP
                                                                               Business Analytics initiatives at         accuracy of decision
                             Transformation – Concept of
     Changes                                                                   corporate levels                          -making at highest
                             Information ERP
                                                                                                                         levels


                                                                               Accuracy of Data
     Data Foundation         Enable bottom-line cost savings                                                             Decrease costs
                                                                               Redundancy of Data




What are the key gaps in today’s business intelligence systems?
Today’s business intelligence systems are adept at gathering, storing, analyzing, and providing access to historical data. However, they often
fall short in looking at the future – they’re quite poor in ensuring that decision makers can deal with volatility in their operating businesses and
markets. Key gaps include:

   •	 Unable to predict key business metrics with reasonable amount of accuracy – volatility in markets, external factors not available in
      historical data

   •	 Lack of industry specific reasoning and decision making models – especially incorporation of functional and sub-vertical specific decision
      scenarios/algorithms

   •	 Lack of deep, yet contextualized visualization that can make use of BI, pervasive across the enterprise regardless of the device it is served
      upon

   •	 Lack of a unified data foundation where there is absolute trust in the quality of data – especially the ability to seamlessly integrate the
      right data from both structured and unstructured sources

   •	 Unable to find statistical relationships between data that can provide strategic insights – co-relation between datasets that can lead to
      insights

   •	 Inability to map disruptive technologies such as big data or in-memory computing into the right kind of decision making tools




2 | Infosys – View Point
The Infosys Business Analytics offering




Infosys’ is creating a business analytics offering that will give you the processes, tools and expertise to extract the most out of your information
investments.

The offerings combine deep domain understanding of business scenarios with advanced technology and analytical techniques to enable quick
time to market at affordable price.

The offering will consist of these components:

   •	 Turnkey Offerings that can be used to manage business metrics and tied to business outcomes e.g Forecasting accuracy

   •	 Domain content for key business scenarios like Vendor performance management

   •	 A seamless platform infrastructure with pre-built stack for decision making, analysis and data management.

   •	 Surround services like Knowledge services that are required to manage the business outcome



A Business analytics scenario
Let’s consider the following scenario around Vendor performance management which is typical for manufacturing companies.




              BUSINESS DRIVER                                                             CHALLENGES


              • Increased outsourcing and reliance on suppliers                           • Increased complexity in managing suppliers
              • Globalization of business and of supply chains



              • Continuous Merger and Acquisitions                                        • Fragmented supplier data across multiple
              • Ever-changing Industry and government regulations                           disconnected purchasing systems



              • Increased uncertainty and unstable supply market                          • Increased risk of supply disruptions
              • Improve Profitability                                                     • Monitor and reduce sourcing costs




                                                                                                                              Infosys – View Point | 3
Infosys approach
The Infosys business analytics approach to such a problem will entail looking at both historical data analysis as well as predictive data analysis
such as early warning systems.




                                                          Infosys approach (Illustrative)




An effective business analytics approach for Vendor management would involve looking at the information from multiple perspectives:




          Historical                                  What-if analysis                             Prediction
          Insights


                  E.g. analysis of quality                    E.g. Ability to model                        Ability to estimate the
                  and effectiveness of                        the key levers that                          number of defects
                  suppliers                                   impact vendor costs                          based on both internal
                                                                                                           and external factors




4 | Infosys – View Point
Illustrative Business Outcomes
 Using a well-rounded business analytics
approach can result in quantifiable benefits
                 such as:




       5%
                 reduction in
                 procurement costs




       3%
                 lead time
                 reduction




       20%
                    improvement in
                    ontime delivery




                                           Infosys – View Point | 5
Conclusion
                           The promise of decision making applications, deployed in cost effective systems
                           that derive insights from all information repositories, internal and external,
                           structured and unstructured along with focus on not just ‘what has happened?’
                           but also on ‘what will happen?’ will make business insights truly beneficial to all
                           business users– the holy grail of Business Analytics.




6 | Infosys – View Point
About the Authors
Arindam Banerji
Unit Technology Officer, Manufacturing, Infosys Limited
For the last 18 years, Arindam has been a technologist of some visibility within the industry.
As one of the visionaries and chief technologist behind E-speak at HP, Arindam in the late-
nineties laid the foundation for the next generation of computing, now broadly known as
web services and Service-Oriented Architectures (SOA). He was also one of the early pioneers
of semantic search.
In the past, he has been the Global R&D head for Hewlett Packard’s Web-Services (then called
E–Services) product lines, Principal Scientist and Head of Strategy Research Organization for
HP’s Services business, Architect at Sun Microsystems and the CTO for several tech. startups
in the Manufacturing space.
At Infosys, his group focuses on providing technology strategy and advisory services to
Manufacturing customers globally, while providing intellectual property driven solutions in
the supply chain and engineering collaboration spaces.
He has a PhD from the University of Notre Dame, over 30 publications and 6 patents.
Arindam can be reached at Arindam_Banerji@infosys.com


Parashar Borkotoky
Principal Architect - Manufacturing
Parashar has over 13 years of experience in the IT industry, and is a certified TOGAF (The Open
Group Architecture Framework) practitioner. He has active interest in supply chain problems/
solutions, information management and data quality. Parashar anchors the Manufacturing
Information Effectiveness suite of solutions within Infosys that focuses on solving business
analytics and data foundation problems in various manufacturing industry sectors like
Automotive, Discrete manufacturing etc. He also works closely with manufacturing
enterprises to strategize technology focused business initiatives.
Parashar can be reached at Parashar_Borkotoky@infosys.com




                                                                                  Infosys – View Point | 7
About Infosys
Many of the world's most successful organizations rely on Infosys to
deliver measurable business value. Infosys provides business consulting,
technology, engineering and outsourcing services to help clients in over
30 countries build tomorrow's enterprise.

For more information, contact askus@infosys.com                                                                                                                                       www.infosys.com
© 2012 Infosys Limited, Bangalore, India. Infosys believes the information in this publication is accurate as of its publication date; such information is subject to change without notice. Infosys acknowledges
the proprietary rights of the trademarks and product names of other companies mentioned in this document.

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Business Analytics

  • 1. View Point Business Analytics Tomorrow’s analytics that will change the way we make decisions - Arindam Banerji, Parashar Borkotoky Introduction Enterprises have been extremely patient with their business intelligence (BI) investments over the years. But, two things have changed, Volatility of markets and the need to manage a myriad of data sources along with huge amounts of data means that decision-making has to move beyond gut feel. Second - with a large number of BI initiatives failing to meet stated objectives within reasonable RoI cycles, decision making capabilities must be made available to a large set of users in quick time with investments that are user-centric and not necessarily just focused on scale. Third, organizations today are not satisfied with traditional reporting models that rely on historical data and answer ‘what happened?’ They are increasingly wanting to know: • What will happen next? • What’s the best that can happen? • What if these trends continue? Finally, the science has changed – Hadoop, Pregel are not the same in their science as traditional OLAP tools – the business decisions they support have also changed. This sea-shift from traditional BI, which we waguely term as Business Analytics, is going to shape how decisions are made and attract significant IT investments. www.infosys.com
  • 2. What are the key trends that are shaping Business Analytics? Business Why is this Examples of metrics/ Financial Driver important? changes Impact Executives want to predict the future and not just the past. They want our Expected GDP Growth Predict the Improve revenue approaches to do through tools/ Regulatory Environment future predictability consulting, what they used to do Consumer Spend Trend through gut feel Appropriate visualization for end Expand the number of users – 8-10% of use models Improve Productivity Consumerization users use BI today of users Device enablement Disruptive Big Data, In-Memory, Analytics as a OPEX Centric business case Reduce Cost of Technologies service, Unstructured data Faster, Cheaper Functionality Initiatives Improve speed and Transformational BI Transformation like ERP Business Analytics initiatives at accuracy of decision Transformation – Concept of Changes corporate levels -making at highest Information ERP levels Accuracy of Data Data Foundation Enable bottom-line cost savings Decrease costs Redundancy of Data What are the key gaps in today’s business intelligence systems? Today’s business intelligence systems are adept at gathering, storing, analyzing, and providing access to historical data. However, they often fall short in looking at the future – they’re quite poor in ensuring that decision makers can deal with volatility in their operating businesses and markets. Key gaps include: • Unable to predict key business metrics with reasonable amount of accuracy – volatility in markets, external factors not available in historical data • Lack of industry specific reasoning and decision making models – especially incorporation of functional and sub-vertical specific decision scenarios/algorithms • Lack of deep, yet contextualized visualization that can make use of BI, pervasive across the enterprise regardless of the device it is served upon • Lack of a unified data foundation where there is absolute trust in the quality of data – especially the ability to seamlessly integrate the right data from both structured and unstructured sources • Unable to find statistical relationships between data that can provide strategic insights – co-relation between datasets that can lead to insights • Inability to map disruptive technologies such as big data or in-memory computing into the right kind of decision making tools 2 | Infosys – View Point
  • 3. The Infosys Business Analytics offering Infosys’ is creating a business analytics offering that will give you the processes, tools and expertise to extract the most out of your information investments. The offerings combine deep domain understanding of business scenarios with advanced technology and analytical techniques to enable quick time to market at affordable price. The offering will consist of these components: • Turnkey Offerings that can be used to manage business metrics and tied to business outcomes e.g Forecasting accuracy • Domain content for key business scenarios like Vendor performance management • A seamless platform infrastructure with pre-built stack for decision making, analysis and data management. • Surround services like Knowledge services that are required to manage the business outcome A Business analytics scenario Let’s consider the following scenario around Vendor performance management which is typical for manufacturing companies. BUSINESS DRIVER CHALLENGES • Increased outsourcing and reliance on suppliers • Increased complexity in managing suppliers • Globalization of business and of supply chains • Continuous Merger and Acquisitions • Fragmented supplier data across multiple • Ever-changing Industry and government regulations disconnected purchasing systems • Increased uncertainty and unstable supply market • Increased risk of supply disruptions • Improve Profitability • Monitor and reduce sourcing costs Infosys – View Point | 3
  • 4. Infosys approach The Infosys business analytics approach to such a problem will entail looking at both historical data analysis as well as predictive data analysis such as early warning systems. Infosys approach (Illustrative) An effective business analytics approach for Vendor management would involve looking at the information from multiple perspectives: Historical What-if analysis Prediction Insights E.g. analysis of quality E.g. Ability to model Ability to estimate the and effectiveness of the key levers that number of defects suppliers impact vendor costs based on both internal and external factors 4 | Infosys – View Point
  • 5. Illustrative Business Outcomes Using a well-rounded business analytics approach can result in quantifiable benefits such as: 5% reduction in procurement costs 3% lead time reduction 20% improvement in ontime delivery Infosys – View Point | 5
  • 6. Conclusion The promise of decision making applications, deployed in cost effective systems that derive insights from all information repositories, internal and external, structured and unstructured along with focus on not just ‘what has happened?’ but also on ‘what will happen?’ will make business insights truly beneficial to all business users– the holy grail of Business Analytics. 6 | Infosys – View Point
  • 7. About the Authors Arindam Banerji Unit Technology Officer, Manufacturing, Infosys Limited For the last 18 years, Arindam has been a technologist of some visibility within the industry. As one of the visionaries and chief technologist behind E-speak at HP, Arindam in the late- nineties laid the foundation for the next generation of computing, now broadly known as web services and Service-Oriented Architectures (SOA). He was also one of the early pioneers of semantic search. In the past, he has been the Global R&D head for Hewlett Packard’s Web-Services (then called E–Services) product lines, Principal Scientist and Head of Strategy Research Organization for HP’s Services business, Architect at Sun Microsystems and the CTO for several tech. startups in the Manufacturing space. At Infosys, his group focuses on providing technology strategy and advisory services to Manufacturing customers globally, while providing intellectual property driven solutions in the supply chain and engineering collaboration spaces. He has a PhD from the University of Notre Dame, over 30 publications and 6 patents. Arindam can be reached at Arindam_Banerji@infosys.com Parashar Borkotoky Principal Architect - Manufacturing Parashar has over 13 years of experience in the IT industry, and is a certified TOGAF (The Open Group Architecture Framework) practitioner. He has active interest in supply chain problems/ solutions, information management and data quality. Parashar anchors the Manufacturing Information Effectiveness suite of solutions within Infosys that focuses on solving business analytics and data foundation problems in various manufacturing industry sectors like Automotive, Discrete manufacturing etc. He also works closely with manufacturing enterprises to strategize technology focused business initiatives. Parashar can be reached at Parashar_Borkotoky@infosys.com Infosys – View Point | 7
  • 8. About Infosys Many of the world's most successful organizations rely on Infosys to deliver measurable business value. Infosys provides business consulting, technology, engineering and outsourcing services to help clients in over 30 countries build tomorrow's enterprise. For more information, contact askus@infosys.com www.infosys.com © 2012 Infosys Limited, Bangalore, India. Infosys believes the information in this publication is accurate as of its publication date; such information is subject to change without notice. Infosys acknowledges the proprietary rights of the trademarks and product names of other companies mentioned in this document.