Business intelligence systems are also unable to deal with market volatiles. Infosys' business analytics offerings provide the processes, tools and expertise to extract the most from information investments description.
[2024]Digital Global Overview Report 2024 Meltwater.pdf
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
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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
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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
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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.
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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
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