The document discusses the growing importance and opportunities of analytics for businesses. It notes that there is a widening performance gap between top performers and bottom performers in their use of data and analytics. While the amount of data is growing exponentially, there is also a significant skills gap in having enough talent to effectively analyze and use data. The document outlines several major themes where businesses are applying analytics, including customer insights, risk management, operations, and product design. It argues that analytics can drive significant business value when integrated into operations and transformations.
Capturing Value from Big Data through Data Driven Business models prensetationMohamed Zaki
This presentation demonstrates a study which provides a series of implications that may be particularly helpful to companies already leveraging ‘big data’ for their businesses or planning to do so. The Data Driven Business Model (DDBM) framework represents a basis for the analysis and clustering of business models. For practitioners the dimensions and various features may provide guidance on possibilities to form a business model for their specific venture. The framework allows identification and assessment of available potential data sources that can be used in a new DDBM. It also provides comprehensive sets of potential key activities as well as revenue models.The identified business model types can serve as both inspiration and blueprint for companies considering creating new data-driven business models. Although the focus of this paper was on business models in the start-up world, the key findings presumably also apply to established organisations to a large extent. The DDBM can potentially be used and tested by established organisations across different sectors in future research.
The purpose of business intelligence is to support better business decision making. BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data.
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.
How to Build Data Governance Programs That Last: A Business-First ApproachPrecisely
Traditional data governance initiatives fail by focusing too heavily on policies, compliance, and enforcement, which quickly lose business interest and support. This leaves governance leaders and data stewards having to continually make the case for data governance to secure business adoption.
In this introductory session, we will share the core components of a business-first data governance approach that promotes organizational adoption, lays the foundation for data integrity, and consistently delivers business value for the long term.
What is business intelligence and where it is applicable is described in this presentation. The subject is offered as elective to BE IT students of Pune University.
Capturing Value from Big Data through Data Driven Business models prensetationMohamed Zaki
This presentation demonstrates a study which provides a series of implications that may be particularly helpful to companies already leveraging ‘big data’ for their businesses or planning to do so. The Data Driven Business Model (DDBM) framework represents a basis for the analysis and clustering of business models. For practitioners the dimensions and various features may provide guidance on possibilities to form a business model for their specific venture. The framework allows identification and assessment of available potential data sources that can be used in a new DDBM. It also provides comprehensive sets of potential key activities as well as revenue models.The identified business model types can serve as both inspiration and blueprint for companies considering creating new data-driven business models. Although the focus of this paper was on business models in the start-up world, the key findings presumably also apply to established organisations to a large extent. The DDBM can potentially be used and tested by established organisations across different sectors in future research.
The purpose of business intelligence is to support better business decision making. BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data.
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.
How to Build Data Governance Programs That Last: A Business-First ApproachPrecisely
Traditional data governance initiatives fail by focusing too heavily on policies, compliance, and enforcement, which quickly lose business interest and support. This leaves governance leaders and data stewards having to continually make the case for data governance to secure business adoption.
In this introductory session, we will share the core components of a business-first data governance approach that promotes organizational adoption, lays the foundation for data integrity, and consistently delivers business value for the long term.
What is business intelligence and where it is applicable is described in this presentation. The subject is offered as elective to BE IT students of Pune University.
Day 1 Keynote address by Winifred Kotin, Country Director of Superfluid Labs, Ghana on the theme: "The promise of Data Science for Economic Transformation".
Ramyam Intelligence Lab has been quoted in various segments in Indian Analytics Products ecosystem a report from NASSCOM (through Deloitte Analysis, Analyst reports and NASSCOM).
Enterprise Business Intelligence
Marketing Analytics
Customer Loyalty Management
Customer Life Cycle Management.
An interview with Jack Levis, Director of Process Management at UPS.
"Our challenge hasn’t been around identifying analytics talent as much as it has been in determining the best way to train the hundreds of business people who are using these tools."
Sage Business Intelligence Solutions ComparisonRKLeSolutions
This presentation outlines the differences between Sage Intelligence (SI) and Sage Enterprise Intelligence (SEI) for Sage 100, Sage 500 ERP and Sage X3.
Data Sciences & Analytics Discover the unknown power of the knownYASH Technologies
Our data science’s and analytics’ competency accelerates the data-driven decision making process and empowers you with capabilities that will guide you in deriving deeper insights. We can transform your business into a more nimble and connected organisation through our extensive portfolio
Industry researchers at Gartner announced in April 2012 that the worldwide business intelligence, analytics, and performance management software market surpassed the US$12 Billion level in 2011, a 16.4% increase over the previous year. This statistic is among many pointing to the need for both groups to apply what management guru Peter Senge proclaimed decades ago in The Fifth Discipline: the need for a learning organization. This presentation focuses on three learning areas for anyone in the business analytics profession. First, we analysts need to learn what the markets and industries are saying today. We discuss recent trends which show how analytics will shape the future. Second, we need to learn what group learning options are available. From industry conferences (such as the PASS BA Conference, and virtual PASS sessions) to free MOOCs (massive open online courses), we have more options available to improve our knowledge. Finally, we need to learn what leadership roles our groups can have. We can leverage social networks (including PASS) and social media -- both individually and as organizations -- to communicate passion.
In this advanced business analysis training session, you will learn Data Analytics Business Intelligence. Topics covered in this session are:
• What is Business Intelligence?
• Data / information / knowledge
• What is Data Analytics?
• What is Business Analytics?
• What is Big Data?
• Types of Data
• Types of Analytics
• What is Business Intelligence?
For more information, click here: https://www.mindsmapped.com/courses/business-analysis/advanced-business-analyst-training/
Transforming Business with Smarter AnalyticsCTI Group
Transforming Business with Smarter Analytics by Deb Mukherji @ BPT IBM Innovative Indonesia with Smarter Analytics, 12 June 2013, Shangri-La Hotel Jakarta
how i managed to Develop a Analytics story for services about 4 years back. Contains
Maturity Model, Business Potential, Services Structures Areas that analytics can be applied to
20150108 create time stamp
Leverage Sage Business Intelligence for Your OrganizationRKLeSolutions
Learn how Sage Business Intelligence provides the insight you need to make better decisions faster! This informative presentation explores Sage Intelligence and Sage Enterprise Intelligence solutions for Sage 100, Sage 500 and Sage X3.
Day 1 Keynote address by Winifred Kotin, Country Director of Superfluid Labs, Ghana on the theme: "The promise of Data Science for Economic Transformation".
Ramyam Intelligence Lab has been quoted in various segments in Indian Analytics Products ecosystem a report from NASSCOM (through Deloitte Analysis, Analyst reports and NASSCOM).
Enterprise Business Intelligence
Marketing Analytics
Customer Loyalty Management
Customer Life Cycle Management.
An interview with Jack Levis, Director of Process Management at UPS.
"Our challenge hasn’t been around identifying analytics talent as much as it has been in determining the best way to train the hundreds of business people who are using these tools."
Sage Business Intelligence Solutions ComparisonRKLeSolutions
This presentation outlines the differences between Sage Intelligence (SI) and Sage Enterprise Intelligence (SEI) for Sage 100, Sage 500 ERP and Sage X3.
Data Sciences & Analytics Discover the unknown power of the knownYASH Technologies
Our data science’s and analytics’ competency accelerates the data-driven decision making process and empowers you with capabilities that will guide you in deriving deeper insights. We can transform your business into a more nimble and connected organisation through our extensive portfolio
Industry researchers at Gartner announced in April 2012 that the worldwide business intelligence, analytics, and performance management software market surpassed the US$12 Billion level in 2011, a 16.4% increase over the previous year. This statistic is among many pointing to the need for both groups to apply what management guru Peter Senge proclaimed decades ago in The Fifth Discipline: the need for a learning organization. This presentation focuses on three learning areas for anyone in the business analytics profession. First, we analysts need to learn what the markets and industries are saying today. We discuss recent trends which show how analytics will shape the future. Second, we need to learn what group learning options are available. From industry conferences (such as the PASS BA Conference, and virtual PASS sessions) to free MOOCs (massive open online courses), we have more options available to improve our knowledge. Finally, we need to learn what leadership roles our groups can have. We can leverage social networks (including PASS) and social media -- both individually and as organizations -- to communicate passion.
In this advanced business analysis training session, you will learn Data Analytics Business Intelligence. Topics covered in this session are:
• What is Business Intelligence?
• Data / information / knowledge
• What is Data Analytics?
• What is Business Analytics?
• What is Big Data?
• Types of Data
• Types of Analytics
• What is Business Intelligence?
For more information, click here: https://www.mindsmapped.com/courses/business-analysis/advanced-business-analyst-training/
Transforming Business with Smarter AnalyticsCTI Group
Transforming Business with Smarter Analytics by Deb Mukherji @ BPT IBM Innovative Indonesia with Smarter Analytics, 12 June 2013, Shangri-La Hotel Jakarta
how i managed to Develop a Analytics story for services about 4 years back. Contains
Maturity Model, Business Potential, Services Structures Areas that analytics can be applied to
20150108 create time stamp
Leverage Sage Business Intelligence for Your OrganizationRKLeSolutions
Learn how Sage Business Intelligence provides the insight you need to make better decisions faster! This informative presentation explores Sage Intelligence and Sage Enterprise Intelligence solutions for Sage 100, Sage 500 and Sage X3.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
In the recent past, we have learnt that data is the lifeline of any business and it is really important to collect data, more and more of it. But no one is telling us what to do with large volumes of data.
Shailendra has successfully delivered over One Billion Dollars in incremental value and will spend 30 minutes in showcasing how many large organisations are using data to their advantage by creating value through generating incremental revenue and optimising costs using analytics techniques.
Key Takeaways:
(i) Demystify the myths of analytics
(ii) Walkthrough a step-by-step approach to delivering successful projects that created an incremental value of hundreds and millions of dollars.
(iii) Three use cases where large organisations are using analytics to their advantage by creating value by generating incremental revenue and optimising costs.
Operationalizing Customer Analytics with Azure and Power BICCG
Many organizations fail to realize the value of data science teams because they are not effectively translating the analytic findings produced by these teams into quantifiable business results. This webinar demonstrates how to visualize analytic models like churn and turn their output into action. Senior Business Solution Architect, Mike Druta, presents methods for operationalizing analytic models produced by data science teams into a repeatable process that can be automated and applied continuously using Azure.
What is Business intelligence
Core Capabilities of Business Intelligence
Elements of Business Intelligence
Why Companies opt for Business Intelligence
Benefits of Business Intelligence
User of Business Intelligence
Reports of Business Intelligence
Business Application in Extended Enterprise
Business Analytics
Golden Rules for Business Intelligence
5 Stages of Business Intelligence
The demand for BI continues to grow, and while there's no question that analytics brings value, there is often uncertainty about how BI initiatives will deliver bottom-line benefits. Your business case for BI should prove ROI, but this is not always a straightforward process.
Big Data, Big Thinking: Untapped OpportunitiesSAP Technology
In this webinar factsheet, SAP’s Rohit Nagarajan and Suni Verma from Ernst & Young explore Big Data in India, adoption patterns across the globe, and how you can embark on your own Big Data journey.
How Can You Calculate the Cost of Your Data?DATAVERSITY
Today, self-service, Cloud and big data technologies make new data preparation capabilities necessary…and possible. But, we've all been through the hype cycle and know the trough of disillusionment can come on hard and fast.
Organizations have been trying to solve the data quality problem and democratize insights for years spending millions of dollars and dedicating an increasing amount of resources to manage and govern the data. The result? Everyone is still looking to solve the problem.
Data preparation offers a new paradigm, but how can you avoid another round of minimal business impact? We’ll review a true data ROI model that helps organizations understand the value of existing versus modern data management architectures.
Business intelligence and data analytic for value realization iyke ezeugo
This presentation centres on how Businesses can take advantage of this era of information overload for enhancing their Business Intelligence and Data Analytic exploits to assure greater values with the available technology solutions.
It is focused on demystifying the BIG DATA phenomenon of the information age, and also on motivating traditional business drivers to begin to take advantage of business decision support systems (DSS) for their business intelligence and data analytics needs. The objective is to help organizations discover what and what they can do with these ICT solutions in their business for greater value realization. These values are expressed in building agile business that are able to thrive, make profit, grow and remain sustainable in the midst of stiff competition, globalization, innovation and regulatory pressures, even with elastic customers’ demands.
Self-service analytics @ Leaseplan Digital: from business intelligence to int...webwinkelvakdag
Our mission is to drive digital data intelligence in a 55-year old company currently undergoing digital transformation.
We do this through cloud big data architecture and intuitive business performance visualizations based on multiple data sources across customer journeys. Join this session to find out how we are enabling enterprise wide adoption of self-service analytics both internally as single source of truth of business performance and as embedded analytics solution to end customers for real-time vehicle maintenance steering through predictive models.
In this session we will share our challenges, learnings, achievements and roadmap to embed self-service analytics in LeasePlan.
My read and summarization of the booklet on devops by mike loukides from O Reilly, great read for starters.. a good reference on automation, inreastructure as code
Tom Davenports Classic on hwo to Build Organizations of Knowledge workers, around talent Management, Information and Managerial Hygiene.. great reference for managers
Read in 2011, a very foundational book on physics, narrated in a very easy lay-man terms.. This book talks about constants, in nature and how we need to interpret and listen to these constants..
These are my book notes, great book one can buy this book on Amazon... worth a read for science buffs
In 2011 i read this wonderful book from the found of IDEO Tom Kelley, on how to manage and inculcate innovation.. this book was a precursor for the book ten faces of Innovation
A personal collection of HR concepts through training sessions attended.. highlights.. Areas like Presentations, Leadersdhip, Influencing, Interviews .. etc...
Life Biography and the philosophy of Sri Sankara, A book that i picked up at vadyar and sons Palakkad, well written introduction into the greatest Advaita philosopher Sri Sankara .. deck to be updated.. with more information later.s
UCF framework presented to a large IT service company in Mumbai in 2008.. showing my thinking then on how an organization could approach organization capability recording and building.. related to PCMMI.
Morey stettner wrote a very practical guide for managers, do surely read it.. this is my prime reference for managing my teams at work.. the presentation is a precis of that book and the key principles resident there..
Anticipatory Failure Determination <afd> is a method similar to FMEA in design, to extract and discover failures in design ad how to cope and manage these risks.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
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We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
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Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
2. Analytics growing as a business mandate.
Data is Growing Performance Gap Widens Capability Gap Exists..
4.4x
2.7x
2.4x
2.4x
2x
Investment in Data and
Analytics
Top Performer Bottom Performer
Sources: IBM Breakaway Now with Business
Analytics and Optimization
17%
42%
28%
10%
USE OF DATA BY BUSINESS*
75% or more 50-74%
25-49% 0-24%
++ There is a skill gap
60% executives say they “have more
information than we can effectively
use”** [IBM Report] .
McKinsey Report on Big Data estimates
50-60% gap in the supply of deep
analytical talent; equaling 140,000 to
190,000 unfilled positions.
40% growth in global data
annually
Globally 2.5 quintillion bytes of
data per day
90 % of the data in the world
today has been created in the last
two years alone.
Customer Transactions
Customer records through device
ubiquity and better data mgmt..
1
Customer Interactions
Social Unstructure, semantics..
20B events / Day – Facebook
2
Machine Interactions
Logs sensors intelligence on all
equipment
3
IBM Report Global Business Analytics
market size is pegged around $105 billion
and growing at CAGR 8%.
Shifting Priorities for
Management in Analytics..
3. Major themes for Analytics
Customer Insight
Business Risk
Operations /
Service Warranty
Service /
Warranty
Customer micro Segments – Delivering personalization
Customer propensities for action, Cross sell, preferences,
Next Best Action
Digital Marketing, Below the line & Discovery
Pricing Models / Sensitivity
Especially in BFSI where financial Risk coverage for
regulation and internal business
Portfolio Management & Ops Risk management
Worldwide financial services OpRisk and GRC technology
market will grow to $2 billion by 2013 [ @ CAGR 6.5% ]
Inventory, Parts Supply, Service Management
Geo-Loc coordination for Logistics, Users, & producers
Predicting failure of service and business components,
Customer contact, sentiment and intent
Resource Allocation and Triaging
New Product Design Pharma, Automobile, Hi Tech
Smart Pricing utilites and Energy
Claims And Litigation Insurance
4. Analytics Value to Business
Business
outcome
Operations
Transformation
Insights Data
•Strategic themes
•Customer Insight
•Digital Marketing
•Pricing / Risk
•Product Design
•Service / Operations
•BI / Dashboards
•Manual Operations
•Embedded Analytics
•CEP / Rules Engines
•RT Integration
•Analysis / Methods
•Prediction / Data Mining
•Machine Learning
•Sample vs Large Data
•Parameterized and NON
•Volume, Variety, Velocity
•Data Sources { External,
Unstructured }
•Data Integration {ETL}
•Data Lineage {Metadata}
•Data Preparation {Index,
Search}
•Customer Segmentation,
Behavior based models in
all industry
•Price Sensitivity analysis
•NPD / Molecule research
in Pharma
•Risk in BFSI
•Driving Digital Initiatives
like Mobile
•Triaging / Routing in
Contact centers
•Running a Analytics KPO
that provides insights for
Operations
•Methods like
Segmentation, Regression
based scoring,
• Sensitivity Scenarios ,
What-if
•Text and media mining
capabilities [ PCA ]
•Semantic Search
•70% of the effort is spelt
out in Data
•External sources, public
and paid..
•Text, media processing /
Index
5. Changing Landscape .. Analytic Techniques ..
MIT SMR – IBM Study – The New path to Value 2012
8. Analytics Services Maturity Model
ALIGNED INTEGRATED OPTIMIZINGFRAGMENTED
DATAANALYTICSVISUALIZATIONPROCESS[ACTIONS]
SCALE / STRUCTURE
SOURCE / RETRIEVE
CONFIG - CONTROL
INTERACTION
ALGORITHM
MODELING
DESIGN
EXECUTE
MANAGE
PRESENTATION
STRUCTURE
Simple 2-Dimensional Graphs and
reports including Types of Visuals
supported?
Static simple play out
Simple structure, numeric [ cardinal]
and non-numeric- [ Ordinal]
Internal Local Files, federated
Ad-hoc Customer opportunity
Operational Changes >
Basic Functions and statistics
User Configuration, Data Security
Structured Data with metadata
support,
Integrated data sets through DB-
DWH, SQL based retrieve
Single Iteration playout
Computational Flows
Process Maps, Kpi- Metrics
Breakdowns,
Manual Process Change / Actions
Tactical Changes – re-structure to
Business operations, processes..
Linear Functions, Regression,
Statistics,
Strategy Changes - New services
models, synthesis of business value
Integrated Partner Actions,
Automation into systems,
scenario analysis, what -if analysis,
Complex Statistics [econometrics] ,
Numerical Method, Clustering
Analysis,
System Generation-Automation ,
visual re-formation,
Compliance and traceability effort in
adding new data sources
external connectors – API,
Composite Visuals, infographics
Unstructured text, Data Scale – Size
and time
Value Chain Analysis , Benchmark
Data
New Revenue Models
Sense and response mechanisms,
Simulation, optimization,
Text & Analytics, Neural Networks,
fractals,
Actions integration - external
systems.
Storyboards, Virtual Reality
late binding – auto discovery of
structure
Access to non standard data, late
structure binding
Real time search
Data as Media like Voice, Image and
Video Bigdata Management
pivot based interaction – User self
service
Maps, Multi-dimensional Graphs,
9. How are Businesses acquiring Analytics
Inhouse /
Captive
Solution
Utilities
Services /
Resources
Platforms /
Products
1. A Typical Bank would have a 1Bn USD budget
2. 80% spend inhouse and in Captive
3. 1200 Person = 600Mn $ Value / 100 Mn $ Cost
4. Slow, lethargy, internal Constraints, IPR
1. Small Boutique companies getting seeded
2. Focusing on either large platforms [ splunk ] or a
very specific Business use Case [ Mydrive ]
3. Scale issues, pricing,
1. Large resource houses, with 80% $ from staff Aug
2. Fragmented delivery, water fall, change is a
challenge , Utilisation is key , security & leakage
3. Can Scale, some can partner,
1. Best complement to Inhouse / Captive
2. Developing the foundations for the next gen,
3. Focused more on tech rather than business
4. Partner to all above entities,
10. Delivering Analytics Value to Business
Business
outcome
Operations
Transformation
Insights Data
SolutionsservicesToolsPlatforms
300 400 7000
wipro
Other players CTS, TCS, Big 4, musigma
TeraData
Pivotal
Opera
Cloudera
Tableau
Clikview
RevoR
Mydrive InfoChimp
70 1200 500Bank captive
11. Typical Analytics Practice
Strategic Eco-system Alliances
1051
Analytics [ 140 – 60 USD ]
BI [ 100 - 40 USD ]
Data / Integration [ 100 – 30 USD]
1. 80% of the business is still Staff
Augmentation
2. 80% of the business in BI / MI and
low end data services..
3. Large players like Wipro / TCS /
MuSigma in the range of 5000-
10000 resources
4. Lot of SME consulting Smaller
players
5. Clients are slower than the vendor..
1. Staff Augmentation in various Skill Areas
2. Partnering and COE development for clients
3. Project based Delivery – Agile Waterfall
4. Embedded Analytics in Operations and other initiatives
like Digital, mobile etc..
5. Service Transformational Analytics – CTS
6. Very weak in industry / Business domain
For Every Analytics
Resource.
12. Analytics Shifting Trends
Rapid Outsourcing
Growth
Bringing Data
together
Capabilities, Scale, =
purchase
Management End
User
Multiple Delivery
focused on Captive
Data Driven Business
Partnership, Eco-
system, Speed
Business End User
• Past helped ISV Grow Business [+30%
CAGR ]
• Analytics == IPR Captives
• Talent and Skills still a big shortage
• From structured to unstructured
• IOT / sensors, new external data
• Unstructured Data Media = Big Data
• Large Data – Lakes, Metadata
• Shift from Model to Compute
• Show & Tell + 0 consulting + Action
• Partnerships, COE, Investments, Utilities =
Value Add
• Utilities and Plug-n-Play
• Generating Business Use Cases Keeping
managers charmed = BI Sophistication +
Cool Tools
• Integrate Analytics within Digital
Initiatives
• Management Ops Customer
• Privacy + Security
Past 5 years Next 5 Years
13. How to Buy $$ Analytics
Business
outcomes
Partnering
Vendor
Total Cost of
Operation
Future
Proofing
• Deep integration with a Business outcome [ MyDrive]
• Charging and Collection Model [RDC]
• Time to deploy and transform [ Splunk ]
• Agile Delivery Models
• Show and Tell / Productized services
• Ability to Partner / Co-innovate
• Non-Linear Scale in the Business Model
• Easy to Consume, Utility, Pricing
• Eco System Partnerships
• Application potential across the Economy [ MyDrive]
• Keeping it simple.
14. Solution Capability Development
Business Value Modeling.
Analytics Program Model..
Business Value and thereby Performance Hotspots drive solutions and messages
Sales &
Marketing
Member
Mgmt & UW
Provider
Mgmt
Claims
Mgmt
Customer
Service
Medical
Mgmt
Revenue - GTM
Business Case
Account Intel
Pitch /
Proposal
Partnership /
POC
Events / ABM
Engagements
Quote
Generation
Broker
Mgmt
Campaig
n Mgmt
Market
Research
Member
Retention
1. Brand Perception / Perf
Ratio
2. Influence Ratio
3. Number of leads
4. Cost per lead
5. Medium Conversion Rate
6. Avg Premium Val
7. Days visit to purchase
8. Task Completion Rate SOLUTION
CATALOG
KEY
OUTCOMES
Key
Resources
Partnership Algorithm
Training Research LAB/ COE
Understand Business Landscape:
What value is business after? Key pain
points in decision making / operations
Leverage Internal Capability:
No duplication of work already done /
capability already in existence
In Sight of the Customer:
Develop capability through the
customer, interface, POC / Pilots
Develop Ecosystem for delivery:
Relationships with established &
emergent OEM who will drive the
market
Time Bound:
Ensure outcomes with time frame. 3
months to customer and 6 months to
pilot
Develop Systemic Solutions:
Consulting to understand customer,
quick entry, low change and capital….
1
2
3
4
5
6Data
Process
Actions
Analytics
Visualization
Capability Framework
1
2
3
Key principles
Program Status
15. Business Themes and Analytics COE
Marketing RoI & Growth analytics
Customer acquisition analytics
Customer retention analytics
Social media driven analytics
Customer/Employee fraud & risk
Competitive intelligence analytics
Supply chain analytics
MFG process quality & compliance
Early warning analytics
Asset Perf. Maint. & warranty
Network analytics
Service Problem Analysis
Service Logistic & Resource Alloc.
Governance, Risk & compliance
Integrated financial perf. - EPM
Store operations Analytics
Merchandising & Pricing analytics
Claims analytics
Pre-Trade Post Trade Analytics
Drug discovery analytics
Post market analytics (Pharma)
Care & Safety analytics
Care analytics
Member Retention Analytics
Smart meter analytics
Technology
Business Automation Modeling
Data
Analysis
Visuals
Process
People
Methods
Tools
Vertical
Themes
Customer
Lifecycle
Service &
Warranty
GRC
EPM/WIPM
• Product Mgrs [10]
• Clustered Solution
Themes + verticals
• Teams for Verticals
program mgmt
• Modelers & Technologist
report in.
• Business Consulting
• Innovation &
Transformation Client Pitch
/ Engagement
• Analytics Program
Management
• Long term look at
business Automation
solutions
• Modelers
• Cluster Solution Themes
• Exploring Analysis Tools
• Develop Models/Methods
• # Of experiments
• Play with data
• Information Technologist
• Cluster 1
• All Data Gather & Aggregation
technologies
• Solution Warranty / Scale
• Speed, Variety – API
• # Of experiments
• Manage COEEnv.
16. Vishwanath Ramdas
Head Analytics FCC Compliance , Large MNC Bank
8 years in the industry with 17 Y experience in Business Transformation.