Presentation deck from a webinar with Comcast Business and Entrepreneur about collecting and using customer and prospect data to provide the best experience for customers.
Big Data in Financial Services: How to Improve Performance with Data-Driven D...Perficient, Inc.
Most banking and financial services organizations have only scratched the surface of leveraging customer data to transform their business, realize new revenue opportunities, manage risk and address customer loyalty. Yet a business’s digital footprint continues to evolve as automated payments, location-based purchases, and unstructured customer communications continue to influence the technology landscape for financial services.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
Every industry is becoming data driven, built around its information systems. Nowhere is this more evident than in retail where customer data is pivoting to flow across the traditional customer touchpoints and retailers are creating organizational structures that are responsible for the customer experience across traditional functional silos.
Presentation deck from a webinar with Comcast Business and Entrepreneur about collecting and using customer and prospect data to provide the best experience for customers.
Big Data in Financial Services: How to Improve Performance with Data-Driven D...Perficient, Inc.
Most banking and financial services organizations have only scratched the surface of leveraging customer data to transform their business, realize new revenue opportunities, manage risk and address customer loyalty. Yet a business’s digital footprint continues to evolve as automated payments, location-based purchases, and unstructured customer communications continue to influence the technology landscape for financial services.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
Every industry is becoming data driven, built around its information systems. Nowhere is this more evident than in retail where customer data is pivoting to flow across the traditional customer touchpoints and retailers are creating organizational structures that are responsible for the customer experience across traditional functional silos.
Your Digital Journey is Being Mapped by Your CustomersCapgemini
Capgemini's Scott Clarke talks with with MIT Sloan Management Review contributing editor Michael Fitzgerald about the impact of digital transformation and the reception of the research in the market.
Given that digitization had such a transformative effect on customer behavior and relationships, it is perhaps not surprising that many organizations focused their digital transformation efforts on the customer experience front-end. However, in the race to focus on the customer, it was all too easy to ignore operations. Our 2013 research with MIT Sloan Management Review found that while 40% of digital initiatives were focused on the customer experience, this dropped to 26% for operations...
Source : https://www.capgemini-consulting.com/going-big-operations-analytics
Big Data: The Road to Know More About Your BusinessOAUGNJ
Does your organization have a Big Data strategy or have you started your Big Data journey? Surveys are showing that Big Data has not been implemented in the majority of companies. The difficulty is that the amount of data the world is producing outstrips most companies’ ability to use it. This session will review the need for a big data strategy, how to get started and the critical success factors to ensure you are on the Big Data Road to Success. Companies are creating huge business value by capturing more data (particularly unstructured data) from social media, sensors and mobile devices. Learn how these companies got started and what they are doing to transform their business.
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Embracing Digital Technology: A New Strategic ImperativeCapgemini
New research from Capgemini Consulting and MIT Sloan Management Review reveals why organizations are struggling to drive Digital Transformation and the need for C-level leadership.
The study – involving over 1,500 executives in 106 countries – reveals that while the potential opportunity of Digital Transformation is absolutely clear, the journey to get there is not.
A business-friendly approach to data governance is imperative to engage all users and accommodate diverse business use cases spanning analytics, operational improvements, and compliance requirements. To increase adoption and collaboration, business and technical data users across your organisation need to have a common, agreed-upon, and documented understanding of which data is most important, what it’s called, and where it’s used.
Watch this on-demand webinar, where we explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
We also look at how Oripharm, one of the dynamic healthcare players in the Nordics and international markets, choose a data governance solution:
• to improve personalisation of products and services
• to achieve accurate and timely credit-risk analysis
• to increase user productivity by improving time-to-insights
• to mitigate risk and facilitate regulatory compliance and reporting
Speakers:
Mikkel Holmgaard - Data Governance Lead, Orifarm
Emily Washington - Sr. Vice President, Product Management, Precisely
Microsoft er en data-drevet organisation, og finance spiller en vigtig rolle ift dette. Data-indsigt er en forudsætning for en transparant forretning og for transformation. Hør Microsofts CFO’s syn på sagen og se en demo af de spændende muligheder med Power BI og visualisering.
George Tsichlis, CFO og Lars Bo Granath, Produktchef for Data Platform, Microsoft Danmark
Presentation from the Markedsføringsdagen 2013 conference, june 12 2013 in Copenhagen. Contains an overview of trends, uses, challenges for the CMO and innovation aspects of big data.
Your Digital Journey is Being Mapped by Your CustomersCapgemini
Capgemini's Scott Clarke talks with with MIT Sloan Management Review contributing editor Michael Fitzgerald about the impact of digital transformation and the reception of the research in the market.
Given that digitization had such a transformative effect on customer behavior and relationships, it is perhaps not surprising that many organizations focused their digital transformation efforts on the customer experience front-end. However, in the race to focus on the customer, it was all too easy to ignore operations. Our 2013 research with MIT Sloan Management Review found that while 40% of digital initiatives were focused on the customer experience, this dropped to 26% for operations...
Source : https://www.capgemini-consulting.com/going-big-operations-analytics
Big Data: The Road to Know More About Your BusinessOAUGNJ
Does your organization have a Big Data strategy or have you started your Big Data journey? Surveys are showing that Big Data has not been implemented in the majority of companies. The difficulty is that the amount of data the world is producing outstrips most companies’ ability to use it. This session will review the need for a big data strategy, how to get started and the critical success factors to ensure you are on the Big Data Road to Success. Companies are creating huge business value by capturing more data (particularly unstructured data) from social media, sensors and mobile devices. Learn how these companies got started and what they are doing to transform their business.
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Embracing Digital Technology: A New Strategic ImperativeCapgemini
New research from Capgemini Consulting and MIT Sloan Management Review reveals why organizations are struggling to drive Digital Transformation and the need for C-level leadership.
The study – involving over 1,500 executives in 106 countries – reveals that while the potential opportunity of Digital Transformation is absolutely clear, the journey to get there is not.
A business-friendly approach to data governance is imperative to engage all users and accommodate diverse business use cases spanning analytics, operational improvements, and compliance requirements. To increase adoption and collaboration, business and technical data users across your organisation need to have a common, agreed-upon, and documented understanding of which data is most important, what it’s called, and where it’s used.
Watch this on-demand webinar, where we explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
We also look at how Oripharm, one of the dynamic healthcare players in the Nordics and international markets, choose a data governance solution:
• to improve personalisation of products and services
• to achieve accurate and timely credit-risk analysis
• to increase user productivity by improving time-to-insights
• to mitigate risk and facilitate regulatory compliance and reporting
Speakers:
Mikkel Holmgaard - Data Governance Lead, Orifarm
Emily Washington - Sr. Vice President, Product Management, Precisely
Microsoft er en data-drevet organisation, og finance spiller en vigtig rolle ift dette. Data-indsigt er en forudsætning for en transparant forretning og for transformation. Hør Microsofts CFO’s syn på sagen og se en demo af de spændende muligheder med Power BI og visualisering.
George Tsichlis, CFO og Lars Bo Granath, Produktchef for Data Platform, Microsoft Danmark
Presentation from the Markedsføringsdagen 2013 conference, june 12 2013 in Copenhagen. Contains an overview of trends, uses, challenges for the CMO and innovation aspects of big data.
Solving Stagnated Business Growth with Data MiningAndrew Leo
In today's data-driven world, leveraging insights from vast datasets can propel your business to new heights. From enhancing customer experiences to optimizing decision-making, data mining offers endless opportunities for growth and innovation.
Key benefits of data mining include:
Personalized customer experiences
Improved decision-making
New business models
Enhanced efficiency
Stronger cybersecurity
Achieving social goals
Discover how data mining can transform your sales strategies, marketing campaigns, healthcare services, customer service, HR management, fraud detection, and manufacturing processes.
Curious to learn more? Check out our comprehensive guide on how data mining can help solve stagnated business growth.
Ready to harness the power of data mining for your business? Let's connect and explore the possibilities.
Top Business Intelligence Trends - By DataToBizKavika Roy
Ready to take your business to the next level? Discover the top business intelligence trends for this year and stay ahead of the game.
Read the full article: https://www.datatobiz.com/blog/top-business-intelligence-trends/
About DataToBiz:
DataToBiz is a team of experts who are committed to helping businesses and enterprises adopt advanced technologies like Data Science, Artificial Intelligence, and Business Intelligence technologies. We possess rich experience in designing, implementing, and crafting Data Engineering Solutions, for a wide array of business challenges.
DataToBiz: https://www.datatobiz.com/
Bigdata analysis in supply chain managmentKushal Shah
big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before.
supply chain industry need this type of data to survive in every situations.
Foster Moore® prepared a white paper for the recent meeting of the National Association of Secretaries of State (NASS). It looks at the reasons that Secretaries of State might consider when going digital.
CHAPTER
9
Business Intelligence
and Analytics
Sergey Nivens/Shutterstock.com
Copyright 2018 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203
Know?Did Yo
u
• MetLife is implementing analytical software to identify
medical provider, attorney, and repair shop fraud to aid
its special investigations unit (SIU).
• Nearly 20 percent of Medicare patients were readmitted
to the hospital within 30 days of their initial discharge,
running up an additional $17 billion in healthcare costs.
Hospitals are now using BI analytics to identify patients
are high risk of readmission—especially now that
Medicare has begun reducing payments to hospitals
with high readmission rates.
• IBM Watson Analytics services, a cloud-based
business analytics tool that offers a variety of tools for
uncovering trends hidden in large sets of data, uses
baseball statistics on every player in Major League
Baseball from AriBall to build predictions of player
performance. You can use this service to gain an
edge over your fantasy baseball league competitors.
Principles Learning Objectives
• Business intelligence (BI) and analytics are used
to support improved decision making.
• Define the terms business intelligence (BI) and
analytics.
• Provide several real-world examples of BI and
analytics being used to improve decision making.
• Identify the key components that must be in place
for an organization to get real value from its BI and
analytics efforts.
• There are many BI and analytics techniques and
tools that can be used in a wide range of problem-
solving situations.
• Identify several BI techniques and discuss how
they are used.
• Identify several BI tools.
• Define the term self-service analytics and discuss
its pros and cons.
Copyright 2018 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203
Why Learn about Business Intelligence (BI)
and Analytics?
We are living in the age of big data, with new data flooding us from all directions at the
incomprehensible speed of nearly a zettabyte (1 trillion gigabytes or a 1 followed by 21 zeros) per year.
What is most exciting about this data is not its amount, but rather the fact that we are gaining the tools
and understanding to do something truly meaningful with it. Organizations are learning to analyze
large amounts of data not only to measure past and current performance but also to make predictions
about the future. These forecasts will drive anticipatory actions to improve business strategies,
strengthen business operations, and enrich decision making—enabling the organization to become more
competitive.
A wide range of business users can derive benefits from access to data, but most of them lack
deep information systems or data science skills. Business users need easier and faster ways to discover
relevant patterns and insights into data to better support their decision maki ...
Using Adaptive Scrum to Tame Process Reverse Engineering in Data Analytics Pr...Cognizant
Organizations rely on analytics to make intelligent decisions and improve business performance, which sometimes requires reproducing business processes from a legacy application to a digital-native state to reduce the functional, technical and operational debts. Adaptive Scrum can reduce the complexity of the reproduction process iteratively as well as provide transparency in data analytics porojects.
It Takes an Ecosystem: How Technology Companies Deliver Exceptional ExperiencesCognizant
Experience is evolving into a strategy that reaches across technology companies. We offer guidance on the rise of experience and its role in business modernization, with details on how orgnizations can build the ecosystem to support it.
The Work Ahead: Transportation and Logistics Delivering on the Digital-Physic...Cognizant
The T&L industry appears poised to accelerate its long-overdue modernization drive, as the pandemic spurs an increased need for agility and resilience, according to our study.
Enhancing Desirability: Five Considerations for Winning Digital InitiativesCognizant
To be a modern digital business in the post-COVID era, organizations must be fanatical about the experiences they deliver to an increasingly savvy and expectant user community. Getting there requires a mastery of human-design thinking, compelling user interface and interaction design, and a focus on functional and nonfunctional capabilities that drive business differentiation and results.
The Work Ahead in Manufacturing: Fulfilling the Agility MandateCognizant
According to our research, manufacturers are well ahead of other industries in their IoT deployments but need to marshal the investment required to meet today’s intensified demands for business resilience.
The Work Ahead in Higher Education: Repaving the Road for the Employees of To...Cognizant
Higher-ed institutions expect pandemic-driven disruption to continue, especially as hyperconnectivity, analytics and AI drive personalized education models over the lifetime of the learner, according to our recent research.
Engineering the Next-Gen Digital Claims Organisation for Australian General I...Cognizant
In recent years, insurers have invested in technology platforms and process improvements to improve
claims outcomes. Leaders will build on this foundation across the claims landscape, spanning experience,
operations, customer service and the overall supply chain with market-differentiating capabilities to
achieve sustainable results.
Profitability in the Direct-to-Consumer Marketplace: A Playbook for Media and...Cognizant
Amid constant change, industry leaders need an upgraded IT infrastructure capable of adapting to audience expectations while proactively anticipating ever-evolving business requirements.
Green Rush: The Economic Imperative for SustainabilityCognizant
Green business is good business, according to our recent research, whether for companies monetizing tech tools used for sustainability or for those that see the impact of these initiatives on business goals.
Policy Administration Modernization: Four Paths for InsurersCognizant
The pivot to digital is fraught with numerous obstacles but with proper planning and execution, legacy carriers can update their core systems and keep pace with the competition, while proactively addressing customer needs.
The Work Ahead in Utilities: Powering a Sustainable Future with DigitalCognizant
Utilities are starting to adopt digital technologies to eliminate slow processes, elevate customer experience and boost sustainability, according to our recent study.
AI in Media & Entertainment: Starting the Journey to ValueCognizant
Up to now, the global media & entertainment industry (M&E) has been lagging most other sectors in its adoption of artificial intelligence (AI). But our research shows that M&E companies are set to close the gap over the coming three years, as they ramp up their investments in AI and reap rising returns. The first steps? Getting a firm grip on data – the foundation of any successful AI strategy – and balancing technology spend with investments in AI skills.
Operations Workforce Management: A Data-Informed, Digital-First ApproachCognizant
As #WorkFromAnywhere becomes the rule rather than the exception, organizations face an important question: How can they increase their digital quotient to engage and enable a remote operations workforce to work collaboratively to deliver onclient requirements and contractual commitments?
Five Priorities for Quality Engineering When Taking Banking to the CloudCognizant
As banks move to cloud-based banking platforms for lower costs and greater agility, they must seamlessly integrate technologies and workflows while ensuring security, performance and an enhanced user experience. Here are five ways cloud-focused quality assurance helps banks maximize the benefits.
Getting Ahead With AI: How APAC Companies Replicate Success by Remaining FocusedCognizant
Changing market dynamics are propelling Asia-Pacific businesses to take a highly disciplined and focused approach to ensuring that their AI initiatives rapidly scale and quickly generate heightened business impact.
The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...Cognizant
Intelligent automation continues to be a top driver of the future of work, according to our recent study. To reap the full advantages, businesses need to move from isolated to widespread deployment.
The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...
Data Modernization: The Foundation for Digital Transformation
1. Data Modernization:
The Foundation for
Digital Transformation
How leading organizations transformed their digital core to
enable artificial intelligence (AI)
2. Bret Greenstein
Senior Vice President
and Global Head,
Cognizant Artificial Intelligence
Data is one of today’s most valuable resources. It’s more
plentiful and varied than ever. But, having more data
doesn’t make your business more digital. In an effort to
turn data into an asset, companies are struggling to access
it, analyze it and mine it for its greatest value leveraging
advanced analytics and AI. Those capable of fully
leveraging advanced analytics and AI will have a significant
competitive advantage. At Cognizant, we’re
delivering on data’s promise by helping our client’s to first
build a modern digital core — regardless of their starting
point. Whether that be ideas and iteration, piloting, data
migration, full implementation or expansion of existing
systems — we help them achieve their business goals.
The following case studies present a range of real-world
examples with quantifiable results from clients that have
made the leap to leveraging data as an asset. Through
these transformations, they have been able to increase
revenues, remove silos across the business, increase
service levels and implement a system of governance
while at the same time decreasing costs associated with
storing, analyzing and disseminating data. Cognizant’s
data modernization delivers the precision that drives
competitiveness by leveraging our reference model,
platforms, tools and methodology. The results? A
convenience store chain piloted a self-service carry-out
solution, a utility was able to use drone imagery to
predict and service remote insulators, and a financial
institution was able to significantly reduce check fraud
and save millions.
Let these case studies inspire how you to transform your
operations and customer experience by starting with a
modern data core.
Getting started on your data modernization journey
2 / Data Modernization: The Foundation for Digital Transformation
3. 3 / Data Modernization: The Foundation for Digital Transformation
Transforming Data Methods and Decision Making
4 BANKING & CAPITAL MARKETS
AI Solution Detects Check Fraud for a Leading
Global Bank
5 LIFE SCIENCES
Data Modernization Cuts Costs, Speeds Data
to Pharma Sales Reps
6 TRAVEL & HOSPITALITY
A Modern Platform Unlocks Fast Food Insights
7 ENERGY & UTILITIES
AI Speeds Repairs, Cuts Costs for Electric Utility
8 LIFE SCIENCES
Healthy Data? That Means Reliable, Defensible
and Accessible
9 RETAIL
Retail Customer Data Accelerates Decision-Making
10 CONSUMER GOODS
Tidying Up the “Digital Shelf” with Centralized Product
Information and Images
Index
4. The Challenge
A global financial services organization wanted
to automate and streamline its fraud detection
process. At many large banks, millions of checks
are still hand-written each month. While part
of this process is truly automatic, including
scanning paper checks, large banks still employ
hundreds of people to sit every day at computer
screens trying to spot signs of fraud in those
scans. This process is time-consuming and
inaccurate, and banks lose millions annually to
counterfeiters.
Our objective was twofold: to spot fraudulent
checks in real time at the time of deposit, and to
reduce the number of checks requiring manual
review. Such a solution would stem the outflow
of disbursements on counterfeits, reduce
tedious work and lower processing costs.
We helped the financial services organization
build a machine-learning solution that teaches
itself to identify counterfeit checks, thus
reducing fraud risk and lowering costs.
The Solution
We developed an artificial intelligence-driven
machine-learning solution to flag potential fraud
by analyzing scanned images of handwritten
checks. The technology is designed to
automatically compare a variety of factors on
scans of deposited checks against a growing
database of checks previously identified as
fraudulent, and then flag potential counterfeits
in near real-time while deposit transactions are
in process.
Our Approach
When we tested our model on a historical
portfolio of past transactions, it demonstrated
50% savings on fraud losses. It processed up
to 20 million checks per day, with end-to-end
response times of less than 70 milliseconds and
the ability to process up to 1,200 checks per
second.
AI Solution Detects Check Fraud for a Leading Global Bank
4 / Data Modernization: The Foundation for Digital Transformation
RESULTS
50% savings in check fraud losses was
demonstrated.
70 millisecond real-time check
confidence score generated.
A $20 million reduction in losses to
fraud annually, based on current models
is forecast.
Reduced manual effort while
keeping initial and ongoing costs low.
Read the full case study here.
BACK TO INDEX Banking & Capital Markets
5. The Challenge
A specialty pharmaceuticals company faced
rising costs and delays in gathering, analyzing
and transmitting the information its sales
representatives needed to plan their physician
calls and meet their sales targets. Sales reps
struggled with incomplete, conflicting and hard-
to-use information, and the company lacked
a single, integrated source of marketing and
financial data to improve its decision making.
The Solution
Using our AI Data Modernization Platform, we
helped the company reduce the time and cost of
collecting and normalizing data from 20 internal
and external systems. Now, sales reps receive
customized advice on a daily basis on their
laptop or mobile devices, based on their location
and the current state of their accounts. This
includes recommendations on which accounts
are the most worthwhile to visit, which physicians
and administrators to see at each account and
which products or promotions they should
spend the most time discussing.
These reports also warn of any danger signs,
such as stagnating sales of a specific product at
an otherwise well-performing customer. For the
first time, the company now has a “single source
of truth” for all its financial and marketing data,
helping sales reps maximize revenue and profits.
Our Approach
In addition to reducing costs and speeding data
access, the new platform also provides advanced
analytics to each representative on a daily basis
and a customized plan of accounts to target the
optimal plan for meeting sales goals.
Pre-built analytics and our industry-aligned
data model reduced the time required to
deploy the platform by one-third, and our
change management capabilities ensured rapid
adoption, user satisfaction and timely retirement
of older platforms.
Data Modernization Cuts Costs, Speeds Data to
Pharma Sales Reps
5 / Data Modernization: The Foundation for Digital Transformation
RESULTS
$450,000 in annual savings for
gathering and distributing account data
to sales reps.
35% reduction in the time required to
produce reports for the sales force.
30% reduction in implementation
time through the use of our pre-built
analytics and industry-aligned data
model.
Maximized revenue and profits
with improved, real-time data.
Read the full case study here.
BACK TO INDEX Life Sciences
6. The Challenge
One of the largest U.S.-based fast-food
companies wanted to improve its decision-
making, provide more self-service data analysis
for franchisees and expand its loyalty offerings.
To accomplish these goals, the company needed
better insights into franchise performance and
improved visibility into its inventory and staffing.
The company knew this meant migrating from
its on-premises legacy data warehouse, which
couldn’t produce needed information in a timely
fashion and was costly and burdensome to
maintain.
The Solution
Our proposal featured our cloud-based AI-
driven platform that enables faster reporting,
better data accuracy and lower maintenance
costs while increasing flexibility, scalability and
customer engagement. It also includes an AI-
driven personalized customer experience and
marketing intelligence reports.
The restaurant chain now has 4,000 stores in
North America that are uploading data to the
warehouse in real time. Leveraging data on a
cloud-based intelligent platform has enabled
the business to gain insights, build customer
relationships and improve operations, achieving
its overall goals of increasing revenue and
reducing costs.
Our Approach
We delivered insights that allow the business
to find and resolve real-time operational
challenges, track sales of specific menu items
to drive insights into customer preferences and
manage labor efficiency and inventory.
The solution also provides quick insights into
sales, product mix and the performance of
promotions and discounts, as well as a single
view of data consolidated from multiple
locations.
A Modern Platform Unlocks Fast-Food Insights
6 / Data Modernization: The Foundation for Digital Transformation
RESULTS
10% reduction in average order time
for drive-through customers.
4,000 North American stores
access the data warehouse, greatly
improving data accuracy.
Significant cost reduction due to
the near elimination of software licenses.
Up-to-the-minute sales, product
and regional insights and performance
metrics.
Read the full case study here.
BACK TO INDEX Travel & Hospitality
7. The Challenge
A U.S. utility needs to monitor the condition of
thousands of different components across tens
of thousands of square miles of service area,
much of it in remote locations. Such monitoring
is essential because in order to maintain service
levels and prevent system outages, it’s crucial to
identify and fix failing or damaged components,
such as the insulators that connect transmission
wires to poles.
While the utility used images taken by drones
to identify equipment that needed repair in
its far-flung distribution network, it was time-
consuming and inefficient to manually examine
the photos and open a repair ticket, making it
impossible to generate actionable real-time
intelligence.
The Solution
The utility now has a fully managed data and
analytic platform that enables data scientists to
build, train and deploy AI models on-site or in
the cloud, greatly reducing the cost and time
required for image analysis and performing
needed repairs.
To compensate for a lack of properly labeled
images, we used image augmentation to create
as many as 12 new labeled images from each
original by changing lighting or angles or adding
new objects to the images. This greatly increased
the raw data on which the application could
learn, and thus its accuracy. We also automated
critical activities such as data labeling, the
building of AI models, training and deployment.
Our Approach
We used our AI Data Modernization Platform to
create an AI-driven image analytics application
that assesses drone-captured photos in real time
to identify problems such as broken or chipped
insulators. This self-service solution provides
immediate insights to detect issues and an
alerting engine to notify the maintenance team
about needed repairs.
The utility’s deep-learning library is now hosted
on a cluster of computing containers to reduce
the cost and effort of implementation and
management. An optimal cognitive computer
vision model has been employed to provide the
highest accuracy and ease of implementation to
seamlessly scale and accommodate the alerting
pipeline.
AI Speeds Repairs, Cuts Costs for Electric Utility
7 / Data Modernization: The Foundation for Digital Transformation
RESULTS
60% reduction in the effort required
for image scanning.
Faster and less costly repairs
through automated identification of
problems and triggering of work orders.
Increased service levels, reduced
outages and improved the customer
experience.
Read the full case study here.
BACK TO INDEX Energy & Utilities
8. The Challenge
Over its 100 years, a global life sciences
company has acquired multiple complementary
businesses, including major pharmaceutical
research companies. The company has
accumulated a vast repository of global human
health data that it uses to address questions
and concerns, respond to legal inquiries and
incorporate in ongoing research.
While the organization had critical information
on its substantial range of drugs and
compounds, the data wasn’t readily accessible.
Faced with an expensive, legacy mainframe
environment that inhibited free and fast access
to its own data, the company chose to migrate
more than 150 terabytes of data to a new,
globally accessible cloud platform, increasing
information flexibility and lowering costs.
The Solution
Our AI Data Modernization Method has
substantially improved the company’s data
access times and sharply lowered its costs — $10
million over three years. It has reduced the IT
department’s reliance on an internal team and
an exhaustive process to design and deliver
custom reports. It also preserves the company’s
existing data access and data security protocols,
and it uses the same portal as the previously
outsourced mainframe hosting provider.
Having ownership of its database allows the
company to manage data across the business
lifecycle, using a unified security model that
ensures active data governance. The new
platform helps ensure compliance with global
regulations for storing and using health data
under the industry-standard rubric of “good
practice” quality guidelines and regulations
(GxP).
Our Approach
We examined the current state of the company’s
IT architecture, developed use cases to support
the blueprint for its desired future state, and
then designed and managed the successful
migration of all its historical data. Our solution,
based on Amazon Web Services (AWS), offered
the company a global repository.
This cloud-enabled architecture is a modernized,
highly responsive data ecosystem that helps
the company source, transform and consume
data through the cloud, leveraging artificial
intelligence and advanced analytical techniques.
The model provides the flexible data structure,
tools and accelerators needed to generate
maximum business value.
Healthy Data? That Means Reliable, Defensible and Accessible
8 / Data Modernization: The Foundation for Digital Transformation
RESULTS
95% reduction in external mainframe
data-hosting costs.
$3.6 million annual savings
through cloud migration.
50% improvement in data access
and retrieval speeds
Read the full case study here.
BACK TO INDEX Life Sciences
9. The Challenge
A leading global convenience store chain
needed to create a new data architecture
and management foundation — modernizing
its technology platform to improve access
to sales data, better manage its supply chain
and implement robust analytics for predictive
decision making. They were being prevented
from doing so due to aging IT infrastructure and
outdated database systems.
Our client sought a scalable, flexible solution that
could meet the demands of its diverse, complex
system of franchisees. They needed a way to
quickly integrate new applications, perform
audits, increase and improve ad-hoc reporting
capability, apply similar business rules across the
organization and reduce overhead. Critically,
management wanted to be able to aggregate
and analyze store data in near real time, to
customize sales at various locations based on
specific customer needs.
The Solution
Our team of retail digital experts migrated
three years of historical data to a cloud-based
infrastructure — moving more than 16 terabytes
of data. We then implemented a cloud platform
that improves data ingestion from the company’s
thousands of stores and allows for real-time
availability of data, while lowering infrastructure
costs and software licensing fees by 40% for on-
premise applications.
Combining our newly streamlined AI-ready data
model and cloud-based platform infrastructure
together meant that the company could
implement intelligent analytics to address
prevailing business challenges and enable new
initiatives.
Our Approach
The new, streamlined AI-based data model
gives the company intelligent analytics to
address prevailing challenges and support new
initiatives, including a project to allow customer
carry-out self-service. Their new cloud-based
data ecosystem significantly improves query
and reporting capability, delivering current and
historical intelligence to the business more
quickly, taking new KPIs into account. Tracked
data includes active-store daily sales, gross
profits, merchandise inventory counts, write-offs,
invoicing and order data. The company benefits
from a more transparent, easily documented
audit trail, with streamlined and consistent
business rules across the organization.
Retail Customer Data Accelerates Decision-Making
9 / Data Modernization: The Foundation for Digital Transformation
RESULTS
Zero downtime due to infrastructure
upgrades, with no negative impact on
the business.
Migrated 16TB to a hybrid cloud
platform.
40% reduction in infrastructure and
software licensing costs.
Read the full case study here.
BACK TO INDEX Retail
10. The Challenge
A global consumer goods business wanted a way
to syndicate accurate product information to
its 500 e-commerce partners and distributors
quickly — and confirm that existing listings were
correct and up-to-date. However, product
information was scattered across many systems.
Attributes such as product titles, features,
descriptions, dimensions and package counts
were inconsistent across countries. Additionally,
the systems could not store product images,
documents and videos, which were spread
across still more systems.
A lack of a single source of truth for product
information was created cascading problems.
New product listings had to wait until marketing
and brand teams could hunt through multiple
systems to find the right information and
images. Different descriptions for the same
product produced inaccurate sales reports
and forecasts. The full auditing process on
e-commerce sites for out-of-date information
took six to eight months, exposing the company
to legal and compliance risks. These challenges
would multiply as the company introduced
more products in more countries through more
channels and in more languages.
The Solution
We built a digital shelf solution that serves as a
single source of truth for tens of thousands of
products and hundreds of thousands of images
for business segments operating in 40 countries.
We worked in two-week sprints to roll it out
across North America, Latin America, EMEA and
Asia Pacific from 2015 to 2019.
Today, more than 3,500 employees and
agencies use the digital shelf solution, which
country teams can customize to accommodate
their needs. The company now has an easier,
more automated way to syndicate product data
to retailers and other channels.
Our Approach
We designed and implemented a centralized
product information management and digital
asset management system that ensures the
company’s e-commerce sites and distributors
are publishing the latest product information
and images — increasing sales, strengthening the
brand and avoiding fines.
Tidying Up the “Digital Shelf” with Centralized Product
Information and Images
10 / Data Modernization: The Foundation for Digital Transformation
RESULTS
$3 million annual savings in
operational expenses.
60% improvement in time to market
via digital channels.
68% time saved on creating product
listings.
Six months of time saved on
auditing images on partner websites.
Read the full case study here.
BACK TO INDEX Consumer Goods