Enterprises face unprecedented challenges, and finance is at the epicenter. Increasing business risk and volatility are evidenced by accelerating business disruption through
disintermediation, virtualization and technical innovation. As a result, new competitors, changing business models and changing customer expectations have emerged.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
The difficult art of quantifying return on digital investmentsBen Gilchriest
Measuring digital investments is proving to be a challenging task. Many companies have tried to create models that demonstrate the value of digital technologies, such as social media, applying traditional metrics to these. However, it's proving to be difficult to find a credible method.
So how do we make the difficult decision on where to invest in digital; especially when we are under so much pressure to do so much more? Whilst we need some sort of mechanism in place to make informed choices, traditional approaches to ROI are falling short. This paper describes these challenges in more detail (you are not alone, even amongst the world's leading digital companies, the 'Digirati', only 56% create a business case). It also describes three approaches you can take to define a digital business case, and provides perspectives on how to best approach digital investment decisions.
Keys to extract value from the data analytics life cycleGrant Thornton LLP
Regulatory mandates driving transparency and financial objectives requiring accurate understanding of customer needs have heightened the importance of data analytics to unprecedented levels making it a critical element of doing business.
Imagine … internal auditors identifying risks + opportunities from data. Internal auditors can + need to grasp this opportunity to transform their role and industry. More >> grantthornton.com/data-analytics
When it comes to scrutinizing costs, most insurance companies can say “Been there, done that. Got the t-shirt.” Managers are familiar with the refrain from above to trim here and cut there. The typical result is flirtation with the latest management trends like lean, outsourcing and offshoring, and others. However, the results tend to be the same. Budgets reflect last year’s spend plus or minus a couple of percent in the same places.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
The difficult art of quantifying return on digital investmentsBen Gilchriest
Measuring digital investments is proving to be a challenging task. Many companies have tried to create models that demonstrate the value of digital technologies, such as social media, applying traditional metrics to these. However, it's proving to be difficult to find a credible method.
So how do we make the difficult decision on where to invest in digital; especially when we are under so much pressure to do so much more? Whilst we need some sort of mechanism in place to make informed choices, traditional approaches to ROI are falling short. This paper describes these challenges in more detail (you are not alone, even amongst the world's leading digital companies, the 'Digirati', only 56% create a business case). It also describes three approaches you can take to define a digital business case, and provides perspectives on how to best approach digital investment decisions.
Keys to extract value from the data analytics life cycleGrant Thornton LLP
Regulatory mandates driving transparency and financial objectives requiring accurate understanding of customer needs have heightened the importance of data analytics to unprecedented levels making it a critical element of doing business.
Imagine … internal auditors identifying risks + opportunities from data. Internal auditors can + need to grasp this opportunity to transform their role and industry. More >> grantthornton.com/data-analytics
When it comes to scrutinizing costs, most insurance companies can say “Been there, done that. Got the t-shirt.” Managers are familiar with the refrain from above to trim here and cut there. The typical result is flirtation with the latest management trends like lean, outsourcing and offshoring, and others. However, the results tend to be the same. Budgets reflect last year’s spend plus or minus a couple of percent in the same places.
Developing a Preventative and Sustainable P-card ProgramCaseWare IDEA
Andrew Simpson from CaseWare Analytics talks about how educational institutions can implement a continuous monitoring program for their p-cards (purchase card) and the benefits.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Analytics in Financial Services: Keynote Presentation for TDWI and NY Tech Co...Fitzgerald Analytics, Inc.
Keynote Presentation Given in New York City on March 30th, at a joint event of The Data Warehousing Institute (TDWI) and the New York Technology Council. This keynote presentation by Jaime Fitzgerald focused on "Bridging the Gap" between business goals in the data and analytic enablers of achieving these goals.
Unlocking the data possibilities of Big Data presentation shared at the Big Data / Internet of Things Conference Board Conference June 25-26, 2015
http://www.pwc.com/us/en/analytics/big-data.jhtml
Broken links: Why analytics investments have yet to pay off, sponsored by ZS, draws on the survey findings, interviews with senior corporate executives and desk research to explore the current state of sales and marketing analytics.
Breaking the data barrier: Lessons from analytically advanced Finance organiz...Spencer Lin
The majority of enterprises recognize that data and analytics are transforming their businesses. But what about the Chief Financial Officer (CFO) and Finance? How are data and analytics changing their professions? To find out, the IBM Center for Applied Insights asked over 1,000 organizations across five industries about their Finance departments’ approach to data and analytics, cloud and engagement. Findings show that enterprises with analytically advanced Finance organizations reported better outcomes when it came to decision making, growth and agility.
The third edition of the BoardMatters Quarterly explores how big data and analytics emerge as game-changers for business. This edition also explores how we can tackle corruption, boosting internal control mechanisms.
Capitalizing on analytics in finance: Creating trusted insights for the enter...Spencer Lin
A recent IBM study of 337 CFOs and senior finance executives found that about 90% are implementing analytics solutions. However, analytics adoption is happening in pockets and isn’t pervasive across finance activities. With investment in analytics poised to double in the near term, how can Finance better capitalize on these new capabilities? To answer that question, we looked at the most effective Finance organizations and learned three important lessons from their success.
Organisations spend heavily on technology, people skills and consulting to understand billions of bits of data, but they still lack clear visibility and insight.....
Close the AI Action Gap in Financial ServicesCognizant
Banks and financial institutions are making strides with artificial intelligence -- but they've been slow to scale it. Here are four steps to realize AI's full potential throughout the enterprise.
See how the new CFO is adapting to a changing financial landscape, utilizing transformative new technology to disrupt, innovate and generate value for the insurance industry. Now is a pivotal moment for CFOs. Our new research on the dynamic role of the finance function reveals how the CFO is positioned at the center of the organization, side by side with the CEO, turning finance into an engine that can power the entire enterprise.
Learn more: https://www.accenture.com/us-en/insights/insurance/cfo-research-insurance
Over the past decade, a combination of new providers, technology, and capabilities have made global payroll administration a possibility – at least conceptually. The key stumbling block in this debate is the perceived need, on the one hand, for tailored services that are compliant with local regulations, and on the other hand standardization for cost reasons. So, where does that leave payroll?
AP & Working Capital – Increasing Revenues from Early PaymentsTradeshift
If you're not capturing supplier discounts because you can't pay your invoices fast enough, this report is just right for you.
PayStream Advisors recently surveyed about 300 AP and finance professionals, analyzed the results, and put together great ideas on how to make early payment programs work for you. This free report will show you how to:
- Utilize the right accounts payable practices to make perfectly timed payments
- Earn annual returns as high as 36% on available cash
- Select the right dynamic discounting solution
Kickstart your early payment program and download the report now.
Predictive and prescriptive analytics: Transform the finance function with gr...Grant Thornton LLP
As all businesses continue to collect, store and analyze more data than ever before, they face growing data challenges to support decision-making. Those who can leverage predictive and prescriptive analytics will differentiate themselves in the marketplace and gain a competitive advantage. In this report by Financial Executives Research Foundation Inc. and Grant Thornton LLP, we highlight insights from in-depth interviews with senior-level executives. These organizations use advanced analytics in their businesses to gain significant profit improvements. See more at - http://gt-us.co/1vv2KU9
With a fundamental shift in the CFO mission, the finance function has become a critical change agent across organizations. The role of financial leaders such as CFOs is evolving, from a traditional financial controller, to one that drives performance improvements across the organization.
Developing a Preventative and Sustainable P-card ProgramCaseWare IDEA
Andrew Simpson from CaseWare Analytics talks about how educational institutions can implement a continuous monitoring program for their p-cards (purchase card) and the benefits.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Analytics in Financial Services: Keynote Presentation for TDWI and NY Tech Co...Fitzgerald Analytics, Inc.
Keynote Presentation Given in New York City on March 30th, at a joint event of The Data Warehousing Institute (TDWI) and the New York Technology Council. This keynote presentation by Jaime Fitzgerald focused on "Bridging the Gap" between business goals in the data and analytic enablers of achieving these goals.
Unlocking the data possibilities of Big Data presentation shared at the Big Data / Internet of Things Conference Board Conference June 25-26, 2015
http://www.pwc.com/us/en/analytics/big-data.jhtml
Broken links: Why analytics investments have yet to pay off, sponsored by ZS, draws on the survey findings, interviews with senior corporate executives and desk research to explore the current state of sales and marketing analytics.
Breaking the data barrier: Lessons from analytically advanced Finance organiz...Spencer Lin
The majority of enterprises recognize that data and analytics are transforming their businesses. But what about the Chief Financial Officer (CFO) and Finance? How are data and analytics changing their professions? To find out, the IBM Center for Applied Insights asked over 1,000 organizations across five industries about their Finance departments’ approach to data and analytics, cloud and engagement. Findings show that enterprises with analytically advanced Finance organizations reported better outcomes when it came to decision making, growth and agility.
The third edition of the BoardMatters Quarterly explores how big data and analytics emerge as game-changers for business. This edition also explores how we can tackle corruption, boosting internal control mechanisms.
Capitalizing on analytics in finance: Creating trusted insights for the enter...Spencer Lin
A recent IBM study of 337 CFOs and senior finance executives found that about 90% are implementing analytics solutions. However, analytics adoption is happening in pockets and isn’t pervasive across finance activities. With investment in analytics poised to double in the near term, how can Finance better capitalize on these new capabilities? To answer that question, we looked at the most effective Finance organizations and learned three important lessons from their success.
Organisations spend heavily on technology, people skills and consulting to understand billions of bits of data, but they still lack clear visibility and insight.....
Close the AI Action Gap in Financial ServicesCognizant
Banks and financial institutions are making strides with artificial intelligence -- but they've been slow to scale it. Here are four steps to realize AI's full potential throughout the enterprise.
See how the new CFO is adapting to a changing financial landscape, utilizing transformative new technology to disrupt, innovate and generate value for the insurance industry. Now is a pivotal moment for CFOs. Our new research on the dynamic role of the finance function reveals how the CFO is positioned at the center of the organization, side by side with the CEO, turning finance into an engine that can power the entire enterprise.
Learn more: https://www.accenture.com/us-en/insights/insurance/cfo-research-insurance
Over the past decade, a combination of new providers, technology, and capabilities have made global payroll administration a possibility – at least conceptually. The key stumbling block in this debate is the perceived need, on the one hand, for tailored services that are compliant with local regulations, and on the other hand standardization for cost reasons. So, where does that leave payroll?
AP & Working Capital – Increasing Revenues from Early PaymentsTradeshift
If you're not capturing supplier discounts because you can't pay your invoices fast enough, this report is just right for you.
PayStream Advisors recently surveyed about 300 AP and finance professionals, analyzed the results, and put together great ideas on how to make early payment programs work for you. This free report will show you how to:
- Utilize the right accounts payable practices to make perfectly timed payments
- Earn annual returns as high as 36% on available cash
- Select the right dynamic discounting solution
Kickstart your early payment program and download the report now.
Predictive and prescriptive analytics: Transform the finance function with gr...Grant Thornton LLP
As all businesses continue to collect, store and analyze more data than ever before, they face growing data challenges to support decision-making. Those who can leverage predictive and prescriptive analytics will differentiate themselves in the marketplace and gain a competitive advantage. In this report by Financial Executives Research Foundation Inc. and Grant Thornton LLP, we highlight insights from in-depth interviews with senior-level executives. These organizations use advanced analytics in their businesses to gain significant profit improvements. See more at - http://gt-us.co/1vv2KU9
With a fundamental shift in the CFO mission, the finance function has become a critical change agent across organizations. The role of financial leaders such as CFOs is evolving, from a traditional financial controller, to one that drives performance improvements across the organization.
Emerging Technologies - The Future Of Finance (CIMA Feb 2019)Michael Sadler
A presentation by IBM on the topic of "The Future Of Finance" examining emerging trends, and how accountants can to prepare for the transition from "running the numbers" to being value-adding partners to the business.
The Future-forward CFO: Harnessing Generative AI in FinanceRNayak3
Explore how Generative AI in finance can drive advanced financial modeling, strategic risk assessment, conversational decision support and regulatory intelligence.
How to Bring About Finance Transformation on Your Own TermsWorkday, Inc.
In this deck, experts from PwC and Workday explain how finance leaders can use automation, artificial intelligence, and analytical skills to help their teams adapt to rapid change.
How Finance is driving growth in the Digital Age via OpenTextOpenText
In the digital age, finance business processes are shifting from batch to real-time, retrospective to predictive, and internally-focused to customer-centric. Innovative companies can drive growth by focusing on the revenue stream from an outside-in perspective. Learn more from OpenText at http://www.opentext.com/campaigns/rundigital/digitize-business/sap-finance/sap-finance-wod
The role of strategic planning, accounting information and advisors in the gr...Chris Catto
Slides for paper delivered at the Asia Pacific Management Accounting Association Conference, Bali Indonesia 2015.
The paper explores the relationship between Strategic planning, accounting information and the role of advisors in the growth of small to medium enterprises SMEs
Making Finance the Predictive Powerhouse | SlideShare | AccentureAccenture Operations
Today’s uncertainty has dialed up the pressure on Chief Financial Officers (CFOs) and their finance planning and analysis (FP&A) teams, who are now being asked to help businesses prepare for what’s next.
Making Finance the Predictive Powerhouse | SlideShare | AccentureAccenture Operations
Today’s uncertainty has dialed up the pressure on Chief Financial Officers (CFOs) and their finance planning and analysis (FP&A) teams, who are now being asked to help businesses prepare for what’s next.
Making Finance the Predictive Powerhouse | SlideShare | AccentureAccenture Operations
Today’s uncertainty has dialed up the pressure on Chief Financial Officers (CFOs) and their finance planning and analysis (FP&A) teams, who are now being asked to help businesses prepare for what’s next.
Emerging Trends in Accounting 08 Digital Transformation of Accounting-Big Data Analytics in Accounting-Cloud Computing in accounting- - Green Accounting-Human Resource Accounting, Inflation Accounting, Database Accounting
Insurance CFOs have stepped out from the confines of their role. Exploiting data and creating value, they can now serve as innovator and disruptor in their business.
The future of treasury is NOW. Corporate treasuries are to act as strategic advisors, participating in C-level decision making and leveraging digital technologies. Digital technologies will not only cut costs in treasury but significantly increase the productivity of the workforce. This session will introduce the emerging trends for innovative treasury as well as case studies in analytics, RPA, AI and more.
Presentación realizada por la Cra. Adriana Arosteguiberry, Tesorera General de la Nación de Uruguay.
El proyecto SIPREF forma parte del proceso de modernización y mejora de la gestión financiera pública de la Tesorería General de la Nación, aporta herramientas analíticas que permiten la explotación de la información de forma dinámica y en tiempo real.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
The cognitive CFO
1. The cognitive CFO
How “leaders” are increasing finance IQ IBM Institute for Business Value
2. How IBM can help
Finance Transformation and Performance Management solutions are
at the core of IBM financial management consulting services. Using
diagnostic and strategic tools for profit improvement and modeling,
IBM can help your enterprise assess its organizational design,
integrate financial functions, improve forecasting and reporting,
develop predictive capabilities, reduce risk and optimize the strategic
functions of the finance organization. IBM’s broad, integrated portfolio
of Financial Performance Management solutions helps companies of
all sizes automate and transform planning, reporting and analysis
processes, and helps anticipate performance gaps, analyze root
cause, assess alternatives and enable more effective decision-
making and execution. To learn more, please visit ibm.com/finance.
Executive Report
Finance Transformation and Performance Management
3. Overview
Enterprises face unprecedented challenges, and finance is at the epicenter. Increasing
business risk and volatility are evidenced by accelerating business disruption through
disintermediation, virtualization and technical innovation. As a result, new competitors,
changing business models and changing customer expectations have emerged. Pressure
on CFOs to enable enterprise agility and help their businesses make better decisions is
intensifying. Finance organizations must now proactively manage business growth and risk
through advanced, predictive analytics, creation of meaningful business partnerships and
curation and integration of enterprise data.
To do so, CFOs need to take advantage of cognitive computing — systems able to adapt
and learn — to make sense of the massive amount of data confronting them. Cognitive
exponentially increases the ability to digest vast amounts of data and infer potential insights
with much greater speed than human or traditional computing platforms. By significantly
expanding digital intelligence, cognitive technologies possess the ability to deepen and
augment human understanding. This can translate into better and quicker decisions to drive
innovation, improve operational efficiency and address capital investments.
To understand the degree to which executives see “real” opportunities to leverage cognitive
computing capabilities, the IBM Institute for Business Value, in collaboration with Oxford
Economics, surveyed more than 6,000 C-suite and heads of functions worldwide —
including 524 CFO respondents. The goal was to better understand and share how
executives assess how cognitive computing can help address pressing business challenges
and opportunities.
This report explores the CFO perspective on the potential use cases for, and benefits of,
cognitive computing. We found that top performers have established operational and
analytical uses for cognitive technologies and understand their value.
Preparing for cognitive
capabilities
For Chief Financial Officers (CFOs), it is no longer
enough to understand what has happened and apply
that to what might happen in the future. Economic
volatility and uncertainty, new competitors and
disruptive innovation highlight the need to more
quickly deepen and accelerate understanding of what
is going on. The application of cognitive computing
can help uncover previously unknown opportunities to
improve operational efficiency and create the potential
for faster profitable growth. In this executive report, we
look at what a small group of leading finance teams are
doing to ready themselves for the cognitive era.
1
4. State of cognitive computing in finance
Cognitive computing represents a new paradigm that can significantly enhance an
enterprise’s ability to synthesize vast amounts of structured and unstructured data, apply
machine-learning capabilities to the analysis of data and query results in natural language,
thereby enhancing analysts’ insights, efficiency and speed.
CEOs say finance is one of the
top-five investment areas for
cognitive computing
90% of surveyed outperforming
organizations agree they
are ready to adopt cognitive
technologies
Three times more outperformers
indicate they will implement
cognitive computing in finance
within two years
cog·ni·tive
adjective
Cognitive computing refers to next-generation information systems that understand,
reason, learn and interact. These systems do this by continually building knowledge and
learning, understanding natural language and reasoning, and interacting more naturally
with human beings than traditional programmable systems.
2 The cognitive CFO
5. According to Chief Executive Officers (CEOs), finance is one of the top-five investment areas
for cognitive computing (see Figure 1).1
With so much press about artificial intelligence, it is no
surprise that information technology and information security are the top areas, but these are
closely followed by customer service, human resources and finance. Surveyed CFOs believe
that cognitive computing can help them address challenges around decision-making,
especially in the quality and insights of reporting and analytics, as well as automation of
judgment-intensive activities. As a result, cognitive technologies can help finance organizations
bridge the gap between undiscovered opportunities and their current capabilities.
So where do finance organizations specifically want to invest in cognitive computing? In a
previous study, cognitive computing priorities for finance included operations improvement,
performance management and growth (see Figure 2).2
Figure 1
How CEOs rank cognitive computing investment priorities
Source: IBM Market Development Insights, Finance analytics and cognitive customer research, June 2016.
Information technology
Information security
Customer service
Human resrouces
Finance
50%
50%50%50%50%50%50%36%
37%
40%
44%
Finance is one of CEO’s top five investment
areas for cognitive computing
Source: IBM Institute for Business Value, “IBM Cognitive Computing
Survey,” 2016.
Note: Other areas not shown include innovation, manufacturing,
marketing, procurement, product development, risk, sales and
supply chain.
Operations
improvement
Performance
management Growth
Finance process
optimization
Expense
management
Order-to-cash
Compliance/
regulatory
Procurement
Management
reporting
Financial planning
and budgeting
Cash forecasting
Profitability/
margin analysis
Enterprise risk
management
Fraud, waste
and abuse
Revenue
forecasting
Mergers and
acquisitions
New products/
services identification
Pricing/promotion
optimization
35%
46% 37%45%
23%
18%
12%
38%
29%
28%
27%
25%
23% 24%
20%
Figure 2
CFOs prioritize cognitive computing across finance activities
3
6. To improve operations, 46 percent of surveyed respondents expect to invest in cognitive
computing for finance process optimization and 35 percent in expense management.
Cognitive computing has helped automate finance processes that deal with large amounts of
transactional data and complex decisions made by finance staff, who must select the best
option among several possible answers. Sophisticated pattern recognition techniques and
self-learning mechanisms can be used in expense management to identify and predict
expense-fraudulent activities more accurately. In addition, cognitive technologies can help
reduce costs through analysis of external market data in advance of travel to uncover the
lowest air fares and hotel rates.
Case study: Operations improvement – optimizing the
record-to-report close cycle4
For a media company, the close process was complex with:
• Resources from all the sub-processes involved in journal preparation and reconciliations
• Disparate distribution of workload among the team
• Lack of standard templates, process and uniform technology, resulting in errors
and escalations.
Cognitive computing provided an opportunity to interpret the large volume of data and
conduct process redesign to standardize and automate processes. Cognitive systems
helped recognize personnel who could do the same work faster and accurately and
recommended redistribution of workload. As a result, the company experienced a
reduction in turnaround time by 2.2 hours and a reduction in errors to less than 0.5
percent. There was also a 24-percent increase in efficiency, and the close process is
100-percent compliant with the Sarbanes–Oxley Act of 2002.
Advanced analytics (predictive/
prescriptive) versus cognitive systems3
Advanced analytics respond to specific
programmed coded requests to make
determinations and analyze predefined data based
on predefined parameters. Cognitive systems
interact with humans naturally to interpret data and
learn from virtually every interaction and propose
new possibilities through probabilistic reasoning.
Cognitive systems are trained but not programmed.
4 The cognitive CFO
7. To enhance performance, finance respondents said they plan to invest in cognitive technologies
for management reporting (45 percent) and financial planning and budgeting (38 percent).
Cognitive technologies have helped finance analyze data extracted across a large population of
management and financial reports. They have also enabled finance staff to quickly hone in on
elements of potential risk and gain deeper insights. With cognitive systems providing insight into
real-time changing market conditions from both internal and external sources, finance
professionals can update plans and budgets with the most current information.
Case study: Performance management – improving forecasting5
For a large pharmaceutical company, cognitive technologies help understand the precise
impact of market forces on the company’s market share. Machine-learning algorithms
model the dynamics of the system and how various market forces interact. The system
self-learns over time as the market evolves. Cognitive systems predict the impact of
competitive events on market share driven by efficacy, brand value, spend and other
variables. New sentiment from unstructured sources is also brought into modeling and
enables complex scenario planning, such as dosage changes and competitive actions.
The result is market-share predictions with more than 99-percent accuracy and less than
1-percent deviation of annual forecast against actual for a blockbuster drug.
5
8. Thirty-seven percent of respondents said they will invest in cognitive systems for revenue
forecasting, and 23 percent said they will do so in mergers and acquisitions, with the primary
objective of improving profitable growth. Cognitive computing can help provide insight into
real-time customer attitudes and their impact on an enterprise’s revenues. It could be used to
analyze customer conversations on social media, present the top-trending products and
services, describe the underlying drivers of each trend and provide foresights into whether the
trend will rise, fall or plateau over time. In mergers and acquisitions, executives could ask in
real-time for acquisition targets based on a set of company characteristics. Cognitive systems
could suggest potential candidates and perform in-depth analyses, as well as rank targets to
highlight value and synergistic opportunities, visualize trade-offs and explore what-if scenarios.
Case study: Growth – Identifying hidden drivers of demand6
A retailer wanted to find hidden relationships between external events and consumer
behavior. Although it had robust internal sales data, the company lacked an automated
way to account for and interpret external events that could help explain sales fluctuations
or deviations from forecasts. Machine-learning algorithms mine what is important for
each product at each location. An intelligent analytical model was developed that
evaluates more than 1,000 variables across seven categories (such as economic events,
consumer, weather, competitors). The model quantifies the impact of abnormal events on
normal sales trends across individual product categories. These “signals” are used in an
array of forecasting models to identify sales anomalies. As a result, product is forward
deployed using numerical optimization techniques, driven by the signals sent in the
exception forecast. The supply chain operates with a new “intelligence” to keep costs low.
6 The cognitive CFO
9. Finance leaders articulate value from cognitive
How can finance organizations use cognitive computing to capitalize on new capabilities?
To help answer this question, we used survey results to identify a small group of finance
outperformers – 14 percent of study participants. This group self-reported that they have
significantly outperformed on revenue growth over the past three years and have been
significantly more efficient and profitable.
By learning from these leaders, other finance organizations can understand the potential
to excel in the cognitive era. They can begin to:
• Create a culture for cognitive
• Build a cognitive data foundation
• Focus on skills and staffing.
Creating a culture for cognitive
Our survey indicates that organizations embracing cognitive tend to be “bolder,” more agile
and have a higher appetite to move first and innovate. They are more likely than others to
embrace learning and the science of insight, as well as foster a culture where that knowledge
is infused into decision making. These firms say they are confident their organizations are
ready to embrace a cognitive future. Ninety-seven percent of outperformers say they believe
that cognitive computing is market-ready. Ninety percent of these leaders indicate their
organizations are ready to adopt cognitive computing, compared to 59 percent of all others
(see Figure 3).
Cognitive computing
is mature and
market-ready
97% 57%
1.5Xmore
Our organization is
ready to adopt
cognitive computing
90% 59%
Outperformers All others
1.7Xmore
Figure 3
Finance outperformers embrace the science of cognitive
Source: IBM Institute for Business Value, “IBM Cognitive Computing
Survey,” 2016.
7
10. The potential to improve enterprise agility and expand the speed, insights and capability of
organizations presents significant opportunities. Finance outperformers say they expect to
use cognitive technologies to reap rewards in specific activities in operations improvement,
performance management and growth. In operations improvement, our study shows that
outperformers say they recognize that cognitive computing can improve efficiency in order-
to-cash (75 percent of outperformers versus 39 percent of peers) and regulatory and
statutory monitoring/compliance/reporting (48 percent of outperformers versus 22 percent
of peers) and improve effectiveness in procure-to-pay (59 percent of outperformers versus
34 percent of peers). Cognitive technologies can provide data mining, pattern recognition
and natural language processing to mimic the human brain’s processes of buying goods
and services.
In performance management, outperformers indicate that cognitive computing can reduce
risk and increase insights. Sixty-six percent of outperformers say that cognitive technologies
can help them reduce risk in treasury/cash management, versus 40 percent of all others.
Cognitive systems can help provide analysis into various drivers, such as seasonality, trends,
social media and more to increase cash forecasting accuracy. And 60 percent of outperformers
say they believe that cognitive computing will increase performance insights for strategic and
operational planning, budgeting and forecasting, versus 40 percent of all others. Cognitive
technologies can provide visibility into real-time changing market conditions to help update
plans and budgets.
8 The cognitive CFO
11. For growth, 65 percent of outperformers say they believe cognitive technologies will help
them improve decision-making in evaluating mergers and acquisitions opportunities, versus
33 percent of all others. In addition, 57 percent of outperformers say that cognitive systems
can assist in reducing risks around supporting organic growth strategies, versus 34 percent
of all others. For example, cognitive computing could analyze diverse types of customer data
in finding personality insights/types/segments to help price products and services and run
campaigns and promotions effectively.
Given the potential benefits, we believe, based on our study results, that finance outperformers
are more likely to adopt cognitive computing sooner than their peers – compared to others
in our study, three times more outperformers indicate they will implement cognitive within
two years.
Course of action:
Adopting a mindset that embraces the science of cognitive computing is a key step in the
journey. It includes a willingness and a commitment to infuse insight into decision-making.
Setting an enterprise-wide cognitive strategy can help provide direction and establish
specific actions for integration across the CEO priorities of information technology,
information security, customer service, human resources and finance.
Cognitive solutions are well-suited to a defined set of challenges in which humans and
existing technologies cannot properly and quickly synthesize and uncover unknown high-
impact opportunities. As a result, CFOs need to pinpoint a small number of high-value
functions where cognitive technologies can play a role. Areas of interest might include those
that today take humans an inordinate amount of time to seek timely answers and insights from
various information sources, requires ranked responses to questions and queries and that
can leverage new data sources to improve decision-making capabilities.
9
12. The order-to-cash area is a good example. In collections, a customer 360-view-based risk
assessment, using structured and unstructured data from different systems, can be created
with cognitive systems. In dispute/deduction management, cognitive technologies can be
used to identify and allocate queries from customers that come through email (unstructured)
and workflow (structured). The technology can also provide a query agent a complete
statistics view on risk associated with a customer, as well as how much accounts receivables
are open for collection.
We believe organizations should start the cognitive journey by identifying the uses cases and
associated benefits provided by cognitive computing. The order-to-cash cognitive computing
example for collections provides cash flow benefits. Cognitive dispute management can lead
to improved productivity.
Building a cognitive data foundation
Finance has historically used huge amounts of financial transaction data — often challenging
and time consuming. But now, a tsunami of data comes from different sources, such as
external market-centric data, competitive data, macro-economic data, social media and
weather data. And this non-financial data needs to be integrated with the financial data to
create new insights. With traditional methods of enterprise-resource-planning systems,
spreadsheets and online analytical processing (OLAP) tools, these challenges will be
exacerbated. It, therefore, becomes imperative that a modern data architecture has the ability
to ingest and digest the 4Vs of data (volume, variety, velocity and veracity) from both internal
and external sources, and then integrate that data into enterprise processes.7
The need for
these capabilities is amplified in the cognitive era (see Figure 4).
10 The cognitive CFO
13. Traditional Cognitive
Information
elements
• Finance transactional
• Volumetric/statistical
• Social
• Demographic
• Economic
• Meteorological
Information types • Structured
• Rule-based (GAAP, IFRS)
• Unstructured
Information time
horizon
• Periodicity
• Quarterly, yearly historic
• 12-month planning
• Real-time
• Predictive
Information lead
times
• SEC calendar driven • Immediate
• Anticipatory
Information uses • Historic
• Explanation/attribution
• Strategy development and adjustment
• Revenue growth
• Anticipate events
Source: IBM Global Business Services.
Figure 4
Cognitive computing has a dramatic impact on enterprise information demands
11
14. Our study shows that finance outperformers outpace their peers in the adoption of the
components needed for a modern data infrastructure. These leaders have indicated they
have invested twice as much as others in cloud-based data storage or analytics services,
streaming data acquisition, shared operational information, data curation services and
distributed storage and processing (see Figure 5). In addition, 56 percent of finance
outperformers say they have implemented or plan to implement data digitization to
support cognitive computing.
Source: IBM Institute for Business Value, “IBM Cognitive Computing Survey”, 2016.
Figure 5
Finance outperformers indicate they outpace all others in their adoption of the components needed for a
modern data ecosystem
Cloud-based data
storage or analytics
services
70% 33%
Distributed storage
and processing
platform
67% 29%
Data curation
services
67% 32%
Outperformers All others
Streaming data
acquisition and
analysis
64% 30% 54% 25%
Shared operational
information
2.1Xmore 2.2Xmore2.1Xmore 2.2Xmore2.3Xmore
12 The cognitive CFO
15. Cognitive systems can ingest and provide a wide variety of data sources, both internal and
external to the organization. CFOs recognize a combination of financial and non-financial data
as critical to accelerate the uncovering of new analytical insights. Cognitive systems are well-
suited to handle large volumes of mixed data types. Most CFOs in our study say the most
important data sources to finance are finance transactional systems, customer profiling/
segmentation, workforce data and supply-chain data. Data from our study reveals that
outperformers are additionally focused on leveraging more external data (see Figure 6).
Mobile application
data
59% 35% 56% 44% 54% 43%
Outperformers All others
Social media Customer-
generated data
1.7Xmore 1.3Xmore1.3Xmore
Source: IBM Institute for Business Value, “IBM Cognitive Computing Survey”, 2016.
Figure 6
Finance outperformers leverage external data
13
16. Course of action:
Most organizations indicate they do not have the data infrastructure needed to support
cognitive systems. By improving the ability to rapidly ingest new data, curate integrated
information and analyze that data to gain insights and deploy new capabilities at a reduced
cost, finance can provide the partnering that the business demands and requires.
Data digitization is a critical part of taking advantage of cognitive computing. It is the
process by which physical or manual records, such as text, images, video, and audio,
are converted into digital forms. This is particularly important for “document-” and
“unstructured-data” heavy processes, such as order-to-cash, to convert remittance advice
received from customers that is in different forms, such as email, fax, PDF files, and pictures,
into structured data.
Cognitive systems create opportunities to expand the sources of data and more quickly
ingest, process and draw inferences from the information. Structured data can be augmented
with new sources of unstructured data or information from external sources. Cognitive
systems can support ingesting and analyzing mobile, social and customer-related data.
As a result, finance organizations can leverage both internal and external data to help address
market changes and improve their operations, thereby contributing to understanding
customers better, leading to improving the customer “experience.”
14 The cognitive CFO
17. Focusing on skills and staffing
With a deluge of data, organizations need a clarity of vision around the data — who owns it,
what it means and how it should be managed. Outperformers drive clear data governance
through a Chief Data Officer (CDO) or an equivalent position — a peer to the CFO. The CDO
is a business leader who defines, develops and implements the strategy and methods by
which the organization acquires, manages, analyzes and governs data. Sixty-one percent
of outperformers have a CDO, versus 45 percent of their peers. In addition, the CDO is
supplemented by a business-driven information-governance committee — 47 percent of
outperformers have a governance committee, compared to just 26 percent of all others.
Leaders in our study have adopted the use of centers of excellence for analytics/cognitive
computing 53 percent more than their peers. This helps create service scalability. In terms
of scope, a previous IBM Institute for Business Value study identified that outperformers are
holistically placing many finance activities into a center to focus on growth, manage risks and
improve efficiency.8
Activities include finance process optimization, revenue forecasting,
enterprise risk management, pricing and promotion optimization, fraud, waste and abuse
and new products/services identification.
15
18. With the transition to cognitive computing, outperformers realize they need “new-collar” skills
and talent necessary to move forward. The leaders are targeting specific skills: statisticians,
the best data analysts, data visualization specialists, advanced mathematical modelers and
big data-related information management specialists (see Figure 7).
Source: IBM Institute for Business Value, “IBM Cognitive Computing Survey”, 2016.
Figure 7
Finance outperformers have the new skills to support analytics and cognitive computing
Advanced data
analysis skills
63% 51% 51% 38% 50% 28%
Outperformers All others
Data visualization
skills
Advanced
mathematical
modeling skills
1.2Xmore 1.8Xmore
43% 31%
Big data-related
information
management skills
1.4Xmore1.3Xmore
16 The cognitive CFO
19. Course of action:
Organizations can accelerate their cognitive journeys by putting in place strong data
management at the enterprise level to complement CFO leadership. A CDO and business-
driven governance system creates enterprise-wide data commonality, lineage and
transparency. This commonality aligns with common finance data definitions and a standard
financial chart of accounts.
Finance organizations should aggregate analytics and cognitive skills to make the best use
of economies of scale. The scope should include activities targeting revenue growth and risk
management.
CFOs will also need to assess the impact of cognitive on jobs and augment in-house talent.
Finance organizations should seek talent to diversify their existing teams — analytic breadth,
data skills and modelling specialists. Organizations need to think strategically and seek
candidates — whether acquired or hired — whose skills vary from those within their teams.
17
20. Are you ready to start using cognitive
technologies?
As you consider the introduction of cognitive into your finance organization, think about these
key questions:
• Which areas within finance do you think could benefit from cognitive computing and what
can you do to get rapid paybacks?
• What is your plan to encourage and support profitable growth, including rapid expansion
of how you can leverage cognitive technologies?
• How effective is your organization in bringing together data from various sources to make
decisions?
• How can your organization collaborate to implement cognitive technologies?
• What new skills or competencies would be required to take advantage of cognitive
computing?
18 The cognitive CFO
21. For more information
To learn more about this IBM Institute for Business
Value study, please contact us at iibv@us.ibm.com.
Follow @IBMIBV on Twitter, and for a full catalog of our
research or to subscribe to our monthly newsletter,
visit: ibm.com/iibv.
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Global Business Services, develops fact-based,
strategic insights for senior business executives on
critical public and private sector issues.
524
respondents
Automotive
Banking and Financial Markets
Chemicals and Petroleum
Consumer Products
Education
Electronics
Energy and Utilities
Government
Healthcare
Industrial Products
Insurance
Information Technology Services
Life Sciences/Pharmaceuticals
Media and Entertainment
Retail
Telecommunications
Transportation
Travel
9%
15%
5%
2%
7%
3%
4%
7%
4%
4%
6%
3%
3%
9%
6%
5%
3%
5%
CFO survey firmographics
Study approach and methodology
In cooperation with Oxford Economics, the IBM Institute for Business Value surveyed 6,050
global executives representing 18 industries, including leaders of government departments
and educational institutions. Roles of responding executives included major C-suite members
— CEOs, CMOs, CFOs, CIOs, COOs and CHROs — as well as heads of customer service,
information security, innovation, manufacturing, risk, procurement, product development and
sales. There were 524 CFO respondents who participated in the study (see Figure 8).
Source: IBM Institute for Business Value, “IBM Cognitive Computing Survey”, 2016.
Figure 8
Firmographics of CFO respondents
19
22. Authors
William Fuessler leads the Global Finance, Risk, and Fraud practice for IBM Global Business
Services. The practice helps clients transform the finance function to be more strategic,
address new risks and challenges, and drive enterprise-wide profit improvement
by fighting fraud. His client experience includes numerous finance transformation projects,
including process redesign, enhancing data consistency, developing target operating models
and advanced analytics. Under his leadership, the IBM 2010 CFO Study, “The New Value
Integrator,” 2014 CFO Study, “Pushing the Frontiers” and 2016 CFO Study, “Redefining
Performance,” shared the future of the finance organization. He can be reached at
william.fuessler@us.ibm.com.
Spencer Lin is the Global CFO Lead for the IBM Institute for Business Value. In this
capacity, he is responsible for market insights, thought leadership development, competitive
intelligence, and primary research on the CFO agenda and trends. Spencer has a
combination of financial management and strategy consulting experience over 20 years,
with extensive experience in finance transformation, strategy development and process
improvement. He was a co-author of the last five IBM Global CFO Studies. Spencer can be
reached at spencer.lin@us.ibm.com.
Carl Nordman is the Director of the Global C-suite Study Program in the IBM Institute for
Business Value. He is responsible for conducting primary research on current and emerging
strategic trends through the lens of the executive suite and board room. The C-suite program
scope spans over 100 countries, 20 industries and 6 Executive roles and conducts research
continuously throughout the year. Carl has 25 years of experience in finance, consulting and
thought leadership, primarily in financial services with an emphasis on corporate functions
such as finance, supply chain, IT and marketing. He was a co-author of the 2016 and 2010
IBM Global CFO Studies. He can be reached at carl.nordman@us.ibm.com.
Acknowledgments
Brian Goehring, Global Cognitive Lead,
IBM Institute for Business Value
20 The cognitive CFO