By combining the statistical and mathematical rigor of advanced analytics with established business acumen and domain experience, retailers can ferret out and reduce shrinkage caused by fraud, non-compliance, poor processes and organized crime.
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.
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.
Organisations spend heavily on technology, people skills and consulting to understand billions of bits of data, but they still lack clear visibility and insight.....
This whitepaper is geared to help
bank marketing professionals
understand the scope of marketing
analytics and also on how it can
contribute value to the various
factions of a bank’s marketing
activities.
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.
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.
Organisations spend heavily on technology, people skills and consulting to understand billions of bits of data, but they still lack clear visibility and insight.....
This whitepaper is geared to help
bank marketing professionals
understand the scope of marketing
analytics and also on how it can
contribute value to the various
factions of a bank’s marketing
activities.
This is an interesting paper providing insight on the utilization of data for Asset Managers that you might find useful and informative. We are happy to schedule direct one on one discussions, as you wish.
MindStream Analytics is a leading consulting firm focused on helping clients improve business understanding and decision making. With years of experience in the analytics and Business Performance Management area, MindStream offers services ranging from software selection and implementation to best practices for financial planning.
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
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
The presentation aims at understanding how analytics can be used and adopted in finance divisions of an organisation to aid effective decision making of the organisation.
Importance of High Availability for B2B e-CommerceSteve Keifer
This white paper explains how B2B e-Commerce technologies have become so critical to manufacturing and retail companies that further investment is required in high availability architectures.
Business analytics is a custom of transforming the data into business understandings enabling the end users for better decision-making. By using the modern tools and techniques, business analytics can help assess complex situations, consider all the available options, and predict outcomes and showcase critical risks for the decision makers.
Business Analytics can simply be described as a practice that includes the use of various techniques such as Data warehousing, Data mining, Programming in order to visualize and discover several patterns or trends in data. In simple, Analytics help convert the data into useful information, which can be used for decision-making. As a means of sorting through data to find useful information, the application of analytics has found new purpose
In the business of money, there can be no errors. That goes doubly so for keeping your customers. With PNA's finance data analytics, discover the hidden patterns that customers give you, and learn the language needed to retain them.
Make Intelligent Decisions that Drive Business Value
Improving profitability is one of the highest priorities for business managers. The challenge is to identify and analyze profit-making activities by specific dimensions such as customers, products, channels, segments, and business units. Accurate data helps drive continuous profit improvement initiatives by helping businesses understand where and how to improve profitability.
The results can be staggering. Companies that leverage cost analytics
to focus on cost reduction can experience reductions of 3–5%, while those that focus on profitable growth and revenue initiatives can achieve 5–15% improvements. For example, a $4 billion financial services
firm added $600 million in annual profit enhancement by focusing on profitable growth and revenue rather than cost containment.
Longview Profitability Analytics leverages your company’s data to provide powerful insight into revenues, business costs, margins, and operations to help you develop profitable action plans.
Data and analytics allow organizations to use intelligence from feedback to tailor offerings that improve customer satisfaction.
B2B are gaining the most since they are able to share data that directly strengthens their relationship.
Decision Analytics: Revealing Customer Preferences and BehaviorsLarry Boyer
This presentation was given at the World Economic Outlook Conference on 22 October 2009 as an introduction to decision analytics and predictive modeling and how it could be applied predicting the decisions of individuals, rather than aggregates, of people. This was before the days of Big Data and Hadoop so the possibilities are even greater today.
Of particular note in this presentation are the slides illustrating the additional power of adding local economic information to an analysis rather than relaying on more aggregate economic information. Small scale, local changes in the economy will influence consumer behavior and it's important to know that when launch products and setting prices, for instance.
Please share your comments.
The true cause of $17 billion cold chain shrink slide shareZest Labs
An overview of share shrink/waste occurs in the food cold chain and how retail grocers can proactively manage inventory and quality to improve customer satisfaction and profitability.
This is an interesting paper providing insight on the utilization of data for Asset Managers that you might find useful and informative. We are happy to schedule direct one on one discussions, as you wish.
MindStream Analytics is a leading consulting firm focused on helping clients improve business understanding and decision making. With years of experience in the analytics and Business Performance Management area, MindStream offers services ranging from software selection and implementation to best practices for financial planning.
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
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
The presentation aims at understanding how analytics can be used and adopted in finance divisions of an organisation to aid effective decision making of the organisation.
Importance of High Availability for B2B e-CommerceSteve Keifer
This white paper explains how B2B e-Commerce technologies have become so critical to manufacturing and retail companies that further investment is required in high availability architectures.
Business analytics is a custom of transforming the data into business understandings enabling the end users for better decision-making. By using the modern tools and techniques, business analytics can help assess complex situations, consider all the available options, and predict outcomes and showcase critical risks for the decision makers.
Business Analytics can simply be described as a practice that includes the use of various techniques such as Data warehousing, Data mining, Programming in order to visualize and discover several patterns or trends in data. In simple, Analytics help convert the data into useful information, which can be used for decision-making. As a means of sorting through data to find useful information, the application of analytics has found new purpose
In the business of money, there can be no errors. That goes doubly so for keeping your customers. With PNA's finance data analytics, discover the hidden patterns that customers give you, and learn the language needed to retain them.
Make Intelligent Decisions that Drive Business Value
Improving profitability is one of the highest priorities for business managers. The challenge is to identify and analyze profit-making activities by specific dimensions such as customers, products, channels, segments, and business units. Accurate data helps drive continuous profit improvement initiatives by helping businesses understand where and how to improve profitability.
The results can be staggering. Companies that leverage cost analytics
to focus on cost reduction can experience reductions of 3–5%, while those that focus on profitable growth and revenue initiatives can achieve 5–15% improvements. For example, a $4 billion financial services
firm added $600 million in annual profit enhancement by focusing on profitable growth and revenue rather than cost containment.
Longview Profitability Analytics leverages your company’s data to provide powerful insight into revenues, business costs, margins, and operations to help you develop profitable action plans.
Data and analytics allow organizations to use intelligence from feedback to tailor offerings that improve customer satisfaction.
B2B are gaining the most since they are able to share data that directly strengthens their relationship.
Decision Analytics: Revealing Customer Preferences and BehaviorsLarry Boyer
This presentation was given at the World Economic Outlook Conference on 22 October 2009 as an introduction to decision analytics and predictive modeling and how it could be applied predicting the decisions of individuals, rather than aggregates, of people. This was before the days of Big Data and Hadoop so the possibilities are even greater today.
Of particular note in this presentation are the slides illustrating the additional power of adding local economic information to an analysis rather than relaying on more aggregate economic information. Small scale, local changes in the economy will influence consumer behavior and it's important to know that when launch products and setting prices, for instance.
Please share your comments.
The true cause of $17 billion cold chain shrink slide shareZest Labs
An overview of share shrink/waste occurs in the food cold chain and how retail grocers can proactively manage inventory and quality to improve customer satisfaction and profitability.
Metro Group, German's leading retailer, aims to optimize its supply chain performance with RFID. The initial results are satisfactory, and right now the company arrives at a new question: Expand the already-proven pallet tagging, or increase the granularity with case-level tagging?
* Understand the financial components of business
* Identify the levers that affect profitability
* Relate your personal finances to business finances
* Make more profitable decisions
A Situational Leadership Workshop. Based on the Hersey - Blanchard Model and the Blake and Mouton’s Leadership Grid this workshop introduces the concepts of how leadership style can be matched to situational factors - in this case follower readiness.
Practical approach to the situational leadership. Vadim NareykoVadim Nareyko
Presentation from the training "Management Psychology. Practical approach to the situational leadership". Vadim Nareyko. 2014
Contents:
- 4 types of leadership styles
- 4 types of individual style
- 3 meta-programs
- 4 levels of competence
- 3 types of service companies
Presentation materials on a business model framework used as part of a course on business acumen offered at the University of Wisconsin Center for Professional and Executive Development.
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.
Business is running ever faster—generating, collecting and using increas-ing volumes of data about every aspect of the interactions between sup-pliers, manufacturers, retailers and customers. Within these mountains of data are seams of gold—patterns of behavior that can be interpreted, classified and analyzed to allow predictions of real value. Which treat-ment is likely to be most effective for this patient? What can we offer that this particular customer is more likely to buy? Can we identify if that transaction is fraudulent before the sale is closed?
The banking industry is data-demanding with acknowledged ATM and credit processing data. As banks face increasing pressure to stay successful, understanding customer needs and preferences becomes a critical success factor. Along with Data mining and advanced analytics techniques, banks are furnished to manage market uncertainty, minimize fraud, and control exposure risk.
Effective demand planning - our vision at SolventureSolventure
As Solventure we proud ourselves of being experts in designing and implementing Sales, Inventory and Operations Planning.
Companies that have a good SiOP process can’t imagine how to live without it. It is the key instrument for the CEO to navigate the business along the budget towards its strategic targets. Demand Planning plays an important role in every SiOP process and is key to to make it successful.
This white paper, Effective Demand Planning, summarizes the vision we have distilled from the many projects we have done over the last 10 years.
Consumer analytics is the process businesses adopt to capture and analyze customer data to make better business decisions via predictive analytics. It is a method of turning data into deep insights to predict customer behavior. It may also be regarded as the process by which data can be turned into predictive insights to develop new products, new ways to package existing products, acquire new customers, retain old customers, and enhance customer loyalty. It helps businesses break big problems into manageable answers. This paper is a primer on consumer analytics. Matthew N. O. Sadiku | Sunday S. Adekunte | Sarhan M. Musa "Consumer Analytics: A Primer" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33511.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/33511/consumer-analytics-a-primer/matthew-n-o-sadiku
How Are Data Analytics Used In The Banking And Finance Industries.pdfMaveric Systems
amplify business success. Today, banks want more than incremental gains. They want datadriven revenue breakthroughs. Banks increasingly rely on data. It’s the future of communication
Similar to Predictive Response to Combat Retail Shrink (20)
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.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
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- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
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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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Predictive Response to Combat Retail Shrink
1. Predictive Response to Combat
Retail Shrink
By combining the statistical and mathematical rigor of advanced
analytics with established business acumen and domain experience,
retailers can ferret out and reduce shrinkage caused by fraud, non-
compliance, poor processes and organized crime.
Executive Summary
Shrink, the unaccounted for inventory or cash
lost in the retailer value chain, is among the key
sore points in the retail industry. Retailers have
used electronic article surveillance, reporting
systems and a plethora of processes and policies
to identify the biggest opportunities to control
shrink. Yet most of these methods are reactive
and tend to be inefficient, cost-wise. Rudimentary
methods of shrink management have led retailers
to consider or undertake more costly approaches.
At the same time, the sluggish economic recovery
has forced these businesses to reduce headcount
and do more with less. Not surprisingly, there is
a growing need to utilize available data assets
more effectively by building capabilities to more
accurately report, analyze and predict shrink.
Analytics can help augment retailers’ abilities to
interpret vast amounts of seemingly unrelated
data from various sources and transform it into
concise, actionable intelligence. This can enable
retailers to become more proactive in countering
shrink before it becomes a huge issue and dra-
matically impacts the bottom line. To take shrink-
reduction programs to the next level, retailers
must improve their business intelligence (BI)
capabilities and embrace predictive analytics.
An enterprise-wide information system that
analyzes data to uncover and predict trends can
help these companies increase revenue, reduce
costs, improve processes and make quicker and
more informed strategic decisions to detect and
prevent shrink. Analytics provides a fresh way
• Cognizant 20-20 Insights
cognizant 20-20 insights | july 2013
Quick Take
• US$119 billion: Estimated global shrink.
• 1.45%: 2011 global shrink rate;
up 6.6% from 2010.
• US$28.3 billion: Money spent globally
on loss prevention (LP) in 2011.
• US$200: Global cost of shrink per family.
Source: Global Theft Barometer 2011
The Cost of Shrink
2. 2
for retailers to effectively utilize available loss
prevention (LP) personnel and resources, and
help them do more without increasing costs.
Retailers have been “thinking” about using
analytics for effective shrink reduction for too
long; the time has come to use the gold mine
of data that exists within their organization and
explore the opportunities that it unravels.
The Old Adage: Increase Spending
to Reduce Shrink
In a 2011 report, RSR Research found that the
most common inhibitors to loss prevention (LP)
initiatives are cost and return on investment (ROI)
(see Figure 1). And according to a recent white
paper by Professor Joshua Bamfield, Director of
the Centre for Retail Research, retail shrink has
a very strong relationship with money spent to
counter it (see Figure 2).1
This is in line with one of
the common retail notions that shrink reduction
is a costly proposition. While this is true, retailers
need to start looking at ways to overcome this
obstacle.
Retailers are not just threatened by shrink alone;
they also face the exorbitant costs of countering
shrinking.2
To avoid this double jeopardy, retailers
need to invest in better technologies that can help
reduce shrink while not undermining an organiza-
tion’s bottom line.
Current Challenges: Too Much to Do
Figure 3 (next page) illustrates the four broad
categories of retail shrink and the multitude of
challenges retailers face in identifying its root
cause and developing a plan for reducing it. Tradi-
tional strategies that retailers follow are what we
refer to as the “shrink cycle” (see Figure 4, next
page). The shrink cycle starts with identifying
potential shrink (typically conducted via periodic
physical counts); analyzing the data manually
to identify issues; further analyzing the issue
to identify the root causes; implementing the
measures to fix the root cause, then validating
the results until the next physical counts in hopes
of seeing positive results.
The time required to complete the whole shrink
cycle is typically three to six months, which in
today’s dynamic retail world is way too long. This
is also evident in the 2011 RSR Research, where
‘”lack of staff to review LP and audit data” was
cited by retailers as the third biggest inhibitor to
countering shrink.
How Analytics Can Help
Over the years, retailers have focused their
investments on gathering data for analysis
purposes; now, they face the increasingly difficult
challenge of analyzing data and putting it to good
use. By doing so, retailers can break the pattern
of increasing LP spend to combat ever-increasing
shrink dollars. Analytics can help retailers solve
this problem and benefit in many ways:
• Reduce the time required to identify the root
causes of shrink.
• Provide actionable data for preparing effective
remediation plans.
• Provide factual data to develop effective
strategies for utilizing resources in an efficient
manner.
• Use predictive analytics to track the effect of
remediation plans in near real time and react
much faster than previously possible.
cognizant 20-20 insights
Source: RSR Research, February 2011
Figure 1
Organizational Inhibitors
Expense
Can’t prove
the ROI
Lack of staff
to review LP
and audit data
2011 2010
79%
86%
66%
53%
54%
41%
Source: Centre for Retail Research
Figure 2
LP Spending and Shrinkage
2001-2010 Europe
31000
30000
29000
28000
27000
26000
25000
24000
23000
5500 6000 6500
LP Spending
Shrinkage
7000 7500
3. Developing an Effective Analytical Response
Getting to the end state where retailers can
predict shrink is a long process; it requires a
change in thinking, as well as the focus and
support of senior management. We recommend
a four-phase approach to reach the end goal (see
Figure 5, next page).
• Phase 1: Building the foundation. Today, most
retailers have started building the foundation
as they collect volumes of data about various
activities by customers, vendors or employees.
However, retailers face major challenges in
making sense of this data, which is critical
to predicting and combating shrink. A strong
foundation will include clean, consistent and
complete data from across the organiza-
tion, such as transactional data related to
inventory movement; financial data related to
inventory movement; master data associated
with product, location, employees and loss
prevention; and data elements like crime rates
and employee theft rates, for example. It’s
quite surprising that in today’s information
age, retailers still struggle with the challenges
posed by siloed information. To build a strong
foundation, retailers need to break down these
silos and bring all meaningful data onto a
common platform.
3
cognizant 20-20 insights
Figure 3
Categorizing Shrink
• Intentional malpractices committed
internally (by staff), externally (by
customers/suppliers) or collusions
between these entities.
• Each event accounting for a
small amount of money.
• Dishonesty at work.
• Administrative/operational
mistakes committed by the
retailer’s staff.
• Small amounts involved and
are mostly involuntary events.
• Actions performed by staff that does
not comply with the company’s rules
or best practices, resulting in loss for
the company.
• May result from lack of
knowledge/knowhow on the
rules established.
• Lack of standardization of policies.
• Professional activity to steal and sell
merchandize.
• Large amount, less frequent events,
typically in a short duration of time.
Fraud
Processes
and Policies
Organized
Retail Crime
Non-
compliance
Figure 4
The Path To Shrinkage Foresight
Foundation
Benchmark
Advance
Analytics
Optimize
P
r
o
g
r
e
s
s
i
v
e
l
y
s
h
o
r
t
e
n
i
n
g
S
h
r
i
n
k
C
y
c
l
e
Capture
Transactional Data
Reporting & KPI
Development
Advance Analytics
• Develop linear regression models to predict shrink
• Enhance and improve the modeling tools by incorporating
additional shrink variables
Analytics and Exception Reporting
• Run standard analytics by slicing and dicing the data
• Gather intelligence around factors affecting shrink
• Use developed KPI’s to identify exceptions
• Generate exception reports
Reporting & KPI development
• Generate periodic reports based on the collected data
• Develop KPIs to measure the performance against acceptable standards
• Sample KPIs should include transaction voids, damage claims, unauthorized,
discounting, suspended transactions and price override
Capture Transactional Data
• Capture and maintain accurate inventory data
• Capture all exceptional events
• Define strong processes around all store transactions
Predictive
Shrink
Analytics &
Exception
Reporting
Develop
Insight
4. 4
cognizant 20-20 insights
• Phase 2: Understanding data and developing
internal benchmarks. Over the last few years
retailers have begun to track and measure
key performance indicators (KPIs). KPIs are
a good way to aggregate data, and compare
and benchmark against industry standards.
KPIs provide retailers with a “data lens”
through which they can monitor processes in
an effective manner. Looking at processes in
this way gives retail organizations an initial
understanding of where the company stands,
which can then be used for establishing goals
and planning for the future.
However, planning based
on KPIs is fairly reactive in
nature.
Building KPIs is the first step
in reducing the time from
identification of shrink to
identifying the issues. KPIs
can easily help identify
the products, departments
and stores that are causing
more shrink than others. A
retailer trying to develop the
right KPIs should identify
the process that needs to be monitored, then
confirm specific KPIs to monitor. For example, to
monitor issues related to vendor credits, retailers
should look at KPIs such as credits-to-purchase
and credits-to-sales ratios for each vendor, at
each location, at each SKU level. These KPIs can
then be rolled up or down at different levels for
effective analysis.
• Phase 3: Developing insight. The fact that
many retailers now use business intelli-
gence tools represents great progress for the
industry. For instance, retailers now use BI
tools and active monitoring of exceptions at
receiving and cash registers. These tools have
provided retailers with insights that can be
used to respond and control shrink.
However, the potential of these tools is still
not tapped completely. More often than not,
they are being used by retailers for creating
static reports with huge volumes of data. Our
experience has shown that there are many
better ways to utilize BI tools. Rather than
creating huge statistical reports listing various
activities and metrics, retailers can use BI
tools to build actionable dashboards. Such
dashboards can be built to utilize analytics for
spotting common trends across products and
stores, or to provide limited, actionable and
meaningful information for the field teams
For example, while researching issues related
to vendor credits, an analytical application can
easily compare credit rates across different
stores and vendors and create a list of outliers.
The LP analyst can then work with field teams
to identify specific issues and create an
action plan.
Using analytics reduces the time needed
to identify the occurrences of shrink and
the reasons behind them. However, a lag
remains in gathering data and then analyzing
To monitor issues
related to vendor
credits, retailers should
look at KPIs such as
credits-to-purchase
and credits-to-sales
ratios for each vendor,
at each location, at
each SKU level.
Quick Take
• Collect every data set related to
inventory and financial transactions
at the most granular level.
• Document all processes which relate
directly or indirectly to shrink.
• This data is of paramount importance,
no analysis or model can work on
incomplete or inaccurate data.
Shrink Cheat Sheet (Part I)
Quick Take
• Connect data elements with various
processes.
• Look at various processes through the
“data lens.”
• Use collected data and process
mapping for developing benchmarks/
KPIs for each shrink-related process.
Understand data and develop the
right benchmarks to move to the next
level of developing insight.
Shrink Cheat Sheet (Part II)
5. cognizant 20-20 insights 5
it to compare outcomes with KPIs to identify
causation issues — making this approach an
inherently reactive model.
• Phase 4: Advanced analytics and predictive
shrink. Predictive analytics is a branch of math-
ematics and statistics that looks for patterns in
data and makes inferences on future outcomes.
Predictive analytics in the framework of a
business intelligence application uncovers rela-
tionships and patterns within large volumes of
data that can be used to predict behaviors and
events. The core of predictive analytics relies
on capturing relationships between causal
factors and how they connect with data from
past occurrences, and exploiting it to predict
future outcomes.
Predictive analytics is the key to transitioning
from reactive reporting to proactive insight.
By applying statistical techniques, the drivers
of business outcomes can be identified more
clearly, along with more precise estimates of
how they affect those outcomes. Predictive
analytics can help retailers optimize existing
processes, better understand customer
behavior, identify unexpected opportunities
and anticipate problems before they happen.
The core of predictive analytics relies on
capturing relationships between explana-
tory variables such as sales-to-return ratios,
employee overrides, on-hand quantity
adjustments at different levels of product/
location hierarchy and the
predicted variables (i.e.,
shrink). These relation-
ships are then translated
into a predictive model
that “listens” for outcome
changes and patterns in
the explanatory variables
to forecast shrink at any
point in time. For example,
in the case of vendor
credits, a predictive model
will be able to identify increases in credits and
adjust the predicted shrink — giving an early
insight so the associated parties can react pro-
actively to control the damage.
Looking Ahead
Retailers can benefit substantially by adopting
a new competitive discipline in the form of
predictive analytics, which uses quantitative
methods to derive actionable insights from the
wealth of data they now have at their disposal.
In recent times, structured transactional data and
unstructured data such as police incident reports,
LP case documents and employee feedback
have increased the data available for analysis by
Quick Take
• Ask critical questions, such as
threshold and acceptable value for
KPIs and benchmarks tracked.
• Measure and analyze how the KPIs
relate to the cause of shrink.
• Identify the outlier and conduct field
research to first validate the reasons
for the outlier, then collect feedback
on the exact causes and remedies for
the exceptions.
• The need for predicting shrink is data
and also how that data connects with
the causes of shrink.
Shrink Cheat Sheet (Part III)
Quick Take
Use the understanding developed in
Phase 3 to start building predictive
models:
• Identify and use the data elements as
the dependent variables (causes) to
predict future outcomes (shrink).
• Start with predicting small subsets;
continue to refine the models and
clean the underlying data. elements
to increase prediction accuracy.
Shrink Cheat Sheet (Part IV)
By applying statistical
techniques, the drivers
of business outcomes
can be identified more
clearly, along with
more precise estimates
of how they affect
those outcomes.