The Internet of Things: P&C Carriers & the Power of DigitalCognizant
As P&C carriers struggle to achieve and maintain profitable growth, they must prepare for and stay in step with advancements in digital technologies. The Internet of Things (IoT) and its network of connected devices and objects makes it possible for carriers to transform how they communicate, collaborate, and operate, and strengthen their capabilities in a number of key areas.
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.
Modernizing Insurance Data to Drive Intelligent DecisionsCognizant
To thrive during a period of unprecedented volatility, insurers will need to leverage artificial intelligence to make faster and better business decisions - and do so at scale. For many insurers, achieving what we call "intelligent decisioning" will require them to modernize their data foundation to draw actionable insights from a wide variety of both traditional and new sources, such as wearables, auto telematics, building sensors and the evolving third-party data landscape.
In this edition of our Work Ahead study, we explore the increasing primacy of digital within the context of the COVID-19 pandemic and assess what’s next for the future of work.
Our supply chain expert shares insights on how Industry 4.0 is enabling companies to create lasting competitive advantage, sustainably and financially. This paper explores the key pillars of today’s sustainable supply chain and what variables have impacted its rise. Key points:
Industry 4.0 advances are being powered by the Internet of Things in which factory “command centers” are tethered to the cloud, enabling real-time monitoring and demand-driven configuration.
To win in today’s market firms must also embrace big data in a way that stiches together fragmented, custom e-commerce orders with reactive, optimized supply chains and factory production.
An overview of a framework companies can use to deliver on Industry 4.0 to seize a competitive advantage in today’s uber-connected world.
Companies embracing the new era of sustainability not only help the environment through decreased energy usage, but also please shareholders via expanding enterprise value – economically and sustainably.
The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...Cognizant
Intelligent automation continues to be a top driver of the future of work, according to our recent study. To reap the full advantages, businesses need to move from isolated to widespread deployment.
The Internet of Things: P&C Carriers & the Power of DigitalCognizant
As P&C carriers struggle to achieve and maintain profitable growth, they must prepare for and stay in step with advancements in digital technologies. The Internet of Things (IoT) and its network of connected devices and objects makes it possible for carriers to transform how they communicate, collaborate, and operate, and strengthen their capabilities in a number of key areas.
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.
Modernizing Insurance Data to Drive Intelligent DecisionsCognizant
To thrive during a period of unprecedented volatility, insurers will need to leverage artificial intelligence to make faster and better business decisions - and do so at scale. For many insurers, achieving what we call "intelligent decisioning" will require them to modernize their data foundation to draw actionable insights from a wide variety of both traditional and new sources, such as wearables, auto telematics, building sensors and the evolving third-party data landscape.
In this edition of our Work Ahead study, we explore the increasing primacy of digital within the context of the COVID-19 pandemic and assess what’s next for the future of work.
Our supply chain expert shares insights on how Industry 4.0 is enabling companies to create lasting competitive advantage, sustainably and financially. This paper explores the key pillars of today’s sustainable supply chain and what variables have impacted its rise. Key points:
Industry 4.0 advances are being powered by the Internet of Things in which factory “command centers” are tethered to the cloud, enabling real-time monitoring and demand-driven configuration.
To win in today’s market firms must also embrace big data in a way that stiches together fragmented, custom e-commerce orders with reactive, optimized supply chains and factory production.
An overview of a framework companies can use to deliver on Industry 4.0 to seize a competitive advantage in today’s uber-connected world.
Companies embracing the new era of sustainability not only help the environment through decreased energy usage, but also please shareholders via expanding enterprise value – economically and sustainably.
The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...Cognizant
Intelligent automation continues to be a top driver of the future of work, according to our recent study. To reap the full advantages, businesses need to move from isolated to widespread deployment.
The Work Ahead: Mastering the Digital EconomyCognizant
The Work Ahead is a research series providing insight and guidance on how business – and jobs – must evolve in an economy of algorithms, automation and AI.
Strategic IT Transformation Programme Delivers Next-Generation Agile IT Infra...Cognizant
The strategic use of the new technology enables Standard Life’s IT group to focus on generating business innovation and directly supporting business stakeholders in areas such as customer engagement while Cognizant manages the provisioning of Infrastructure as a Service.
A Digital Way Forward for Australian SME InsurersCognizant
The ongoing digitisation of the small- and medium-sized enterprise (SME) market has only accelerated post COVID-19, opening new opportunities and challenges to established carriers. Winning insurers will need to hyper-personalise their offerings and experiences to attract and retain new and
modern SME businesses, as well as tap the billowing insurtech ecosystem – whilst leaning into extended capabilities of their modernised core systems – to remain relevant in this fast-growing and dynamic market segment.
Top data science and AI trends to watch out for in 2021 | AIM & AnalytixLabsSrishti Deoras
The annual data science and AI trends report by Analytics India Magazine aims to highlight the top trends that will define the industry each year. This report, which has been developed in association with AnalytixLabs, covers the trends that will shape the year 2021.
Market Research Reports, Inc. has announced the addition of “Big Data in Global Telecom Market: Key Trends, Market Opportunities and Industry Forecast 2015-2020" research report to their Offering. See more at - http://mrr.cm/oqS
Telecommunications is at the heart of the digital economy, driving and enabling the changing consumer behaviors and demands that have transformed how people consume products and services across many sectors. However, digitization is as much a struggle for Telcos as it is for traditional organizations in many industries.
Our latest survey of over 5700 mobile consumers in the US and Europe has found, for example, that consumers are discontented with their operators.
In partnership with IDG, our 2022 Insight Intelligent Technology™ Report examines how companies are making progress on long-term IT strategies to meet the changing, post-pandemic expectations of their businesses, their employees, and the market more broadly.
Patrick Couch - Intelligenta Maskiner & Smartare Tjänster IBM Sverige
Industriföretag, såväl tillverkare som användare av maskiner, fordon och utrustning, står inför ett paradigmskifte drivet av ökad global konkurrens, kunders förändrade efterfrågan samt det faktum att produkterna nu blir instrumenterade, ihopkopplade och mer intelligenta. Stora datamängder är inte ett buzzword för dessa företag, utan en reell verklighet som de behöver förhålla sig till för att säkra sin framtida verksamhet. I bästa fall omvandlar dessa företag denna teknologiska revolution (populärt kallad Internet of Things, Industrial Internet, M2M, Industri 4.0 etc.) till en motor för att utveckla verksamheten mot tillväxt och effektivare produktion. Detta skifte skapar framförallt stora möjligheter att förflytta sig mot leveranser av tjänster som kraftigt ökar mervärdet för kunderna, deras kunders kunder samt för producenten.
How Analytics Can Transform the U.S. Retail Banking SectorCognizant
To regain customer trust, U.S. retail banks must seriously consider using analytics to improve decision-making, uncover unseen innovation opportunities and improve compliance.
Big Data BlackOut: Are Utilities Powering Up Their Data Analytics?Capgemini
Analytics is seeing greater recognition amongst utility executives. Our research showed that 80% of utilities consider big data analytics as a source of new business opportunities and 75% see it as crucial for future success. Big Data indeed offers an exciting opportunity to transform utility operational effectiveness, while at the same time dealing with the historical problem of low customer satisfaction. Take operational efficiency alone. The annual cost of weather-related power outages to the U.S. economy is estimated to be between $18 billion to $33 billion. Organizations can use Big Data analytics to detect operational challenges and prevent outages, substantially reducing costs. Big Data also affords opportunities to utilities for inventing new business models through the data generated by the smart infrastructure.
The analytics opportunity for utilities is clear, but there continues to be a lack of real impetus and value delivery. Only 20% have already implemented big data analytics initiatives. What is putting the brakes on utilities?
In this paper, we highlight the big data opportunities that utilities can leverage and identify the challenges that are currently holding them back. We conclude the paper with concrete recommendations on how to ensure analytics drive business value.
The Work Ahead for Healthcare Payers: Gaining a Foothold in the Digital Healt...Cognizant
Healthcare insurers need to continue applying intelligent automation and overcome skills gaps to realize expected digital gains, according to our recent research.
Digitization will reinvent the world economy with individuals, businesses, and societies becoming
interconnected in real time. This new digital economy is more collaborative, intelligent,
responsive, and efficient, with dramatic increases in productivity and economic value.
The digital economy will transform the way we live and work, how business runs, and how society
functions – and it will do this in a timeframe that is much shorter than any other major economic
transition in history.
In our latest piece, we share unique perspectives on how artificial intelligence is amplifying human potential and reshaping business. This article explore 3 fundamental questions:
How will AI shift the expectations of my customers?
How will AI transform the way my competitors run their businesses?
How should my company respond to AI?
In this piece, we explore how AI has the potential to deliver the active management that will be required for the grid of the future. Powerful intelligence will be able to balance grids, manage demand, negotiate actions, enable self-healing and facilitate a host of new products and services.
Evolution of AI ML Solutions - A Review of Past and Future Impact.pdfChristine Shepherd
Need to incorporate technologies that drive unparalleled advancements? If yes, leveraging AI and Machine Learning services helps enterprises to streamline operations and also usher in a new era of possibilities and societal benefits. Whether it's designing novel solutions, creating intelligent products, or optimizing workflows, AI and ML serve as catalysts for innovation, propelling enterprises into the forefront of their respective industries.
With enterprises putting digital at the core of their transformation, our annual Data Science & AI Trends Report explores the key strategic shifts enterprises will make to stay intelligent and agile going into 2019. The year was marked by a series of technological advances, including advances in AI, deep learning, machine learning, hybrid cloud architecture, edge computing (with data moving away to edge data centres), robotic process automation, a spurt of virtual assistants, advancements in autonomous tech and IoT.
The Work Ahead: Mastering the Digital EconomyCognizant
The Work Ahead is a research series providing insight and guidance on how business – and jobs – must evolve in an economy of algorithms, automation and AI.
Strategic IT Transformation Programme Delivers Next-Generation Agile IT Infra...Cognizant
The strategic use of the new technology enables Standard Life’s IT group to focus on generating business innovation and directly supporting business stakeholders in areas such as customer engagement while Cognizant manages the provisioning of Infrastructure as a Service.
A Digital Way Forward for Australian SME InsurersCognizant
The ongoing digitisation of the small- and medium-sized enterprise (SME) market has only accelerated post COVID-19, opening new opportunities and challenges to established carriers. Winning insurers will need to hyper-personalise their offerings and experiences to attract and retain new and
modern SME businesses, as well as tap the billowing insurtech ecosystem – whilst leaning into extended capabilities of their modernised core systems – to remain relevant in this fast-growing and dynamic market segment.
Top data science and AI trends to watch out for in 2021 | AIM & AnalytixLabsSrishti Deoras
The annual data science and AI trends report by Analytics India Magazine aims to highlight the top trends that will define the industry each year. This report, which has been developed in association with AnalytixLabs, covers the trends that will shape the year 2021.
Market Research Reports, Inc. has announced the addition of “Big Data in Global Telecom Market: Key Trends, Market Opportunities and Industry Forecast 2015-2020" research report to their Offering. See more at - http://mrr.cm/oqS
Telecommunications is at the heart of the digital economy, driving and enabling the changing consumer behaviors and demands that have transformed how people consume products and services across many sectors. However, digitization is as much a struggle for Telcos as it is for traditional organizations in many industries.
Our latest survey of over 5700 mobile consumers in the US and Europe has found, for example, that consumers are discontented with their operators.
In partnership with IDG, our 2022 Insight Intelligent Technology™ Report examines how companies are making progress on long-term IT strategies to meet the changing, post-pandemic expectations of their businesses, their employees, and the market more broadly.
Patrick Couch - Intelligenta Maskiner & Smartare Tjänster IBM Sverige
Industriföretag, såväl tillverkare som användare av maskiner, fordon och utrustning, står inför ett paradigmskifte drivet av ökad global konkurrens, kunders förändrade efterfrågan samt det faktum att produkterna nu blir instrumenterade, ihopkopplade och mer intelligenta. Stora datamängder är inte ett buzzword för dessa företag, utan en reell verklighet som de behöver förhålla sig till för att säkra sin framtida verksamhet. I bästa fall omvandlar dessa företag denna teknologiska revolution (populärt kallad Internet of Things, Industrial Internet, M2M, Industri 4.0 etc.) till en motor för att utveckla verksamheten mot tillväxt och effektivare produktion. Detta skifte skapar framförallt stora möjligheter att förflytta sig mot leveranser av tjänster som kraftigt ökar mervärdet för kunderna, deras kunders kunder samt för producenten.
How Analytics Can Transform the U.S. Retail Banking SectorCognizant
To regain customer trust, U.S. retail banks must seriously consider using analytics to improve decision-making, uncover unseen innovation opportunities and improve compliance.
Big Data BlackOut: Are Utilities Powering Up Their Data Analytics?Capgemini
Analytics is seeing greater recognition amongst utility executives. Our research showed that 80% of utilities consider big data analytics as a source of new business opportunities and 75% see it as crucial for future success. Big Data indeed offers an exciting opportunity to transform utility operational effectiveness, while at the same time dealing with the historical problem of low customer satisfaction. Take operational efficiency alone. The annual cost of weather-related power outages to the U.S. economy is estimated to be between $18 billion to $33 billion. Organizations can use Big Data analytics to detect operational challenges and prevent outages, substantially reducing costs. Big Data also affords opportunities to utilities for inventing new business models through the data generated by the smart infrastructure.
The analytics opportunity for utilities is clear, but there continues to be a lack of real impetus and value delivery. Only 20% have already implemented big data analytics initiatives. What is putting the brakes on utilities?
In this paper, we highlight the big data opportunities that utilities can leverage and identify the challenges that are currently holding them back. We conclude the paper with concrete recommendations on how to ensure analytics drive business value.
The Work Ahead for Healthcare Payers: Gaining a Foothold in the Digital Healt...Cognizant
Healthcare insurers need to continue applying intelligent automation and overcome skills gaps to realize expected digital gains, according to our recent research.
Digitization will reinvent the world economy with individuals, businesses, and societies becoming
interconnected in real time. This new digital economy is more collaborative, intelligent,
responsive, and efficient, with dramatic increases in productivity and economic value.
The digital economy will transform the way we live and work, how business runs, and how society
functions – and it will do this in a timeframe that is much shorter than any other major economic
transition in history.
In our latest piece, we share unique perspectives on how artificial intelligence is amplifying human potential and reshaping business. This article explore 3 fundamental questions:
How will AI shift the expectations of my customers?
How will AI transform the way my competitors run their businesses?
How should my company respond to AI?
In this piece, we explore how AI has the potential to deliver the active management that will be required for the grid of the future. Powerful intelligence will be able to balance grids, manage demand, negotiate actions, enable self-healing and facilitate a host of new products and services.
Evolution of AI ML Solutions - A Review of Past and Future Impact.pdfChristine Shepherd
Need to incorporate technologies that drive unparalleled advancements? If yes, leveraging AI and Machine Learning services helps enterprises to streamline operations and also usher in a new era of possibilities and societal benefits. Whether it's designing novel solutions, creating intelligent products, or optimizing workflows, AI and ML serve as catalysts for innovation, propelling enterprises into the forefront of their respective industries.
With enterprises putting digital at the core of their transformation, our annual Data Science & AI Trends Report explores the key strategic shifts enterprises will make to stay intelligent and agile going into 2019. The year was marked by a series of technological advances, including advances in AI, deep learning, machine learning, hybrid cloud architecture, edge computing (with data moving away to edge data centres), robotic process automation, a spurt of virtual assistants, advancements in autonomous tech and IoT.
Machine Learning and IoT Technologies_ Changing Businesses Operations in 2024...Polyxer Systems
The digital transformation in businesses is now only limited to our imagination. The ever-changing context of technology is predicted to leap in 2024.
While businesses brace for the next advanced technological waves, the Internet of things and machine learning technologies have already started making a great deal. These technologies are envisioned to uphold the rapid evolution in 2024.
How AI and ML Can Optimize the Supply Chain.pdfGlobal Sources
Artificial intelligence (AI) and machine learning (ML) were already buzzwords in the technology and manufacturing spheres before the pandemic upended the global supply chain. Ironically, with the disruption from the health crisis the push toward translating them into reality has become stronger.
Although there is still a huge gap between “ambition and execution,” as industry analysts put it, the AI and ML promises of higher productivity and better resilience cannot be ignored. A few have started adopting the technologies and many more are expected to follow and reap the benefits of a highly integrated system in the coming years.
Global Sources‘ latest e-book, How Artificial Intelligence & Machine Learning Can Optimize the Supply Chain, explores the potential benefit of technology on key areas, such as data collection and analysis, supply chain optimization, cost reduction, forecasting and planning. It offers a roadmap to augmentation and automation, and how this will help speed up operations, boost efficiency and build resilience. The book also covers challenges posed by the adoption of artificial intelligence and machine learning in current setups, and how they can be overcome.
Read more about the advantages of adopting a highly integrated system using artificial intelligence and machine learning.
Download here to get a free copy of How Artificial Intelligence & Machine Learning Can Optimize the Supply Chain.
Generative AI in supply chain management.pdfStephenAmell4
Generative AI in the supply chain leverages advanced algorithms to autonomously create and optimize processes, enhancing efficiency and adaptability. This technology generates intelligent solutions, forecasts demand, and streamlines logistics, ultimately revolutionizing how businesses manage their supply chains by fostering agility and cost-effectiveness through data-driven decision-making.
Advanced Manufacturing – Solutions That Are Transforming the IndustryMRPeasy
Advanced manufacturing is on its way to transform the industry. And there are solutions in place already that could help even small manufacturers keep up in the rapidly changing business environments.
This emerging tech research from CompTIA describes the growing role of artificial intelligence in the technology strategies that businesses are building.”
Five Converging Forces that Are Driving Technological EvolutionCognizant
The digital era is catalyzing business, unleashing technological change that may appear chaotic on the surface but is resulting in massively powerful systems of intelligence that enable humans and machines to collaborate securely.
Are you exploring the best way for your business to save expenses, enhance margin, or reinvest in the coming years? Check out the top technological advancements in business that are beneficial for business expansion and that result in a technology roadmap that has an impact on a number of the organization's strategic goals.
For more information, see: https://www.albiorixtech.com/blog/technology-trends-in-business/
#technology #technologytrends #webappdevelopment #mobileappdevelopment #softwaredevelopment
Certus Accelerate - Building the business case for why you need to invest in ...Certus Solutions
Becoming an analytically driven or cognitive business is a journey.
Businesses will be able to rapidly capitalize on new opportunities if they have invested in the foundations of their information management systems.
Generative AI is a branch of AI that aims to enable machines to produce new and original content. Unlike traditional AI systems, which rely on predefined rules and patterns, generative AI employs advanced algorithms and neural networks to generate outputs that autonomously imitate human creativity and decision-making.
AI & Analytics Predictions of 2022. InfographicInData Labs
What does 2022 hold for artificial intelligence? Will the AI revolution continue to gain momentum?
This report will provide a look into the future of AI technologies, including:
- Strategic AI predictions and trends for 2022 and beyond
- The current and projected state of the AI market and its value
- Business functions that already benefit from AI implementation
- Industries where AI is making the greatest disruption
- The business value generated by Artificial Intelligence
- Costs of AI implementation and main challenges
The Total Economic Impact Of IBM Multivendor Support Services (MVS) Cost Savi...Cor Ranzijn
A Forrester Total Economic Impact Study , January 2019
The Total Economic Impact Of IBM Multivendor Support Services (MVS) Cost Savings And Business Benefits Enabled By IBM MVS
Elevate your enterprise cfo role reportCor Ranzijn
Companies in virtually every industry are undergoing a secular change to new, platform- based businesses. To thrive, organizations need to digitally reinvent their enterprise business
and operating models. CFO"s continue to be instrumental in providing the analytical insights to help the enterprise invest capital into new opportunities. Essential to this process is a highly collaborative, in-synch C-suite. The CFO’s newest mandate – to help steer the strategic direction
of the enterprise and do so iteratively – requires changes to their finance organizations. Startlingly, nearly half of CFOs report their own finance organizations fall short of what’s required.
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
1. Welcome to the cognitive supply chain
Digital operations – reimagined IBM Institute for Business Value
2. How IBM can help
The Cognitive Internet of Things (CIoT) is creating the
potential to enable new markets and grow new revenue
streams. We see this rapidly evolving market pushing at the
boundaries of what is possible today. Clients need strategies
to harness this potential for real-time actionable insight, apply
predictive analytics and enable their digital transformation.
IBM Digital Operations for IoT and supply chain management
offers integrated services, software and infrastructure
solutions. Our portfolio includes Connected Solutions,
Building & Asset Optimization and Next Generation Supply
Chain. Connect with us to navigate this dynamic, rapidly
changing landscape in the artificial intelligence (AI) and
cognitive computing era. Visit ibm.com/services/us/
business-consulting/digital-operations-internetofthings.
Executive Report
Operations and supply chain
3. The future has arrived
The futuristic renderings of science fiction movies and literature have become reality, and
robotic likenesses are now automating and instrumenting learning supply chains. The next
wave of technology – artificial intelligence (AI) – is already making sense of the deluge of
operational data streaming in from a plethora of devices and cloud applications. This technology
is also applying advanced mathematics to create products, processes and systems that are
able to adapt and learn.
We predicted these developments in 2010, when we envisioned what we called the smarter
supply chain of the future. We foretold that smarter supply chains would need to be:
“Instrumented. Information that was previously created by people will increasingly be
machine-generated – flowing out of sensors, RFID tags, meters, actuators, GPS and more.
Inventory will count itself. Containers will detect their contents. Pallets will report in if they end
up in the wrong place.
Interconnected. The entire supply chain will be connected – not just customers, suppliers and
IT systems in general, but also parts, products and other smart objects used to monitor the
supply chain. Extensive connectivity will enable worldwide networks of supply chains to plan
and make decisions together.
Intelligent. These supply chain decisions will also be much smarter. Advanced analytics and
modeling will help decision makers evaluate alternatives against an incredibly complex and
dynamic set of risks and constraints. And smarter systems will even make decisions
automatically – increasing responsiveness and limiting the need for human intervention.”1
Less than a decade later, our predictions are becoming reality.
Unparalleled operational
excellence
Supply chain executives across all industries have
been developing digital strategies over the past
several years. They are aggressively addressing
integrated technologies, including the Internet of
Things (IoT) on mobile, collaborative and cloud-based
platforms. These executives are applying predictive
analytics even more rapidly to all supply chain
processes, including asset, inventory, fleet and energy
management. They are further automating digital
manufacturing, customer service and distribution with
robotics and drones. And now, in this cognitive era,
these digital operations are being enhanced even
more – with artificial intelligence (AI). When combined
with advanced automation, thinking and learning,
supply chains can be trained to augment and enhance
human decision making and bring about a new level of
operational excellence.
1
4. More than half of
outperforming supply chain
executives surveyed
said their top investmentsin the
next three years will be cognitive
or cloud
86% of outperforming supply
chain executives surveyed
said cognitive computing will
transform their demand planning
and forecasting capabilities
92% of outperforming
manufacturing executives
said AI and cognitive computing
will enhance performance in
production planning
Adaptive robotics act on Internet of Things (IoT) device information and a multitude of structured
and unstructured data to learn and make autonomous decisions. Natural language processing
(NLP) tools can understand human speech and react to what they are being told. Predictive
analytics are being applied to demand responsiveness, inventory and network optimization,
preventative maintenance and digital manufacturing. Search and pattern recognition algorithms
– which are no longer just predictive, but hierarchical – analyze real-time data, helping supply
chains to react to machine-generated, augmented intelligence, while providing instant visibility
and transparency.
Bob Stoffel, former Senior Vice President, Engineering, Strategy and Supply Chain at UPS, said,
“When we talk about supply chain visibility, it does not simply mean visibility into your own
supply chain. It means visibility among partners, which enables collaborative decision making
closer to the customer. This is both a science (managing the technology) and an art (using the
information and metrics for competitive advantage).”2
AI is becoming essential to innovative supply chain transformation. Forty-six percent of supply
chain executives anticipate that AI/cognitive computing and cloud applications will be their
greatest areas of investment in digital operations over the next three years (see Figure 1).
To better understand the impact of AI and cognitive computing solutions on supply chain and
operations, we surveyed senior operational executives across a wide range of industries and
geographies. We asked more than 1,600 Chief Operating Officers (COOs), Chief Supply Chain
Officers (CSCOs) and executives of product development, procurement and manufacturing
about their current views on AI and cognitive computing, their priorities and the value that they
expect to derive. (For more information, see “Study approach and methodology,” page 19.)
2 Welcome to the cognitive supply chain
5. Figure 1
Executives predict their greatest digital operations investments over the next three years
Source: IBM Institute for Business Value
46%
46%
42%
41%
36%
28%
25%
21%
Cognitive computing
Cloud applications
Internet of Things
Predictive analytics
Mobile applications
Collaboration technologies
Digital manufacturing
Automation
Our research shows that COOs and CSCOs are aggressively reinventing business models,
strategies and technological capabilities. They are resolute on assisting the CEO in defining
agile business models and working with the CMO to support the go-to-market strategy, while
backing investments and explorations into new ways of optimizing their supply chain operations.
Pioneering firms are applying these AI and cognitive technologies to their products and their
daily operations. Some are living the future; others have just begun the journey.
3
6. Supply chain is a natural fit for AI
In our global research data, we identified a group of more than 700 outperformers (12 percent
of the total sample) with stronger financial performance than their peers. These companies,
across many industries, report annual revenue growth and profit increases of more than
5 percent over the past three years. We ranked public sector organizations based on
effectiveness and efficiency.
Eighty-eight percent of the highest-performing organizations surveyed report that AI is
inevitable in their industry. Among those polled, fully 95 percent of the highest-performing
organizations see AI as central to their innovation success.
COOs and CSCOs are looking to AI and cognitive computing to resolve many of their end-to-end
supply chain process challenges, and financial outperformers are investing in AI more (see
Figure 2). The most common applications of these technologies are directed at material quality,
preventative maintenance, and risk management from supply to production to customer provision.
Machine learning is becoming mainstream in the operational technology portfolio. Baseline
forecasts for new products are instrumental in determining new product introductions and
go-to-market plans. When applied to demand signals, AI can determine changing demand
behaviors and optimize inventory levels and replenishment plans to feed the continuous loop of
product lifecycle management.
4 Welcome to the cognitive supply chain
7. Sales and operations planning is the ultimate collaborative decision-making process.
Companies can apply AI technologies to sales and operations planning and other massive
supply chain data pools to manage demand volatility, supply constraints, production scheduling
and dynamic distribution. AI can augment human interaction by allocating resources, assigning
people and scheduling processes.
Figure 2
How companies are using cognitive computing and AI to resolve supply chain challenges
Source: IBM Institute for Business Value
40%
38%
42%
33%
Supply allocation and distribution decisions
Determining unplanned event alternatives
Transportation disruptions
Inaccurate forecasts
54% 24%
125%
more
Financial outperformers Financial underperformers All respondents
Material quality and
risk management
51% 39%
31%
more
Sales and
operations planning
32%
5
8. Machine learning capabilities apply algorithms to massive operational data feeds to discover
insights to track and predict supply chain disruptions, providing new levels of visibility into day-
to-day operations. These capabilities can also recommend alternative actions for unplanned
events and transportation disruptions. Weather data integrated with operational data can
predict potential problems and alert transportation and logistics service personnel with
recommended actions.
And in manufacturing, collaborative robots equipped with AI software can “see” their environment
and move in a safe manner around the humans working alongside them in production.
In our research, we asked a set of distinct questions about the priorities, plans and purpose of
employing AI capabilities in three distinct and complex supply chain areas:
• Product development
• Procurement
• Manufacturing.
The priorities represent the business and competitive challenges, as well as the current trends,
that will affect companies’ operations. The plans are the investments in technology, processes
and people that organizations are making and plan to make over the next three years. And the
purpose represents those initiatives, with emphasis on intelligence, that executives are
prioritizing to aim for the highest return on their investments.
6 Welcome to the cognitive supply chain
9. The future unfolds: Innovative product
development
Across industries, executives face many challenges in getting the right product to the right
customer at the right time. And to bring innovative products to market, they are challenged with
combining capabilities from new technologies such as IoT, drones and robotics with enterprise
cloud applications. Many research and product development executives are experimenting with
cognitive computing capabilities embedded into their products and their operations. Cognitive
computing is supporting product research and market analysis, as well as product
development and production (see Figure 3).
Figure 3
Product development priorities, plans and purpose
Source: IBM Institute for Business Value
Trends with impact
• Cloud applications
• Internet of Things
• Drones, robotics
Priorities
current
trends
Purpose
the value
proposition
Product
development
Plans
investments
now and
beyond
Investment areas
• Security and surveillance
• Energy management
• Customer experience
Investment initiatives
• Cloud applications
• Predictive analytics
• Cognitive computing
Challenges
• Lack of engineering skills
• Insufficient competitive analysis
• Costly energy and environment
regulations
Value from investments
• Increase innovation
• Increase operational efficiency
• Increase workforce productivity
Value in cognitive computing
• Product research
• Market analysis
• Prototype development
Using image-processing models to
identify elusive problems
Experts know that it takes trained eyes to spot
when something’s not right at the top of a cell
phone tower. Hundreds of feet up, it could be a
frayed cable, a spot of corrosion on a support or
any one of a long list of potential warning signs.
A drone maker in the Netherlands saw the
convergence of IoT and cognitive computing as an
opportunity to develop a new tower inspection
capability. The company’s new products use
image-processing models that are trained to
identify anomalies within high-resolution images
captured by drone-mounted cameras. These
intelligent drones are helping to keep risky tower
accidents to a minimum, reducing costs and
increasing service reliability.3
7
10. The future unfolds: Intelligent procurement
Chief Procurement Officers (CPOs) are concerned with maintaining the health of their global
supply chain networks, which face added pressures of regulations and security risks, while
transforming their operating models for revenue growth (see Figure 4). But their organizations
have a great deal of data buried in contracts and transactional systems and externally, among
regulators, that can be applied for intensified procurement insights. Using cognitive computing
capabilities to parse through unstructured data, such as news feeds and social networks, can
augment learning for supply risk scoring and supplier performance.
Figure 4
Procurement priorities, plans and purpose
Source: IBM Institute for Business Value
Trends with impact
• Regulations and sustainability
• Global supply chain network
• Internet of Things
Priorities
current
trends
Purpose
the value
proposition
Procurement
Plans
investments
now and
beyond
Investment areas
• Inventory and distribution control
• Security and surveillance
• Supply chain management
Investment initiatives
• Cognitive computing
• Cloud applications
• Predictive analytics
Challenges
• Integration with suppliers
• Risk mitigation
• Global sourcing
Value from investments
• Increase revenue growth
• Transform the operating model
• Increase operational efficiency
Value in cognitive computing
• Risk management
• Spend analysis
• Logistics and distribution
8 Welcome to the cognitive supply chain
11. CPOs report that their top three technology investment initiatives over the next three years will
be cognitive computing, cloud and predictive data analytics. During that same period, more
than a third of CPOs will focus these investments on supply chain management transformation.
They are seeking to bring secure, real-time transactions to source-to-settle processes, while
advancing predictive analytics in global inventory optimization. We found that for many,
especially in the manufacturing and distribution industries, gaining visibility, insight and
understanding in buy and supply functions is mission critical.
The anticipated returns on these investments will be to increase operational efficiency,
grow revenue and transform the operating model. Cognitive technologies can bring the
comprehensive visibility needed to gain true insight into supply chain disruptions and risks.
With this new level of understanding, procurement professionals can predict outlier events
and put plans in place before these events occur. In fact, 40 percent of CPOs expect that
cognitive computing will add value with risk mitigation, spend analysis and global logistics
and distribution.
Cognitive procurement capabilities
bring supply chain optimization
It’s hard to overstate the importance of an efficient,
low-cost supply chain for contract manufacturing
companies. An electronics contract manufacturing
service provider in the United States knew that to
drive more data-driven decision making among
procurement specialists, it needed to be smarter
about all of its suppliers – not just the biggest. That
meant addressing the reality that procurement staff
simply lacked the time to dig out and analyze
volume and pricing details for thousands of smaller
supplier relationships – as important as they are.
So the company developed an AI procurement
solution that brought all supplier relationships
under the same microscope. The solution pulls
together diverse unstructured data from within
and outside the company and visualizes it in
a way that helps specialists make quick and
accurate decisions. By bringing the same
granularity of insight to all supplier relationships,
the company opened a new frontier for supply
chain optimization.4
9
12. The future unfolds: Learning and automated
manufacturing
Manufacturing executives are working hand-in-hand with their product development
colleagues to bring innovative products to market and support their companies’ growth and
profitability agendas. They are rapidly implementing the foundational technologies of IoT
and cloud, and advancing into the automation technologies of adaptive robotics. And now,
the industry is engaged in its next automation breakthrough – using AI to make production
decisions in real time (see Figure 5).
In automotive production, for example, when a sensor discovers a defect, it feeds data to the
cloud production application, which immediately requests that the defective part be pulled from
the line and a replacement ordered.
Figure 5
Manufacturing priorities, plans and purpose
Source: IBM Institute for Business Value
Trends with impact
• Cloud applications
• 3D printing
• Internet of Things
Priorities
current
trends
Purpose
the value
proposition
Manufacturing
Plans
investments
now and
beyond
Investment areas
• Energy management
• Security and surveillance
• Inventory management
Investment initiatives
• Analytics and cloud
• Robotics and IoT
• Cognitive computing
Challenges
• Skill gaps
• Regulation and traceability
• Product development
innovation
Value from investments
• Increase revenue growth
• Increase operational efficiency
• Reduce cost
Value in cognitive computing
• Manufacturing/production
• Logistics and distribution
• Quality and preventative
maintenance
Filling the gaps in public transportation
with self-driving buses that talk to
passengers
In an effort to expand public transport to areas
that are not served by conventional public
transportation options, a vehicle manufacturer
developed a new on-demand capability that chats
with passengers about destinations, recommen-
dations and more. Using collaborative design, the
manufacturer developed a small, efficient vehicle
that drives itself and communicates with
passengers. To bring the vehicle “to life,” the
company integrated more than thirty onboard
sensors. This IoT solution understands and
responds to a flood of data from the sensors
feeding these buses while in operation.
Passengers request service using a phone app
and speak directly to the vehicle. Their input is
channeled into navigation decisions and
conversational interactions, as the vehicle
discusses best routing options, provides
recommendations on local points of interest,
and learns each passenger’s preferences.5
10 Welcome to the cognitive supply chain
13. AI and cognitive computing underpin future
automation
The AI and cognitive computing journey progresses as automation technologies are receiving
more attention, and more investment, from COOs and CSCOs. Automation includes both
software bots, such as application programming interfaces (APIs) and algorithms, and mechanical
robots. A new augmentation is adaptive robots – cognitive IoT-interconnected and intelligent
machines – which are being used to personalize products and services, improve operations,
reduce costs and elevate efficiency.
Coupled with the greater IoT ecosystem, adaptive robots can learn from other connected devices
to cyclically improve their actions. To innovate their supply chains, financial outperformers are
investing more in the essential technologies while continuing to invest in automation technologies
(see Figure 6).
Figure 6
Which technologies companies are deploying; financial outperformers are at the adoption forefront
Source: IBM Institute for Business Value
Internet of Things
Location technologies/RFID
Digital manufacturing
Drones
Robotics
Cognitive
computing
Financial outperformers Financial underperformers All respondents
Cloud
applications
Big data/
analytics
34%
51%
38%
51%
33%
51% 42%
25%
25%
24%
Essential technologies Automation technologies
14%
Cognitive services support hands-free
productivity
A German manufacturer of advanced earphones
saw an opportunity to evolve its consumer product
in a way that would improve worker productivity.
The company incorporated services from a
cognitive IoT platform into a new offering that
enables workers to use simple verbal commands
to summon complex information and receive
targeted communications to help them complete
immediate tasks. The technology supports hands-
free communications, helping workers to remain
productive while getting the technical and learning
information they need.6
11
14. Cognitive computing adds significant value across
digital operations
AI and cognitive computing are enhancing, in varying degrees, all areas of supply chain
management. Topping the list of current applications is the use of automation for event and
emergency response, asset management and global network design – all for proactive and
predictive responsiveness. But let’s look to the near future. Operational executives have big
plans to completely transform their capabilities in demand, risk and security management, as
well as in the customer experience, verifying a customer-centric perspective on future
undertakings (see Figure 7).
Figure 7
The effects that cognitive computing may have on operations, according to respondents
Source: IBM Institute for Business Value
56%Demand management and forecasting
Risk and security management
Supply chain customer experience
Distribution management
Event and emergency response
Service and returns management
Asset management
Multi-modal transportation management
Global network design
Add value Transform our capability
55%
55%
53%
53%
53%
52%
53%
50%
24%
24%
24%
23%
27%
24%
25%
23%
25%
12 Welcome to the cognitive supply chain
15. The various case studies in this report demonstrate the potential value and innovation of
applying AI to further automate devices and operating processes. In a nutshell, pioneering
leaders are building more cerebral operations, with the goals of
• Increasing revenue and entering new markets
• Increasing operational efficiency and agility
• Increasing innovation to achieve competitive advantage.
In the past decades, we have advanced supply chain processes from “sense and respond”
to “predict and act.” Now we have supply chain capabilities that can feel, perceive, react and
learn. AI is next-generation supply chain management that enables unparalleled operational
excellence.
13
16. The cognitive supply chain journey
The road to successful cognitive, or learning, supply chain management may seem long and
daunting at first thought. The journey, like most, must be strategically planned and executed with
a roadmap to value. After working with and observing successful digital reinventions of
organizations in every industry, across the globe, we have developed a course of action.
Imagine the future
We learned from the financial outperformers and C-suite operations executives in this study
how important it is to integrate the business strategy with the operating model. But many
companies lack a clear strategic vision and plan for digital operations. Our analysis shows that
the most financially robust companies are following a transformation roadmap.
The roadmap should include a program of many innovations and launches. Envisioning
workshops use design thinking to understand customers, clients and colleagues through
brainstorming sessions and visualizing operating use cases. Align these initiatives with the
target operating model and ecosystem strategy.
14 Welcome to the cognitive supply chain
17. Example supply chain use cases that incorporate AI might include:
• Available to promise: Use real-time customer demand and environmental data to better align
the committed and actual date with the requested date.
• Put away strategy: Combine connected material handling machine data, spatial and location
data, as well as existing product data to optimize the existing rules and policy for inventory
storage.
• Production route determination: Augment advanced process controls (APCs) with
machine data, energy consumption, customer segment, demand and sales campaign data
to sequence and schedule production processes and routes, as well as respond quickly to
changes when necessary.
• Safety stock planning: Optimize safety stock levels at a more granular level with the use of
additional dependent system information from both the vendor and customer.
From the use cases, create prototypes using agile development techniques. Augment
capabilities and continue to build and deploy IoT products and operation control devices
supported by enterprise cloud applications for real-time visibility. Articulate the impact and
business case. Don’t forget to develop scorecards to monitor the prototype into implementation.
15
18. Understand your data
Data – it all begins with the data. Develop a data strategy to target information needed to
address the operational problems identified in the use cases. Identify the right data sets to solve
the challenge. We learned which are the most important data sets from the executives in various
role capacities (see Figure 8).
Weather and other unstructured data can now be automatically analyzed to provide insight and
– even better – action. For example, a building management company in the United Kingdom
helps customers anticipate the weather and remotely adjust their building systems, cutting up to
50 percent of heating costs and saving 90 percent of site visits with a cognitive IoT solution.7
Figure 8
Cognitive computing can derive the most value from these data sets
Source: IBM Institute for Business Value
Product development
• Analysis of previous products
• Customer-generated data
• Industry and open-source
investigation
• Social media data
• Patent and product informationCognitive
computing
Procurement
• Global inventory
• Procurement process
• Spend analysis
• Supplier evaluations
• Contracts
Manufacturing
• Production scheduling
• Machine monitoring
• Inventory and materials costs
• Customer order management
• Machine repair history
Supply chain management
• Customer communications
• Transportation modes, routes
and rates
• Competitive pricing and news
• Weather/storm disaster data
• Geopolitical data
16 Welcome to the cognitive supply chain
19. Ready your AI skillset
The nature of work is changing, and digital technologies have a lot to do with those changes.
Businesses and institutions will need employees with digital problem-solving skills to drive
development, growth and success in competitive markets that favor high performance levels
and innovation. Basic computer technology and math backgrounds form the backbone of most
AI programs. Typical knowledge and skill sets include:
• Various levels of math, including probability, statistics, algebra, calculus, logic and algorithms
• Bayesian networking or graphical modeling, including neural nets
• Physics, engineering and robotics
• Computer science, programming languages and coding
• Cognitive science theory.
It is also critical to understand the differences between data analysis and machine learning
engineering. Data analysis is typically focused on dissemination – charts, models and
visualizations – to be presented to a human for actionable insights. With machine learning
engineering, the final output is working software, and the audience is often other software
components that run autonomously, with minimal- to-no human intervention. The actionable
intelligence is shifted to decisions made by machines as they affect how a product or
service behaves.
Many of the companies in our case examples in this report more effectively deploy their AI and
cognitive projects by engaging a Cognitive Center of Competency (CCoC) to build awareness,
skills, best practices and communication plans. This is a shared service function across the
organization to provide expertise in cognitive technologies and their application. The ultimate
goal is to support the roadmap, communicate the AI and cognitive agenda, and strive for greater
supply chain excellence.
17
20. Are you ready to experience unparalleled
operational excellence?
• How will you assess the opportunities that AI and cognitive computing offer your supply chain
operations and product development?
• What is your plan to integrate IoT and operational control devices as you leverage cognitive
technologies?
• In what ways will you verify that your data strategy targets the information necessary to solve
important business problems and operational event management?
• How can your organization collaborate to implement cognitive technologies? How will you
define and measure against agreed-upon success milestones?
• What can you do to get rapid paybacks from cognitive computing, and how will you build on
early results for even greater returns over time?
18 Welcome to the cognitive supply chain
21. Study approach and methodology
We examined key streams of data for this report:
• IBM Institute for Business Value 2016 Cognitive Computing Study – We surveyed over
6,000 global executives from various industries and markets, including 1,672 supply chain,
procurement, manufacturing and product development senior executives. Respondents were
asked to answer questions related to the trends and challenges best served by cognitive
computing, specific to their function. This paper focuses on the operations functions;
forthcoming studies will explore cognitive computing in other areas of the business.
• IBM Institute for Business Value 2016 Cognitive Digital Operations Study – We surveyed over
500 executives, most of them from the operations function and all with direct knowledge of it,
about how their companies are reinventing themselves to improve digital operations. This
research included respondents from companies with at least USD 500 million in revenue in
11 countries around the world and across 12 industries.
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.
Access IBM Institute for Business Value executive
reports on your mobile device by downloading the free
“IBM IBV” apps for phone or tablet from your app store.
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At IBM, we collaborate with our clients, bringing together
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give them a distinct advantage in today’s rapidly
changing environment.
IBM Institute for Business Value
The IBM Institute for Business Value (IBV), part of
IBM Global Business Services, develops fact-based,
strategic insights for senior business executives on
critical public and private sector issues.
19
22. Related IBV publications
Butner, Karen, Dave Lubowe and Louise Skordby. “Who’s leading the cognitive pack in digital
operations?” IBM Institute for Business Value. November 2016. https://www.ibm.com/services/
us/gbs/thoughtleadership/cognitiveops
Butner, Karen and Dave Lubowe. “Thinking out of the toolbox: How digital technologies are
powering the operations revolution.” IBM Institute for Business Value. November 2015. http://
www.ibm.com/services/us/gbs/thoughtleadership/operationstoolbox/
Butner, Karen and Dave Lubowe. “The digital overhaul: Redefining manufacturing in a digital
age.” IBM Institute for Business Value. May 2015. http://www.ibm.com/services/us/gbs/
thoughtleadership/digitalmanufacturing/
About the Authors
Karen Butner is the Business Strategy and Analytics Cognitive IoT and Supply Chain
Management Leader for the IBM Institute for Business Value (IBV). Karen is frequently invited to
speak at international conferences and is widely quoted in leading business and industry
publications. With over 30 years of experience in strategy development and transformation, her
passion is to assist clients in developing improvement agendas to bring significant value to their
global performance. Karen can be reached at kbutner@us.ibm.com.
Dave Lubowe is a Vice President and Partner in IBM Global Business Services and is the North
America Leader for IoT and Supply Chain Management. Dave has over 30 years of industry and
consulting experience in electronics and consumer products. His consulting work has focused
on large-scale transformation and continuous improvement of operational performance. He can
be reached at dave.lubowe@us.ibm.com.
20 Welcome to the cognitive supply chain