Digital disruption, economic instability, political upheavals and skills shortages have all at some point in the past 24 months been blamed for business failure, or at the very least, lost profitability and earnings.
It’s perhaps not a huge surprise that a Gartner CEO survey on business priorities revealed that digital business is a top priority for next year. Survey respondents were asked whether they have a management initiative or transformation program to make their business more digital. The majority (62 percent) said they did. Of those organisations, 54 percent said that their digital business objective is transformational while 46 percent said the objective of the initiative is optimisation.*
So, for businesses it’s a case of learning to evolve and be agile, to use technology to help compete more efficiently and not fall victim to inertia. As businesses become increasingly dependent on the insights from data analytics and face-up to competition fuelled by the 24/7 society of in
In this January 2019 report from Forrester, you’ll learn how leading technology companies must engage their customers consistently while learning from their changing needs. To make this happen, IT leaders must offer technical platforms that enable agility and end-to-end integration. This report will show you:
• Why tech leaders must embrace technology that engages and adapts with customers
• The importance of building tech platforms that deliver speed and flexibility
• How to automate and scale Zero Trust security throughout your environments
Get the report to find out how smart organizations are using new strategies to simplify IT infrastructures and empower employees to do their best work:
• Get advice from Google and Citrix on how to manage the cloud transition strategically
• Avoid common cloud work side effects such as excessive application logins, siloed data searches, and channel switching
• Capture a vision for how artificial intelligence (AI) and machine learning are making work even more intuitive and personalized
Published By: HP Inc.
Published Date: Jun 20, 2019
Four billion people now generate four quintillion bytes of data every day - and with the number of IoT devices set to increase to three times the global population by 2022 - volumes will only continue to rise. The challenge is processing the data. This is why machine learning, deep learning and all the other developing forms of AI must deliver the analytics toolset businesses need to compete.
Published By: Genesys
Published Date: Jun 19, 2019
Contact centers often pool agents into large groups of generalists to distribute work evenly. Skills-based routing takes this a step further with specialized groups. But neither approach scales properly to identify all opportunities and drive business outcomes on each interaction.
Predictive routing uses artificial intelligence (AI) and machine learning to create balance—meeting targets and giving customers a personalized experience. Read Demystifying AI: Creating an AI partnership that maximizes business results to learn how predictive routing systematically:
Evaluates historical and real-time data to make predictions;
Makes the best customer-agent match to drive desired outcomes;
Keeps agents engaged and reduces handle times.
Published By: Genesys
Published Date: Jun 19, 2019
Successfully managing a contact center requires a collaborative, multidisciplinary approach to handle a broad range of operational and tactical tasks. Planning, day-to-day operations and quality management must be seamlessly orchestrated, along with human resources functions like recruitment, learning and development, and employee scheduling.
Read this executive brief to learn how to transition to an AI strategy that can take your team – and business results – to the next level. See how you can:
Create an AI strategy with a single data model that includes routing, interaction analytics, forecasting/scheduling and predictive engagement
Harness the power of your data to align customers with the best resource
Drive employee effectiveness by ensuring you hire the right people and manage their performance to drive their success over the long term
Join our webinar to hear how Consensus, a Target-owned subsidiary, utilizes AWS and Trifacta to prepare data for use in fraud detection algorithms. You’ll learn how self-service automated data wrangling can save your organization time and money, and tips for getting started with Trifacta’s solution, built for AWS.
Webinar attendees will learn:
Why automating your data wrangling tasks can lead to greater data accuracy and more meaningful insights.
How you can reduce your data preparation time by 60% and more with self-service data wrangling tools built for AWS.
How easy it is to get started with machine learning solutions for data wrangling on the cloud.
Businesses are struggling with numerous variables to determine what their stance should be
regarding artificial intelligence (AI) applications that deliver new insights using deep learning.
The business opportunities are exceptionally promising. Not acting could potentially be a
business disaster as competitors gain a wealth of previously unavailable data to grow their
customer base. Most organizations are aware of the challenge, and their lines of business
(LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond
the remote monitoring systems of a prior generation. Three key features differentiate cloud-based
predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine
learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically
what types of value these systems can drive, IDC discusses them at some length in this white paper."
The bar for success is rising in higher education. University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
Artificial Intelligence (AI) has already begun to improve targeting, segmentation, media buying and planning in the advertising industry. AI algorithms can extract complex patterns from vast numbers of data points, and in so doing, are able to self-correct and learn patterns. The revenue potential that improved personalization, segmentation and targeting that AI provides to marketers is huge.
At HERE Technologies, we are placing AI and machine learning at the center of our products and services. We see the opportunity in automated machine learning to enrich the targeting and effectiveness of mobile advertising campaigns in real time. But the outcome of implementing such technology depends on the quality of data being fed into it from the outset. AI wouldn’t be as helpful if it’s being used alongside questionable location data or audience data.
HERE’s location data provides a strong thread that can be woven throughout every stage of the media buying process, offering more context and
Published By: Cisco EMEA
Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
• Facing a myriad of challenges from digital transformation, business today are making big bets on the best collaboration tools they need on hand to meet those challenges. From employee buy-in, to machine-learning capabilities, to security, it's important to select a service with the right capabilities to further your business goals. The challenge, however, is that with so many services to choose from it can be difficult to figure out which one is the right fit for your business.
• This eBook, 5 Considerations in Choosing a Collaboration Platform in the Digital Age, will walk you through the ins and outs of what to keep in mind as you choose the best collaboration platform for you.
The performance of enterprise applications will have a direct impact on business activities and outcomes. The quality of the delivery of applications will depend on how smoothly the underlying data infrastructure operates.
? Optimal application performance and delivery is difficult to achieve in complex environments.
? Many IT infrastructure and operations teams are stretched to the breaking point.
? Predictive analytics and machine learning can be applied to great effect
Business users expect immediate access to data, all the
time and without interruption. But reality does not always
meet expectations. IT leaders must constantly perform
intricate forensic work to unravel the maze of issues that
impact data delivery to applications. This performance
gap between the data and the application creates a
bottleneck that impacts productivity and ultimately
damages a business’ ability to operate effectively.
We term this the “app-data gap.”
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out:
Top 5 causes of downtime and poor performance across the infrastructure stack
How machine learning and predictive analytics can prevent issues
Steps you can take to boost performance and availability"
“In any successful workplace, people expect to work together,” explains Maurice Schweitzer, co-author of ‘Friend & Foe: When to Cooperate, When to Compete, and How to Succeed at Both’. “This is even more important for millennials, who are learning that they have to be adaptable, flexible and open to new ways of working.”
Published By: Dell EMC
Published Date: Oct 13, 2016
Flexibility is important, since many future initiatives—big data, machine learning, emerging technologies, and new business directions—will be built on this cloud structure.
No matter what shape your cloud infrastructure takes, Dell EMC converged and hyper-converged platforms and innovations like Dell EMC VscaleTM Architecture, powered by Intel® Xeon® processors, deliver the pathways to scale-up and scale-out, today and tomorrow.
Published By: Genesys
Published Date: Jun 06, 2017
In this ebook, learn:
- Five trends will have the biggest impact on customer experience
- How to use machine learning to detect patterns and trends to deliver the next great customer experiences
- How to future-proof your contact center and adapt to changing customer needs
Every week InfoSight analyzes more than a trillion data points from
more than 9,000 customers. How does this translate into true
business value? By reducing your business risk with over Six-Nines
of measured availability. By providing you with an infrastructure
that gets “smarter” every single day. By empowering IT staff to
focus on business priorities instead of mundane maintenance.
Overcoming the obstacles to deliver the modern learning demands of a smart campusFrom secure BYOD to robust WiFi and comprehensive video surveillance, the IT challenges schools face to ensure smart, safe campuses are not minor. This on-demand webinar details how schools like yours seamlessly integrated new technology on a budget.