TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management systems and data warehouses.
The need for a COVID-19 vaccination “passport” has prompted some to suggest using blockchain technology as a means of reliably verifying an individual’s status at an international level. There are precedents: for example, until smallpox was eradicated, all international travelers were obliged to carry an immunization record for that disease on a standard paper form to gain entrance to a country. With the likelihood that COVID-19 will remain endemic for many years, a reliable digital record with universal accessibility would be a boon to everyone, especially to international travelers. Vaccination records are just one part of the broader topic of using blockchain technology for medical identity management.
It has been clear for some time that future enterprise IT architecture will span multiple cloud providers as well as on-premises data centers. As Ventana Research noted in the market perspective on data architectures, the rapid adoption of cloud computing has fragmented where data is accessed or consolidated. We are already seeing that almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research are using cloud computing for analytics and data, of which 42% are currently using more than one cloud provider.
Many of us can recall the excitement generated by the first Applicant Tracking Systems or ATS’s hitting the market in the late 1990s and early 2000s. After all, activities related to sourcing, screening, selecting and offering jobs to candidates was perennially a very manually intensive endeavor that also produced many false positives (unsuccessful hires) as well as false negatives (potentially great hires that were never brought into the recruiting process). The first wave of ATS’s proved to be extremely successful in the market due to the impact of their automation capabilities, with virtually all of the ATS market leaders back then either getting acquired and folded into larger HCM platforms, or continuing their path to amassing very large, typically global, customer bases today.
Organizations have become more agile and responsive, in part, as a result of being more agile with their information technology. Adopting a DevOps approach to application deployment has allowed organizations to deploy new and revised applications more quickly. DataOps is enabling organizations to be more agile in their data processes. As organizations are embracing artificial intelligence (AI) and machine learning (ML), they are recognizing the need to adopt MLOps. The same desire for agility suggests that organizations need to adopt AnalyticOps.
The emergence of the Chief Revenue Officer (CRO) has mirrored the adoption of the subscription model and the development of multiple selling and buying channels over and above the traditional direct sales model, referred to as Revenue Management. Supporting the traditional sales team and management was the sales operations team with responsibilities around incentive compensation, territory and quota planning, sales metrics and reporting and sales forecasting as well as sales engagement and enablement tools and applications. Aligned with this functional area under the CRO is another set of roles and functions called revenue operations or RevOps.
The pandemic has had many profound impacts on organizations and their workforces, particularly the need to manage workers differently. Fewer face-to-face interactions make it difficult to “read” employee sentiments and reactions, even with the assistance of artificial intelligence. Employers are faced with the challenge of managing engagement more closely given unprecedented levels of change in policies and corresponding practices.
Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a unified view of all data. Its code generation architecture uses a visual interface to create Java or SQL code.
Traditionally, price management and optimization have been contained to certain industries, such as large-scale manufacturing and chemicals. Those industries involve potentially tens of thousands of stock-keeping units (SKUs) covering a wide variety of products and price points. For many organizations, pricing systems are “cost plus” or “follow the leader,” not typically designed to invoke optimization but rather just move pricing along. Price management is often seen as a complex, arduous task that yields small returns for the effort it dictates, and not a strategic lever.
When migrating their communications stacks to the cloud, many organizations come face to face with a quandary: do they emphasize the business phone system and gravitate toward a unified communications vendor? Or should they focus on the specific applications needed for running their contact centers and seek out a CCaaS vendor?
Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As such, the ability to manage and process data across multiple clouds and data centers is a growing concern for large and small enterprises alike. Almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research study are using cloud computing for analytics and data, of which 42% are currently using more than one cloud provider.
How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but why leave this evaluation to chance? Why not be more explicit about what results are expected?
Digital transformation of the Office of Finance has been a recurring theme for several years, but adoption accelerated when offices were locked down and organizations had to collaborate remotely. It involves shifting manual work, often completed via spreadsheets circulating in emails, to software and systems for improved performance.
When NICE acquired inContact in 2016, it began a transformation that saw it broaden its product offering and positioned itself to play a larger role in the contact center and customer experience industries. It was a prescient move, creating a firm that could supply end-to-end contact center functionality in the cloud. And it anticipated today’s market dynamic, in which NICE and its competitors are racing to define (and capitalize on) the post-contact center future.
Topics: Customer Experience, Voice of the Customer, Business Continuity, Analytics, Contact Center, Data, Digital transformation, AI and Machine Learning, agent management, Digital Business, Experience Management, Customer Experience Management, Field Service, customer service and support
Our research shows that nearly all financial service organizations (97%) consider it important to accelerate the flow of information and improve responsiveness. Even just a few years ago, capturing and evaluating this information quickly was much more challenging, but with the advent of streaming data technologies that capture and process large volumes of data in real time, financial service organizations can quickly turn events into valuable business outcomes in the form of new products and services or revenue.
In my recently published Analyst Perspective “Selecting an HCM System? Include the Tougher Use Cases in Evaluations,” I highlighted a few HCM systems use cases that have historically been under-supported across the vendor/product landscape. My view on “critical HCM use cases” is the same today as when I led global HR and HR technology initiatives: use cases flow from the business imperatives faced by nearly every organization and their associated workforce-related implications. These HCM business imperatives range from elevating organizational agility—which I define as the ability to rapidly respond to both potential business risks and opportunities with optimal workforce-related actions and decisions—to delivering a superior employee experience or “EX” which directly correlates with a great customer experience and therefore business performance, to continuously focusing on ways of improving employee productivity, as even modest productivity gains can translate into major value creation.