Business phone systems and contact center platforms received renewed attention in 2020 as organizations acquired tools for agents working from home. That put the spotlight on vendors, like Avaya, that have feet in both worlds. Since both forms of communications technology are well-suited to the cloud, Avaya has developed its Unified Communications as a Service (UCaaS) and Contact Center as a Service (CCaaS) portfolios in parallel. The effort has borne fruit, with significant product enhancements notched recently. Ventana Research asserts that by 2023, one-quarter of organizations will to UCaaS and CCaaS technologies to collaborate in the enterprise and with customers more effectively.
Many of us who have operated within the human resources profession or been involved in strategic initiatives aimed at placing the workforce at the center of competitive advantage (aka human capital management endeavors), thought we were at least conversational about predictive HCM tools. We were aware that industrial and organizational psychologists have, for decades, been creating skill- and personality-based assessments using predictive algorithms that stood up to rigorous testing, and how tools such as the Hogan or Myers-Briggs tests became industry standards.
The amount of data flowing into organizations is growing exponentially, creating a need to process more data more quickly than ever before. Our Data Preparation Benchmark Research shows that accessing and preparing data continues to be the most time-consuming part of making data available for analysis. This can potentially slow down the organizational functions which depend on the analysis results. Trying to get ahead of the backlog with incremental improvements to existing approaches and traditional technologies alone can be frustrating.
The ERP system is at the core of nearly every organization’s record keeping and business process management. Its smooth and uninterrupted functioning is essential to an organization’s accounting and finance functions. In manufacturing and distribution, ERP manages inventory and logistics. Some organizations use it to handle human resources functions like tracking workers, payroll and related costs.
Organizations are becoming more and more data-driven and are looking for ways to accelerate the usage of artificial intelligence and machine learning (AI/ML). Developing and deploying AI/ML models can be complicated in many ways, often involving different tools and services to manage these solutions from end to end. Accessing and preparing data is the most common challenge organizations face in this process, and consequently, AI/ML vendors typically incorporate tools to address this part of the process. But there are many other steps in the process as well, such as coordinating the handoff between data scientists and IT or software engineers for deployment to production. This can potentially slow down the entire data-to-insights process. End-to-end platforms for AI offer the promise of simplifying these processes, allowing teams that work with data to improve organizational results.
IBM Planning Analytics, formerly known as TM1, is a comprehensive planning and analytics application designed to integrate and streamline an organization’s planning processes. It can support multiple planning use cases on a single platform, including financial, headcount, sales and demand planning. The software automates enterprise-wide data collection to make it repeatable and scalable across multiple users and departments. It supports sophisticated driver-based modeling that enables rapid what-if or scenario-based planning, while its built-in analytics provide deep business intelligence capabilities. This enables senior executives and managers to work interactively to immediately assess their current position and consider the impact of various options to address opportunities and issues rather than laboring through a lengthy process.
Process-mining software isn’t exactly new, but it’s also not widely known in the software technology market. The discipline has been around for at least a decade, but is generating more interest these days with both specialist vendors and major enterprise software vendors offering process-mining products and services. We assert that through 2022, 1 in 4 organizations will look to streamline their operations by exploring process mining.
Digital commerce affects almost everyone’s lives. It is hard to remember a time when one could not sign on to a website like Amazon, order a product, pay for it and have it delivered to your front door within days, not weeks. Although catalogues have been around for a century or so, the digital-commerce revolution has changed the way we think about shopping for many of our everyday and special occasion products. Extend this to digital services, such as streaming videos or online games, and there is barely a sector that has not been touched by digital commerce. And, for organizations, it is an essential component of their revenue-management efforts that enables the digital transformation and monetization of goods and services.
Organizations have long sought ways to achieve a fast but “clean” (accurate) financial close. The most widely accepted benchmark is to be able to close within one business week. Organizations that close within a business week are almost always more competent in how they manage the process and therefore use resources more efficiently. Also, organizations that close their books within six days after the end of the quarter are more likely to provide executives with timely information and respond to markets and competitors with greater agility. While there have been some improvements in efficiency from modern accounting systems, our research shows that one-half of organizations still take more than a business week to complete their quarterly close.
Organizations are accelerating their digital transformation and looking for innovative ways to engage with customers in this new digital era of data management. The goal is to understand how to manage the growing volume of data in real time, across all sources and platforms, and use it to inform, streamline and transform internal operations. Over the years, the adoption of cloud computing has gained momentum with more and more organizations trying to make use of applications, data, analytics and self-service business intelligence (BI) tools running on top of cloud-computing infrastructure in order to improve efficiency. However, cloud adoption means living with a mix of on-premises and multiple cloud-based systems in a hybrid computing environment. The challenge is to ensure that processes, applications and data can still be integrated across cloud and on-premises systems. Our research shows that organizations still have a significant requirement for on-premises data management but also have a growing requirement for cloud-based capabilities.
The challenges of the pandemic prevented auditors from visiting client offices, which led to widespread adoption of remote audit processes. Although there are outward similarities between a remote audit and a virtual audit, they aren’t the same. A remote audit uses technology to adapt the existing audit processes to an environment where in-person interactions are impossible. A virtual audit uses technology to redefine and streamline how auditors conduct an annual audit.
Having just completed the 2021 Ventana Research Value Index for Analytics and Data, I want to share some of my observations about how the market has advanced since our assessment two years ago. The analytics software market is quite mature and products from any of the vendors we assess can be used to effectively deliver information to help your organization improve its operations. However, it’s also interesting to see how much the market continues to advance and how much investment vendors continue to make.
Topics: Big Data, Key Performance Indictors, embedded analytics, exadata, Analytics, Business Collaboration, Business Intelligence, Collaboration, Data Preparation, Digital Technology, natural language processing, Conversational Computing, AI and Machine Learning, collaborative computing, mobile computing
Irked by the need to account for every penny of his college expenses, poet Robert Frost penned the lines:
I am happy to share insights gleaned from our latest Value Index research, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Data 2021 is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to analytics and data vendors supporting the spectrum of business intelligence. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ adaptability, capability, manageability, reliability and usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor validation.