David Menninger's Analyst Perspectives

The 2022 Market Agenda for Analytics: Enabling Actions and Effective Insights

Posted by David Menninger on Feb 3, 2022 3:00:00 AM

Ventana Research recently announced its 2022 Market Agenda for Analytics, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments in order to improve business outcomes.

1-Jan-24-2022-05-47-46-87-PMIt has been exciting to follow innovations in the analytics market, but for businesses, it can be challenging to stay on top of these changes and find ways to operationalize analytics. To support this, I assert that by 2024, one-half of organizations will include guided analytics processes and storytelling capabilities to help create and deliver insights for line-of-business personnel. We craft our annual market agenda using our firm’s knowledge of technology vendors and products as well as our expertise in business requirements. Through this ongoing research, we offer insights and best practices that help both IT and the lines of business understand this dynamic market segment and use these technologies to their maximum potential.

Our Analytics practice encompasses six focus areas: Artificial Intelligence and Machine Learning (AI/ML), Business Intelligence (BI), Embedded Analytics, Natural Language Processing (NLP), Process Mining and Streaming Analytics. Our overarching Analytics and Data Benchmark Research explores each of these topics, providing insights to guide decision-making. And if you are looking for how well vendors and their products are meeting organizations’ requirements, then review our Analytics and Data Value Index. Here is our view of how each of these areas will advance in 2022.

Artificial Intelligence and Machine Learning

VR_2022_AI&ML_Assertion_1_SquareThe application of AI/ML within organizations is transforming analytics. Opportunities to take advantage of these technologies will increase over the coming year as vendors automate more AI/ML processes and further incorporate AI/ML capabilities in products. Our upcoming research will explore the extent to which these advances reduce the skills needed to reap the full benefits of AI/ML, but we assert that through 2024, AI/ML solutions will remain largely independent of business intelligence (BI) solutions, requiring three-quarters of organizations to maintain multiple, separate skill sets.

For an assessment of how your organization stacks up in its use of this technology, take our short Dynamic Insights Survey on Machine Learning.

Business Intelligence

Business intelligence produces insights from data to guide decision-making, employing an increasing variety of analytic, presentation and deployment techniques. Our recent research finds that reports and dashboards are still an important component of most organizations’ BI efforts, but it also shows growing interest in additional forms of analysis including AI/ML and natural language processing.

The mission critical nature of many of today’s analytics suggests that organizations must integrate their data operations and analytics operations in order to provide the agility needed to be competitive. To support this, I assert that by 2024, one-half of organizations will deploy chatbots and other conversational experiences as a standard BI system capability, making it easier for line-of-business personnel to derive value from their analytics. To create this agility, both the data and analytics processes are often supplemented with AI/ML-based assistance to enable non-technical workers to use these tools more effectively. This year we will continue to study how software vendors are incorporating these changes and how well organizations are able to adopt these advances.

Embedded Analytics

Segregated analytics and business processes are not uncommon, but the resulting analysis is less insightful than can be derived when the two are integrated. Organizations gain a more comprehensive business view through the data that comes from embedding analytics in business processes. I assert that by 2024, more than two-thirds of line-of-business personnel will have immediate access to cross-functional analytics embedded in their activities and processes, helping to make operational decision-making more efficient and effective.

In our recent research, nearly three-quarters (73%) of organizations considered it important to embed analytics into business. Throughout 2022, enterprise software developers and application vendors will continue to refine embedded analytics as BI vendors hone their application programming interfaces, to enable more custom and embedded analytics.

Natural Language Processing

Conversational computing is becoming an increasingly common part of user interfaces. Smart speakers, mobile assistants and chatbots are propelling consumer interest in natural language capabilities. NLP generates narratives based on a set of data values, using text and voice as inputs to access information. And I assert that by 2024, one-third of organizations will adopt NLP as a component of improving digital experiences to business professionals who desire conversational methods via reading and talking.

Many BI vendors have developed their initial NLP capabilities. Future enhancement by ML will improve language recognition, making NLP more accurate and easier to use over time. We continue to explore these issues in our Natural Language Processing Dynamic Insights research, studying these advances and how organizations are embracing them.

Process Mining

VR_2022_Process_Mining_Assertion_2_SquareMost business processes are supported by software. These applications provide a lens into the multitude of operational processes within an organization. In recent years, we have seen the emergence of a new category of technology that mines the information and statistics collected through these processes in order to analyze them and improve them. We assert that by 2024, two-thirds of organizations will examine methods to gain intelligence on the events and activities of people and machines, elevating the importance for process-mining technology.

We have recently added a focus area to study how this information can be analyzed to better understand and improve the operations of an organization. Watch for a new Dynamic Insights study in this area later this year.

Streaming Analytics

Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. The process of using that data is evolving as the amount and frequency of data collection increases. Including streaming data in analytical efforts enhances operational activities and processes to better support real-time decision-making and help make organizations more agile. We will continue to study these issues in our Streaming Data Dynamic Insights research. And the market evolves to support this as by 2024, one-half of organizations will incorporate streaming analytics into their business processes enabling them to respond to opportunities and threats faster.

Analytics is having a major impact across lines of business. It is changing the customer experience, allowing organizations to use data to optimize engagement. It is transforming finance operations, providing insights on performance and enabling more forward-looking planning. It is improving hiring and retention as part of the human capital management process. Sales, marketing and supply chain functions also stand to benefit from the context and guidance that well-implemented analytics can provide. Through our 2022 Market Agenda for Analytics, we will continue our relentless focus on helping organizations realize the valuable operational improvements that can come to light through effective data analysis.

Subscribe to our Ventana Research community to stay up to date on our 2022 research efforts. Visit our Analytics expertise and focus areas for a detailed agenda and our continuously updated 90-day research calendar as well as additional research facts and best practices.


David Menninger

Topics: embedded analytics, Analytics, Business Intelligence, Digital Technology, natural language processing, Process Mining, Analytics & Data, Collaborative & Conversational Computing

David Menninger

Written by David Menninger

David is responsible for the overall research direction of data, information and analytics technologies at Ventana Research covering major areas including Analytics, Big Data, Business Intelligence and Information Management along with the additional specific research categories including Information Applications, IT Performance Management, Location Intelligence, Operational Intelligence and IoT, and Data Science. David is also responsible for examining the role of cloud computing, collaboration and mobile technologies as they affect these areas. David brings to Ventana Research over twenty-five years of experience, through which he has marketed and brought to market some of the leading edge technologies for helping organizations analyze data to support a range of action-taking and decision-making processes. Prior to joining Ventana Research, David was the Head of Business Development & Strategy at Pivotal a division of EMC, VP of Marketing and Product Management at Vertica Systems, VP of Marketing and Product Management at Oracle, Applix, InforSense and IRI Software. David earned his MS in Business from Bentley University and a BS in Economics from University of Pennsylvania.