David Menninger's Analyst Perspectives

In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations find it challenging to access data sources and integrate data and analytics in business processes. Vendors such as IBM offer a broad set of analytics tools with self-service capabilities that allows organizations to reduce IT dependencies and enables decision-makers to recognize performance gaps, market trends and new revenue opportunities. Its technology can simplify data access for self-service applications, enabling users to make business decisions informed by insights and take the guesswork out of decision-making. IBM is a leading software provider and has offerings in almost all business sectors. IBM Business Analytics offers data analytics and artificial intelligence (AI) with an integrated workflow to enable organizations to implement data-driven decisions and reduce data and process silos. IBM Cognos Analytics with Watson is its business intelligence (BI) solution that can integrate reporting, analysis, dashboards, stories, explorations, modeling, and other functionality. Users can access data modules, packages, datasets, and uploaded files as sources of data. Reports and dashboards continue to be the most important type of analytics for organizations. Our research shows that more than three-quarters of users still use traditional reports and dashboards to drive insights. Some of IBM’s other offerings include its Planning Analytics for budgeting and forecasting, Watson Studio to automate MLOps, SPSS for advanced statistical analytics, and CPLEX to build optimization models. Ventana Research has examined various IBM offerings as part of our focus on data and how organizations are adopting strategies to derive greater value from analytics. My colleague Matt Aslett recently covered IBM Cloud Pak for Data in his perspective. Cloud Pak combines the functionality for data compute, management and governance with automation and AI to support self-service analytics and data science. Our colleague, Rob Kugel, has covered IBM Planning Analytics in the past. IBM has invested heavily in augmented intelligence research that builds on its existing technology ecosystem. I’ve written previously on how organizations can use augmented intelligence to reduce dependency on artificial intelligence and machine learning (AI/ML) skills. It can enable organizations to automate AI/ML analyses and accelerate business processes. As large enterprises continue to evolve in response to constant competitive pressures and unforeseen events, they need a broad range of analytical capabilities. IBM can help organizations keep up with the increasing volume of data and analytics workloads, improve processes and potentially reduce IT costs. IBM recently announced new software designed to help enterprises break down data and analytics silos to facilitate data-driven decisions and navigate unpredictable disruptions: IBM Business Analytics Enterprise, which is a suite including Cognos Analytics with Watson and Planning Analytics with Watson; and also IBM Analytics Content Hub, which enables users to access analyses from multiple vendors in a unified dashboard. Our research shows that organizations have an increasing need for analytics and planning tools, and they are looking for technologies that can help them accelerate their processes. IBM had also previously announced an expansion to its embeddable-AI software portfolio with the release of three new libraries designed to help IBM Ecosystem partners, clients and developers build their own AI-powered products and bring them to market. This expansion allows users a scalable way to build natural language processing (NLP), speech-to-text and text-to-speech capabilities into applications across any hybrid, multi-cloud environment. IBM has made strides in bringing its products together but must continue to do to align them even more closely together, so users can seamlessly move between products. Organizations need a broad set of analytics capabilities, and the IBM portfolio provides those capabilities along with an ecosystem where users can perform all types of analysis. I recommend that organizations that are in the process of becoming data-driven evaluate IBM’s data and analytics capabilities. Their portfolio enables organizations to integrate enterprise data and allows them to build digital, operational, analytical, data science and AI models, and automate processes using intelligent workflows. Further, IBM enables users to deploy data science, predictive analytics, and data visualization within its unified ecosystem to gain insights and accelerate decision-making. And IBM’s Watson is helping to expand its augmented intelligence capabilities to make analytics easier to use and more powerful. Regards, David Menninger

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