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October 24, 2019

IBM Adds AI to Planning Analytics

George Leopold

Among the emerging enterprise applications for AI are cloud-based business intelligence tools that can be used to collect, organize and explore financial data, helping planners move beyond their beloved spread sheets to build predictive models that can be used, for example, to generate more reliable budget forecasts.

Players like IBM (NYSE: IBM) are promoting AI-based business intelligence platforms and “planning analytics” tools that can be used to improve data exploration and, therefore, self-service analytics, along with the ability to compile and then tweak financial forecasts.

They make the case that repetitive analytics tasks are prime candidates for automation while emerging AI tools can boost the ability of business analysts to sift through ever-larger rows and columns of financial data. The more variable that can be analyzed using cloud-based AI, the more columns of data available to help reduce bias in business intelligence applications, said Mike Norris, director of product management for IBM Business Analytics.

The centerpieces of IBM’s AI-backed cloud analytics initiatives are its Cognos Analytics platform and a “planning analytics” tool running on its TM1 client-service architecture. (TM1 stands for “Tables Manager 1).

Those planning analytics tools are designed to run on IBM’s Cloud Pak data analytics platform that among goals seeks to reduce data movement by applying AI tools to data, not the other way around. The hybrid approach allows customers to use any cloud or access data on-premise.

The planning analytics tool aims to promote collaboration across organizations as more self-service analytics tools are deployed. While budget forecasting and other planning tasks are being transformed by new business intelligence tools, IBM notes that clients are unwilling to dump their Microsoft Excel spreadsheets.

Hence, IBM product manager Paul Glennon said its planning analytics tools includes an Excel interface as a way to promote adoption and allow planning analytics users to “hit the ground running.”

That gateway option along with hybrid deployment options are designed to entice users to test drive self-service reporting and visualization tools. In one financial planning scenario, Glennon said, budget forecasters might complete their quarterly projection ahead of schedule, giving them the opportunity to fine-tune a final forecast that incorporates fresh data.

IBM executives stressed during a company event this week in Miami that its suite of Watson-based tools seek to reduce the movement of data by applying automation to large data sets. Once data is cleansed and combined, said Rachel Su, an IBM product manager, AI-based queries can be used to drill down into business data.

Ultimately, Norris added, IBM’s analytics tools running on Cloud Pak are designed to “make data available in a holistic way.”

IBM, Oracle (NYSE: ORCL) and SAP (NYSE: SAP) ranked among leaders in recent industry surveys of the planning analytics market. IBM is seeking to differentiate its cloud analytics offerings by bringing new Watson-based analytics tools to the table that can help “shape” large data sets for analysis.

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