IBM has added a new layer to its Planning Analytics portfolio with the release of Planning Analytics On Demand.
The new offering is intended for SMBs and enterprises seeking to migrate individual departments from manual budgeting and forecasting processes to an automated, artificial intelligence (AI)-powered process.
Many organisations, large and small, still rely on manual processes using spreadsheets for budgeting and forecasting, including demand planning, salary planning, merchandise planning and more. When performed manually, this process can take days or even weeks. Enterprise planning systems such as Planning Analytics On Demand promise to bring that time down to hours.
IBM’s existing Planning Analytics powered by TM1 enables a collaborative planning process in which data is connected to a central hub, with workflow approvals and review.
"Where we see Planning Analytics On Demand coming in is an extension to that," says David Marmer, vice president of Offering Management for Planning Analytics at IBM.
"While it's become a mission-critical system for our clients, it can also sometimes be a barrier for new departments to onboard them or evaluate new use cases that they might want to go to because it's managed by their systems team, who would then have to go through that process."
Among the AI-powered capabilities of the offering is the ability to ingest existing Excel spreadsheets used for planning and use them to build a collaborative model and generate dynamic dashboards
"The other area that we generally see with AI is the ability to identify variances in plans and things like that that may come from exogenous data," Marmer says.
Marmer says these capabilities are essential to help organisations move from an annual planning process based on historical data to a more dynamic rolling forecast process based on current data that gives them greater agility in the face of quickly moving events such as the global Covid-19 pandemic.
He points to one IBM customer, which manages many restaurants, that is using Planning Analytics to understand various scenarios based on when government-imposed shutdowns of in-restaurant dining end.
"They were seeing a 30 percent drop in business," Marmer says. "They still had a takeout business, delivery business, and curbside pickup, but without having the dining services, that's a challenge to them. They've been able to go back and model exactly this: If this is the expected time to open, this is what it means, and this is when I need to bring resources back so I can manage my capital allocation better."
Planning Analytics On Demand is designed to allow a department or user to sign up and get running quickly. It has a starting price of $45 per month for one authorised user and a single 2GB application database, and additional users can be brought on for $40 each.
The software uses natural language processing to capture and analyse human language data and then recommend improvements to the planning process. Other machine learning capabilities help clients create what-if modelling scenarios without turning to a data scientist.
"They can create models, workbooks, invite others to participate, much like they would do in a system that was managed by their systems team, but now they can do it self-service on their own," Marmer says.
Planning Analytics On Demand also includes tutorials and demos, as well as the ability to add users and applications as needed.