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Anaplan Is Not the Only Vendor to Benefit From the Growing Need for Intelligent Business Planning

Multibillion-dollar firms still primarily use spreadsheets for demand forecasting, but this approach leaves a lot of room for enterprise software vendors to displace manual work with solutions better suited for large enterprises, and hence gain significant revenue in this space.

Anaplan, a leading provider of cloud-based business planning software for large enterprises, announced its first quarter fiscal results last month, reporting total revenue of $75.8 million, an increase of 47% year-over-year. Subscription revenue was $65.1 million, an increase of 45% year-over-year.

This is in light of generally disappointing earnings across enterprise software vendors posted in recent months.

Anaplan is also anticipating between $77.5 and $78.5 million for its second quarter, with its non-GAAP operating margin expected to be between negative 25.5% and 26.5%.

“We are very pleased to start our fiscal year with strong first quarter results. This is an indication of our continued success with our Connected Planning solution,” said Frank Calderoni, chief executive officer at Anaplan. He explained, “Our customers are consistently impressed with the value they receive from the results of deploying Anaplan across their enterprise.”

Our Take

Good S&OP and overall business planning processes fuel and enable clockwork operations of the supply chain. Nevertheless, such planning requires a combination of heavy history-based analytics with art-like elicitation and heuristic prediction of sales aspirations. Multibillion-dollar firms still use spreadsheets as the primary means of addressing such planning exercises. Of course, this gap leaves a lot of room for enterprise software vendors to provide (expensive) solutions touted as better suited for the needs of an enterprise, and hence they gain significant revenue in this space.

The promise of automated planning, however, hinges on maturity of the planning processes, which in principle should be tried out on paper first. Otherwise, there is a very high risk of gaining little to no value from a very significant investment. Predictive analytics, machine learning, and AI bring a lot of hope into the future of S&OP, but so far this area remains to be dominated by people and processes, and only then technology.

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