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Actabl Continues to Improve Visibility Into Labor Forecasting With the Integration of ProfitSword and Hotel Effectiveness

Hospitality Net

Actabl, the hospitality software company that enables hotels to drive profit through actionable insights, announced that it integrated two of its award-winning products, ProfitSword and Hotel Effectiveness, to support more efficient hotel labor management.

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Actabl Partners with Avalara

Hotel Business

Hotel management companies can leverage ProfitSword’s data consolidation and send it to Avalara, automating their tax compliance and reconciliation processes. Avalara’s partnership with Actabl allows hotel management groups to divert their aggregated data via ProfitSword to Avalara.

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Better Together: Actabl Celebrates One Year of Innovation and Growth

Hospitality Net

The company unites four renowned software solutions — ProfitSword, Hotel Effectiveness, Alice and Transcendent — to streamline operations, enhance profitability and empower the people who power the hospitality industry. Today, Actabl serves more than 12,000 properties.

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Actabl sees record growth six months after launch

Hotel Business

New industry partnerships Actabl has partnered with Dimension Hospitality to activate both ProfitSword and Hotel Effectiveness by Actabl to enable data-driven decision-making and deliver labor optimization solutions to its 80 hotels across the U.S.

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This New Integration Signals the Next Phase of Hotel Labor Controls

Larry Mogelonsky

As a provider of a suite of operations and asset management solutions, Actabl has recently completed a full integration between Hotel Effectiveness – the company’s labor management and optimization platform – and ProfitSword – its enterprise BI platform – ostensibly an industry first in terms of the nature of this interface.

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Finding Hidden Cost Savings Using Actabl’s Integrated Hotel Platform

Larry Mogelonsky

Specifically, Moore showed us a visualization dashboard within ProfitSword for a portfolio where the insights engine effectively filtered the multitudes of siloed data to show which properties had higher utilization over normalized expectations. How is this done, though?