Harvest is a time of reaping crops when they are ripe and ready for gathering. It signifies the bounty of nature, hard work, and the culmination of a year's worth of farming efforts.
Harvest Time Tracking allows individuals and companies to track their time and expenses, making it easy to determine where you’re spending your time, which projects are profitable and to easily produce invoices and forecasts.
With Databox, track your Harvest time tracking KPIs alongside metrics from the other project management, marketing, sales, customer service and accounting software you use on any device: computer, mobile, Apple Watch, TV display and Slack. By building reporting dashboards with data from Harvest and other tools, you can make sure the work you’re doing is producing the desired outcomes, and report effort alongside results to your team and clients.
Get started in minutes by connecting your Harvest account and using one of our templates below, or add any of the metrics below to an existing or new dashboard of your own design.
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When setting up Harvest metrics, reports, goals, or notifications to show data ‘by Projects’ in Databox, always select the Project with an ID number attached in the drop-down menu. Namely, Databox adds project ID number to the names of the dimensions (Projects in this case) in order to make them unique and identifiable. Using dimensions with no project ID number in ‘by Projects’ dimensional metrics may result in data discrepancy.
For time entries metrics, such as ‘Hours Tracked’, ‘Billable Hours’, etc, including dimensional metrics (e.g. ‘Hours Tracked by Clients’), Databox reports on rounded hours. If exact time entries values from Harvest User Interface are compared with data in Databox, a slight discrepancy might be noticed in Databox due to rounding the hours. More information on time rounding in Harvest can be found in this link.
If the time zone or the first day of the week is changed in the Harvest Account user interface after the Data Source is connected in Databox, this could result in duplicated data in the Databox Account. In such cases, there are two possible workarounds: