Forecast.it is built on the philosophy, that we can use technology to do things faster and more efficiently. You could run all your projects on your notepad and have the team track their time on an old school timesheet.
You could employ five assistants to keep your timetable and project boards up to date, and you could just celebrate finished projects and hope that the money paid will cover your expenses. But this is not the 60'ies, and the name on the door is not Sterling Cooper.
Here is how Forecast applies machine learning and artificial intelligence to help you plan and run projects more efficiently.
When you ask a team member, be it a designer, developer or writer how long he or she thinks a specific part of the project will take, there is a high risk that the first estimate will be wrong.
But when you use Forecast, you input a low and high estimate, and one or more tags for the type of task you're dealing with. Then based on the type of task, previous projects, that team members previous performance, and data from other similar industry projects, Forecast applies complicated math to give you a much more accurate estimate. And since it's a learning system, estimations reach 95% accuracy over time.
As your project develops and tasks get more specific, you simultaneously provide the system with more data. And since the machine is constantly learning how your team works, Forecast.it helps you update your project estimates. This helps you catch unforeseen delays and either make corrections or at least communicate early with your client or boss. The technology sort of acts like an all-seeing project assistant with a math degree on steroids.
Some call it business intelligence, but more often than not you're dealing with a series of spreadsheets. Sheets that need manual updating and are either out of date or only maintained by the CEO or CFO.
Forecast.it instead take advantage of having all the data having the raw mathematical power to just tell you, if your project is profitable, how much money your team is making and whether or not your favorite client is also bringing in the most for the bottom line.
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