When people are not matched well to who they work with and what they work on, you cannot expect them to perform well.

That’s why we’re building a machine learning-based recommender system for teams that takes into account employee skills, talents, psychometric profiles, teamwork preferences, and more. Good teammate fit means both higher work satisfaction and higher performance! The more data we gather and the longer you use dodowork, the more accurate the team-matching predictions will become.

And what if you don’t have the right talent in your company to match a project’s requirements? We’ll help you identify who exactly you need and find the right people outside (think contractors, freelancers, retired employees…).

The bigger the company, the more time employees waste at work… to find the information they need to do their work. Oftentimes though, it’s enough to ask someone for help. But how to find that person, when he or she can be in a different project, another department, or even a whole other country?

Our know-how sharing module will help your employees get to the right people fast, cutting the time required to get to the know-how they need to do their jobs. It will also facilitate scheduling know-how exchange sessions needed for day-to-day work, project kick-offs, onboarding, inside / outside mentoring, and more.

The data gathered from the team-matching and know-how-sharing modules will allow you to make better decisions about things like:

• what skills are missing;
• what know-how employees are looking for most often;
• upskilling and reskilling;
• internal and external hiring;
• … and whatever else you can think of.