Spring is colder than usual in Finland, but our product team is on fire. What’s new in April:
Let’s dig into the details.
It’s now possible to define allocations in hours. You can choose your default allocation unit depending on what works best with your business model. To allow for flexibility, you can override the default setting and choose between percentages, workdays, or hours when creating an opening. You can define the setting for each opening separately.
All allocation views now support switching between percentage and hour-based views for individual projects or the entire people or project portfolio. As an added bonus, you can now view deviations in the Allocations view under the People tab.
Hour-based allocations can only be enabled by Agileday staff, so contact us if you’re keen to try them out.
With the new Team blueprint feature, you can greatly reduce the time it takes to create the right openings for an opportunity. Our AI Sales Assistant analyzes opportunity context (like RFPs or customer requirements) to propose a team setup with proper roles, skills, and allocations. It translates complex input into a structured team plan tailored to the opportunity.
By automating team design, Team blueprint enables faster, more precise responses, improves sales-delivery collaboration, boosts bid quality, and suggests optimal staffing models for better talent use from the outset.
The Team insight feature generates a rationale for why a particular team is a great fit for a given opportunity. This feature is a crucial part of the AI flow, where you first enrich your opportunity, create openings, find the right candidates, and, finally, generate team insights to be used, for example, in your sales presentation or email.
The AI model uses an opportunity’s context and proposed team members to craft messaging that showcases both collective strengths and individual contributions. This will enhance your proposals, build customer confidence, and add clarity to bids.
We believe Team insight will improve your chances of winning deals by aligning the team’s narrative with customer needs and expectations.
Thanks to our new Reference story builder, writing reference stories is now faster and more precise. Instead of manually writing about a project, its challenges, solutions, results, and so on, let our AI model do that for you. It knows the project details, resulting in an accurate (and well-written) reference story of the project.
To keep you in the driver’s seat, you can edit the AI-generated content by hand or give the AI more instructions for improving the content.
We hope this feature will change the way you think about writing customer stories. Give it a spin!
Last but not least, here are some more minor improvements and fixes we’ve released:
That's it for April, see you again next month. Until then, let us know if you have any questions.