Customer Use-Cases: Executive View

Not sure how to structure your executive view? See what works for other companies!

We'll work with you to understand the best way to aggregate information for your org. We can use any combination of fields to understand work in initiatives, themes, quarters, teams - you name it! For a high-level explanation, see our main article on the executive summary. For inspiration, you can see some of the different examples from our current customers below: 

Understand Status at a High Level

Some companies care most about health by team, some care about health by product line. We can help you group work in whatever subset matters the most to you. The example below is how one company monitors overall health and progress of work by getting a summary by each product team.

Highlight Key Projects

We can aggregate project status and progress into themes, OKRs, or big rocks and highlight the top priority projects within them. There are some things you need to see at the high level and some things that you want to track the details of - because they're just that important. The company below tracks their work categorized into "Big Rocks". However, within the dozens of projects across Big Rocks, they also have 3 critical projects they care about every detail for.

What About Teams Outside of R&D? 

We all know that it's not just the development that dictates whether a release or launch will be successful. We also need to worry about the marketing, customer education, and other GTM activities that are part of the Launch process. We can separate what's "Under Development" primarily in the R&D org to what is going through the "Release Process" and in the hands of the GTM team

Only Look at What Has Changed

Maybe you don't have time to review all projects, but you need a little more detailed than a top-level status. We can help you pull out the changes or insights that matter the most to you. The company below highlights all the work that's "At Risk" or "Off Track" as reported internally by their teams as well as what's flagged by Velma based on our machine learning models.