I have spent the last ten years building and using tools to run teams.
Most tools do it incorrectly since they mix the "context" and "decision" into one big data soup. What is context data? The data helps users make decisions, for example, historical messages for email/communication software and state of the orders for e-commerce software.

Why is it wrong?

Data format for "context" is complex, takes a lot of time to make it right and is not uniform between different applications. This is what AI agents will disrupt in a few years.

However, most of the decisions in business are about humans.
Who is the best customer service? Who is the worst customer? What managers are killing, and what always makes the wrong decision? What team works in harmony, and what team struggles to make the smallest decision?

Those questions have nothing to do with "context" data, but they are mixed up in the context data, which is tough to extract. Also, the nature of work is changing where one person tends to take up more than one role and running an organisation requires a much more holistic view than before. Data should present humans as it is, not cogs in a machine.

How to make it right?

It is straightforward: separate "context" and "decision" data.
SyncVote can act as the "decision" data, while other "context" data can be built with software packs like Airtable, and the Interface is a chatbot.

This design would accelerate the speed of building tools and enable organisations to change workflow and protocol on the fly without rebuilding the whole software infrastructure.