Decisions are processes, not moments.

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Modern teams ‘self-organize’ first in a way they are best able to consume information and then collaborate within their own circles of trusted humans to validate decisions.

Notion, Google Docs, Slack, Figma are all modern tools that create seamless experiential layers to allow humans to organize information in their own way and collaborate to gain consensus (e.g. polls), enable majority voting (e.g. upvotes), make autocratic decisions and ask for consent (e.g. approval processes).

However, all these methods require an ability to understand, share context and adopt one method over another with awareness!

To enable self-organizing teams to make decisions effectively and efficiently, they must deal with decisions not as “moments,” but as “processes”.

Decision making is a process

Processes are mostly a series of logical questions, the output of one process/question often is the input to the consequent process.

Decision making processes evolve and mature with changing environments or context (that acts as one of the major controlling variable). If you observe how the brain works you will notice that decision-making process often happens in portrait mode in our minds, one step leading to another in a logical fashion.

Let’s take an everyday example

Let’s take an example of an every day situation where you want to decide on your travel to work that is based on today’s context.

Now, let’s imagine that you want to reach work by 9am for a meeting and you want to pick-up food on the way.

You may notice that you gather information from different sources, be it google maps, yelp, train schedule etc to optimise your decision based on what’s happening today. The context of today is almost always different from yesterday. Our brain explores various permutations and combinations to make the best possible decision.

Context + Data → Decisions

Teams rely heavily on data from different sources to make decisions, but often lack the necessary context and understanding to make the best decisions. To ensure teams are making the best decisions possible, they must adopt a process-oriented approach that allows them to create a feedback loop and continuously refine their decision-making process.

Airbook is a modern data solution that helps teams to replicate the way the human brain makes decisions. It provides an experiential layer that allows users to self-organize and collaboratively analyze data, applying logical questions to create a framework for making decisions. This framework includes key decision points, data needed to make those decisions, and criteria for analyzing the data.

Teams can ensure that their decisions are based on the most up-to-date information and that the criteria used is appropriate for the context. This helps teams to avoid the common mistake of using a ‘one size fits all’ approach to consume data and instead become an important part of the value chain of making meaningful business decisions.

Cross pollination of information

Revenue teams today are wildly adopting to tools like Notion, Slack or Google Docs for their daily collaboration needs amongst them where as Jupyter notebooks is now a go-to tool for modern data teams to collaborate amongst their community of trusted data wizards.

Whether they are embeds of a data-frame from Jupyter notebooks or screenshots from dashboards from BI tools, information is often cross-pollinated on either of these systems for the last mile of data-driven decision-making to take place. The need for both of these teams to talk to each other scream for a need for one place where both feel like home!

Today, these note-book style solutions are siloed to be used within revenue and/or data communities separately- the benefits of which must focus on a product-led collaboration which will drive rapid adoption.

These are strong enough signs for a new paradigm shift to take place by making an attempt to bring both data and revenue teams come together, operate and help each other make decisions, all on one page.

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