How do we choose our first use cases?

First use cases are often chosen because they are visible: an assistant for customers, a spectacular tool for the sales team. Or because a supplier offers them ready-made. They get off the ground quickly, and often disappoint.

A good first case is judged on three levels. Its impact: does it touch a flow the company really depends on? Its feasibility: does the necessary data exist, and is it reliable enough? Its effects: what happens to the departments upstream and downstream when this step changes? The case that ticks all three is rarely the most visible.

• The most profitable cases are often discreet.Handling cases, matching documents, preparing a decision: not spectacular, but at the heart of how the company runs.
• Feasibility is often overestimated at the start.Along the way, it turns out the data is incomplete, scattered or inaccessible.
• The effects on neighbouring departments are almost always forgotten.The gain for the department concerned is assessed, rarely what it changes for the others.

1. 01List a dozen candidates, and score each one on impact, feasibility and effects on neighbouring departments.
2. 02Before choosing a case, open the files and check the data it needs for real.
3. 03Choose a first case that can succeed within a few months, and that serves a broader direction.

We help leadership teams choose their first uses from a map of the company, not from a catalogue.

• Where do you start when you do not know where to start?→
• How do you measure the return on investment of an AI project?→
• Can automating one department unbalance another?→
• Is one big project better than several small ones?→