Describe the problem before the solution
Instead of using "artificial intelligence," write down what work is slow, expensive, or prone to error. Find out who has the problem, what condition, and how often. The same approach applies when talking about the connection of manufacturing and digital systems: the investment in sensors or automation must be linked to a use scenario first.
Complete the brainstorm with a selection method
In the process of generating ideas, eliminating options early can reduce diversity. However, at the end of the meeting you need to make a choice based on impact, applicability, data need and dependencies. Do not turn every idea into a big project. Take the option to test the most uncertain assumption with the smallest trial.
Rewrite the experiment's stopping condition
Let it be clear who will participate, what will be observed, and what finding will change the decision to continue. Do not turn a failed experiment into an indefinite development. Kortex Digital Reklam Ajansı product description can relate the decisions on the prototype and user experience side to this learning. Technical applicability and operational capacity should be evaluated together with relevant teams.
Check before you start
- Is the real problem defined?
- Has the most risky assumption been chosen?
- Do they have any go-ahead and stop measures?