Start with the decision to improve
Start with the decision to improve starts by returning to the real work rather than the imagined solution. For “When simple automation is enough, and when you need a real application”, the team should observe the people involved, the information they use, the decisions they make, and the exceptions that interrupt the normal path. This practical view prevents an interface preference from becoming a product requirement and separates meaningful value from scope that only adds volume and maintenance.
At this stage, document one representative example, the owner of the decision, the data required, and the expected result. Then compare it with a difficult or exceptional case. If the rule remains understandable in both situations, it can become a design and validation criterion. If not, clarify the process before adding more automation or software. This discipline reduces rework and makes later trade-offs easier to explain, test, and maintain.
- A real example connected to “Start with the decision to improve”
- A clearly named owner
- A rule tested with a normal and an exceptional case
- A measure that can verify the outcome
Recognise a good automation candidate
Recognise a good automation candidate starts by returning to the real work rather than the imagined solution. For “When simple automation is enough, and when you need a real application”, the team should observe the people involved, the information they use, the decisions they make, and the exceptions that interrupt the normal path. This practical view prevents an interface preference from becoming a product requirement and separates meaningful value from scope that only adds volume and maintenance.
At this stage, document one representative example, the owner of the decision, the data required, and the expected result. Then compare it with a difficult or exceptional case. If the rule remains understandable in both situations, it can become a design and validation criterion. If not, clarify the process before adding more automation or software. This discipline reduces rework and makes later trade-offs easier to explain, test, and maintain.
- A real example connected to “Recognise a good automation candidate”
- A clearly named owner
- A rule tested with a normal and an exceptional case
- A measure that can verify the outcome
Know when an interface becomes necessary
Know when an interface becomes necessary starts by returning to the real work rather than the imagined solution. For “When simple automation is enough, and when you need a real application”, the team should observe the people involved, the information they use, the decisions they make, and the exceptions that interrupt the normal path. This practical view prevents an interface preference from becoming a product requirement and separates meaningful value from scope that only adds volume and maintenance.
At this stage, document one representative example, the owner of the decision, the data required, and the expected result. Then compare it with a difficult or exceptional case. If the rule remains understandable in both situations, it can become a design and validation criterion. If not, clarify the process before adding more automation or software. This discipline reduces rework and makes later trade-offs easier to explain, test, and maintain.
- A real example connected to “Know when an interface becomes necessary”
- A clearly named owner
- A rule tested with a normal and an exceptional case
- A measure that can verify the outcome
Compare maintenance cost with operational value
Compare maintenance cost with operational value starts by returning to the real work rather than the imagined solution. For “When simple automation is enough, and when you need a real application”, the team should observe the people involved, the information they use, the decisions they make, and the exceptions that interrupt the normal path. This practical view prevents an interface preference from becoming a product requirement and separates meaningful value from scope that only adds volume and maintenance.
At this stage, document one representative example, the owner of the decision, the data required, and the expected result. Then compare it with a difficult or exceptional case. If the rule remains understandable in both situations, it can become a design and validation criterion. If not, clarify the process before adding more automation or software. This discipline reduces rework and makes later trade-offs easier to explain, test, and maintain.
- A real example connected to “Compare maintenance cost with operational value”
- A clearly named owner
- A rule tested with a normal and an exceptional case
- A measure that can verify the outcome
Choose an architecture that can evolve
Choose an architecture that can evolve starts by returning to the real work rather than the imagined solution. For “When simple automation is enough, and when you need a real application”, the team should observe the people involved, the information they use, the decisions they make, and the exceptions that interrupt the normal path. This practical view prevents an interface preference from becoming a product requirement and separates meaningful value from scope that only adds volume and maintenance.
At this stage, document one representative example, the owner of the decision, the data required, and the expected result. Then compare it with a difficult or exceptional case. If the rule remains understandable in both situations, it can become a design and validation criterion. If not, clarify the process before adding more automation or software. This discipline reduces rework and makes later trade-offs easier to explain, test, and maintain.
- A real example connected to “Choose an architecture that can evolve”
- A clearly named owner
- A rule tested with a normal and an exceptional case
- A measure that can verify the outcome
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