The challenge
Consulting delivery involves information moving between people, products and platforms. Manual handovers can mean repeated data entry, inconsistent records and time spent checking whether the next step happened.
Automation can help, but it also carries the assumptions of the process it implements. Unclear ownership or unreliable input data can become harder to see once a workflow runs in the background.
My role
My work brings together automation frameworks, integration platforms, data governance and custom tooling across professional services. That includes the engineering direction behind connecting systems and turning scattered delivery data into more reliable insight.
The tooling includes Workato, n8n and Airflow, alongside SQL, Python, ETL and reporting. The choice depends on the workflow, its operational needs and the people who will support it.
The approach
Understand the process first
Identify the trigger, the information required, the decision points and the expected outcome. Clarify which steps are repeatable and where someone needs to exercise judgement.
Make the data contract explicit
Define required fields, identifiers and ownership of each record. Validate information before acting on it, and decide how changes and duplicates should be handled.
Design the exception path
A workflow needs a response to missing data, unavailable systems and partial completion. Make failures visible, support safe retries and give someone a clear route to intervene.
Build for the next person
Document the purpose, dependencies and recovery steps. Reusable patterns, source control and clear ownership make an automation easier to maintain as the surrounding process changes.
The important trade-offs
- Automation and judgement. Automate repeatable actions and keep decisions requiring context visible to the right person.
- Platform features and custom code. Use the platform where it makes operation simpler; add code when the requirement justifies the maintenance cost.
- Immediate value and long-term support. The happy path is only part of the solution. Monitoring, exception handling and ownership need attention too.
- Reusable patterns and specific needs. Share the common parts without forcing every integration into an unsuitable template.
What success should look like
Useful measures include manual touches, processing time, exception rates and the effort required to support the workflow. Reliability matters as much as the number of steps automated.
The intended result is a process people can trust and a team with more attention available for work that needs their expertise. These describe the outcomes to evaluate, not quantified project results.