Workflow discovery
Document current steps, owners, triggering events, source-of-truth systems, exceptions and expected decisions.
Automation / Business Workflows
Automate the workflow you can define, observe and recover.
Automation is most effective when the business rule and the source of truth are known. D2 maps the real handoffs, determines what can safely run unattended and leaves high-impact approvals under the client's control.
Direct answer
Which business processes are suitable for workflow automation?
Start with a repeatable process that has a clear trigger, reliable inputs, a defined decision rule, an accountable owner and a measurable output. Processes with uncertain data, changing approvals or no recovery path should be standardized before they are automated.
Buyer fit
When this research or operating scope is relevant
- Operations teams copying approved data between systems
- Managers handling recurring validation, notification or document handoffs
- Teams needing audit trails for predictable processes and exceptions
Work scope
What D2 would evaluate and deliver within an agreed scope
Integration design
Specify permitted APIs, data contracts, transformation rules, credentials, idempotency and approval checkpoints.
Controlled operation
Build staging tests, failure alerts, retry policies, reconciliation logs and a human recovery runbook.
Reviewable outputs
Deliverables that can be checked before acceptance
Process map and ownership matrix
A step-by-step specification connecting triggers, business rules, actors and source systems.
Tested automation workflow
Configured workflow with representative input, output, duplicate and failure cases.
Handoff and support runbook
Monitoring responsibilities, exception owners, rollback steps and agreed change process.
Delivery sequence
A bounded first engagement, not a universal promise
STEP 01
Select and baseline one high-friction process
STEP 02
Prove the data contracts and stage the happy path plus failure cases
STEP 03
Accept the workflow against measurable checks before production handoff
Evidence and QA checks
- Client must approve source system permissions and data handling.
- Idempotency and retry behavior require scenario tests, not a checkbox.
- Performance claims need pre- and post-deployment operational evidence.
Scope boundaries
- D2 does not replace accountable owners or authorize consequential actions without an approved workflow policy.
- Unstable source data and undocumented human judgment are discovery blockers rather than automation promises.
Sources, market access and implementation responsibilities are assessed during discovery. Examples here describe the method, not verified client results.
Frequently asked questions
What to clarify before starting
Should we automate our whole department at once?
Usually not. Begin with one owned process, establish a baseline and expand only after the failure and exception paths have been tested.
Does every automation need AI?
No. Deterministic rules, validation and APIs are often more appropriate; AI can be evaluated separately when unstructured inputs justify it.
What happens if an integration fails?
A production-ready scope defines retries, monitoring, record reconciliation and a manual recovery owner before go-live.
Discuss a scoped engagement
Start with your business problem, existing systems and constraints.
D2 can assess fit, delivery boundaries and evidence requirements before proposing an implementation or research engagement.