Migrating from WDFlow to HubFlow: Step-by-Step Checklist

HubFlow (formerly WDFlow) — Top Features and Workflow TipsHubFlow, formerly known as WDFlow, has been gaining traction as a flexible workflow and collaboration platform designed for teams that need a blend of automation, clear process modeling, and real-time collaboration. This article walks through HubFlow’s top features, explains how they fit together, and offers practical workflow tips to help teams get more done with less friction.

What is HubFlow?

HubFlow is a workflow orchestration and collaboration platform that helps teams design, automate, and track processes across departments. It combines visual process modeling, task automation, integrations, and analytics into a single environment designed to reduce manual handoffs and provide visibility into work in progress. The rebrand from WDFlow to HubFlow brought an updated UI, broader integration support, and an expanded library of templates targeted at both technical and non-technical teams.

Top Features

Visual Process Designer

Drag-and-drop canvas for mapping processes with conditional branches, loops, and parallel tasks.
Visual debugging tools to simulate process flows before activation.
Version control for process diagrams so teams can iterate safely.

Automation and Orchestration

Built-in action blocks (email, notifications, approvals, data transforms).
Custom script nodes for advanced logic (JavaScript/Python support).
Event-driven triggers (webhooks, schedule-based, and external system events).

Integrations and Connectors

Prebuilt connectors for common tools: Slack, Microsoft Teams, Salesforce, Jira, GitHub, Google Workspace, and more.
Generic REST API connector for custom integrations.
Two-way sync capability for several supported systems to keep data consistent.

Task and Case Management

Human task assignments with SLA tracking and escalation rules.
Case views that aggregate related tasks, documents, and communications.
Role-based queues and workload balancing.

Collaboration and Communication

In-context commenting on tasks and process steps.
Shared team dashboards and activity feeds.
Real-time presence indicators and notifications across channels.

Data Mapping and Transformation

Visual data mapping tool for transforming payloads between systems.
Support for JSON, XML, CSV and common authentication methods (OAuth2, API keys).
Test harness for validating mappings with sample data.

Monitoring, Alerts, and Analytics

Live process monitoring with per-instance logs and error traces.
Custom dashboards and KPI widgets (throughput, cycle time, failure rate).
Alerting on SLA breaches, failed tasks, or anomaly detection.

Security and Governance

Role-based access control and single sign-on (SSO) support.
Audit trails for process changes and user actions.
Environment separation (development, staging, production) and deployment approvals.

How These Features Work Together — Typical Use Cases

Cross-functional approvals: Design a multi-step approval process with conditional routing, automatic reminders, and escalation to managers when approvals lapse.
DevOps automation: Orchestrate CI/CD steps with webhooks from GitHub, automated testing, and deployment gates that require human signoff.
Customer onboarding: Combine form intake, CRM updating, background checks (via third-party API), and handoff to account managers with SLA tracking.
Incident response: Trigger runs from monitoring alerts, create a case, notify responders, and log remediation steps with timestamps.

Workflow Tips: Designing Efficient Processes in HubFlow

Start with a single outcome
- Define the desired result (e.g., “new customer onboarded with validated billing”) before modeling steps. This keeps the diagram focused and prevents scope creep.
Use modular sub-processes
- Break complex flows into reusable sub-processes (approval module, notification module, data validation module). This improves maintainability and lets teams reuse tested components.
Model exceptions explicitly
- Don’t rely on “edge-case” handling after the fact. Add explicit error paths, compensating actions, and retry strategies in the process design to reduce runtime surprises.
Keep human tasks simple
- Assign clear inputs, expected outputs, and timeboxes for human tasks. Use templates for task descriptions and prefilled fields to reduce cognitive load.
Prefer event-driven triggers
- Where possible, trigger flows from events (webhooks, message queues) rather than polling. Event-driven designs reduce latency and resource usage.
Use data mapping tests
- Validate data transforms with sample payloads early. Catching mapping issues before connecting production systems prevents broken integrations.
Monitor and iterate
- Instrument key metrics (cycle time, failure rate, rework percentage). Review these regularly and iterate on the process to remove bottlenecks.
Enforce governance with environments
- Use separate dev/staging/prod environments and require approvals for promotions. Keep test data out of production and maintain change logs.
Document intent, not just steps
- Add brief notes or documentation nodes describing why a step exists. This helps future maintainers understand tradeoffs behind decisions.
Train and onboard with real examples
- Create a small set of sample processes for common tasks that new users can clone and adapt. Real examples accelerate adoption.

Example: Simple Approval Flow (conceptual)

Trigger: Form submitted (external web form webhook).
Validate data: Run data mapping and validation node.
Create case: Generate case record in CRM.
Assign approval: Human task to assigned approver with deadline and reminder.
Conditional branch:
- Approved → Update CRM and notify requester.
- Rejected → Notify requester with feedback and close case.
Post-process: Log metrics and close instance.

This pattern demonstrates combining automation (validation, CRM updates) with human tasks (approval), and clear conditional branching to keep state explicit.

Best Practices for Integrations

Start with prebuilt connectors for the most common systems to reduce custom code.
Use the generic REST connector for niche systems and wrap calls in retry logic.
Keep credentials in the platform’s secure vault and rotate keys regularly.
Map minimal necessary fields between systems to reduce coupling and complexity.
Test integrations end-to-end in a staging environment with representative data.

Common Pitfalls and How to Avoid Them

Over-automation: Automating everything can create brittle flows. Keep human checks for high-risk decisions.
Monolithic processes: Very large single diagrams are hard to maintain. Break them into smaller, focused sub-processes.
Ignoring observability: Without metrics, optimization is guesswork. Add monitoring early.
Poor error handling: Failing to model retries/escalations leads to stuck instances. Add explicit error flows.

Measuring Success

Key metrics to track after deploying HubFlow processes:

Cycle time (time from start to completion).
Throughput (completed instances per period).
First-time-right rate (percentage completed without rework).
SLA compliance (percentage meeting deadlines).
Mean time to recover (MTTR) for failed or stuck instances.

Final Thoughts

HubFlow (formerly WDFlow) is most valuable when teams treat it as both a design and execution environment: use its visual tooling to capture intent, its automation to reduce manual toil, and its observability to continuously improve processes. Start small with critical processes, instrument them, and iterate—over time the combination of clearer workflows and automation delivers measurable efficiency gains and fewer operational surprises.