Object Workflows
Audience: Administrators, Developers, Solution Architects
Purpose: Explains how to convert an Object from a static container into a lifecycle-driven workflow or pipeline.
Overview
Object Workflows add lifecycle behavior to an Object by introducing a structured process. Records move through defined stages that represent process milestones or stage progressions, allowing the platform to track state changes, outcomes, and performance over time.
When enabled, Object Workflows is configured in Step 2 of the Object Configuration process.
General Settings
Object Workflows
Related Objects
Customize Fields
Customize Layout
Permissions
This stage-driven model differs from non-workflow Objects, which maintain Records without interpreting their progression. Workflow-enabled Objects provide operational context, making them ideal for processes that require visibility, forecasting, or structured execution. Enabling workflows also unlocks advanced filtering and reporting capabilities, including metrics such as time in stage, pipeline value over time, and progress toward team goals.
When to Use Object Workflows
Use workflows when Records must follow a repeatable lifecycle.
Best suited for:
Sales pipelines
Customer onboarding
Project delivery
Approval processes
Service workflows
Operational funnels
Avoid enabling workflows for Objects that store reference data or do not require stage progression.
Contains Workflow Toggle
The Contains Workflow toggle activates the ability to create a pipeline for an Object. Once enabled, the object gains stage-based behavior and workflow system fields that support lifecycle tracking that displays in the Stage Settings tab.
Caution: The Contains Workflow setting is immutable after Object creation. If workflow behavior needs to be added or removed, the Object must be recreated.
After a workflow is enabled:
A Stage Settings tab is added to the Object
All Records are required to belong to a stage
Board View Layout becomes available in the Customize Layout tab
Outcome tracking fields can be generated
How Records Move Through a Workflow
Records progress through stages as work advances.
Users can update a Record’s stage by:
Creating an Automation Field Update,
Selecting a new stage from the Stage field, or
Dragging the Record between columns in Board view
This ensures the pipeline reflects real-time operational status.
Stage Settings
The Stage Settings tab is where the workflow structure is configured. Stages represent the sequential steps a Record moves through from creation to completion, arranged in a defined order that reflects the process and supports accurate tracking, reporting, and workflow analytics.
Examples of Stages include:
New → Qualified → Proposal → Closed
Requested → Approved → In Progress → Complete
Each stage is assigned a Stage Status, which determines how the platform interprets the Record’s state.
Statuses include:
Open: Active work
Won: Successfully completed
Lost: Unsuccessfully closed
Disqualified: Removed from the process
Configuring statuses enables more accurate reporting and clearer lifecycle visibility.
Note: At this time, statuses are not editable.
Outcome Reason Fields
When Lost or Disqualified statuses are added, the platform automatically generates reason fields. These fields help organizations analyze pipeline performance and identify patterns behind unsuccessful outcomes.
Include % Chance to Close
The Include % Chance to Close toggle converts a workflow into a probability-driven pipeline.
When enabled:
Each stage can be assigned a probability value
Records inherit the probability of the stage they enter
Values can be manually overridden when necessary
This capability is commonly used for revenue forecasting, weighted reporting, and performance analysis.
Note: If a Record moves from a stage with a 25% probability to one with a 75% probability, the Record’s likelihood to close updates automatically unless manually adjusted.
When to Enable This Setting
Enable probability tracking when forecasting outcomes is important or when pipeline performance influences strategic decisions.
Common examples include:
Sales pipelines: Estimate expected revenue by weighting opportunities based on their likelihood to close.
Partnership or business development funnels: Predict which deals are most likely to finalize.
Recruiting pipelines: Forecast hiring outcomes as candidates move from screening to offer stages.
Fundraising pipelines: Project incoming contributions based on donor commitment levels.
Enable this setting when stages represent increasing commitment or certainty, allowing probability values to reflect realistic progression toward completion.
Leave this setting disabled for workflows where probability does not provide meaningful insight.
Examples include:
Internal task tracking
Approval workflows
Support ticket management
Project step tracking
In these scenarios, Records are expected to complete regardless of stage progression, making likelihood-to-close metrics unnecessary.
Use AI to Update Stage % Toggle
The Use AI to Update Stage % toggle enables Kizen's artificial intelligence to automatically calculate and assign the probability of a Record closing based on historical pipeline performance.
When this setting is enabled, the platform overrides manually configured stage percentages and continuously analyzes how Records move through your workflow. Using this data, Kizen adjusts the likelihood-to-close values to better reflect real-world outcomes.
Administrators can also configure how long the system waits to gather sufficient data before applying AI-driven probability updates, helping ensure predictions are based on a confident data set.
How It Differs From Manual Probability
Manual stage %: Values are static and defined by administrators
AI-driven stage %: Values are dynamically generated using pipeline history and team performance patterns
This allows probability metrics to evolve as your organization’s sales or operational behavior changes.
When to Enable This Setting
Enable AI-driven probability when you want stage likelihoods to automatically reflect actual pipeline performance rather than relying on manually assigned percentages.
Common examples include:
Mature sales pipelines: Improve forecast accuracy by using historical win rates to calculate stage probabilities.
High-volume recruiting funnels: Identify conversion patterns as candidates progress through interview stages.
Established revenue workflows: Generate data-driven projections based on consistent deal progression.
Organizations moving away from manual forecasting: Reduce administrative effort and limit human bias in probability estimates.
Enable this setting when your workflow generates consistent historical data and follows repeatable progression patterns.
Leave this setting disabled for workflows where AI may lack sufficient data or where process behavior changes frequently.
Examples include:
Newly created pipelines with limited historical Records
Experimental or evolving business processes
Low-volume workflows
Short-term initiatives or pilot programs
In these scenarios, manually assigned percentages typically provide more predictable results until enough data exists for AI to model progression accurately.
Board View Layout
Workflow-enabled Objects support a visual board layout organized by stage.
Board view helps teams:
Understand workload distribution
Identify stalled records
Monitor pipeline health
Prioritize work
For teams managing high Record volumes, this visualization improves speed and decision-making. For more information on customizing layouts, see Object Layout Customization.
Analytics
Workflow-enabled objects surface key operational metrics directly within Board View, providing immediate visibility into workflow performance.
Available metrics may include:
Record counts to understand stage volume
Total pipeline value to assess potential outcomes
Time in stage to identify delays or process bottlenecks
Workflow-enabled Objects also support advanced filtering and reporting, enabling teams to evaluate trends such as pipeline value over time and progress toward team goals.
These insights help organizations monitor execution, optimize processes, and make more informed operational decisions.
What’s Next
Now that you understand how workflows structure an Object’s lifecycle, you can learn more about any of the following topics below:
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