Hi Appian Team and Community,
We’re designing a generic, audit-compliant task module to support multiple business processes—KYC, retail and corporate loan origination, ESG, and more. Before finalizing our architecture, I’m weighing two approaches for task management:
Uses process reports and task assignment rules
Tasks are tied to process instances
UI and SLA logic driven by Appian’s native task engine
We build our own TASK_GROUP and TASK tables
TASK_GROUP
TASK
Tasks are instantiated based on business rules and metadata
UI, counters, and SLA logic are fully controlled via record types and expressions
If we rely on Appian’s built-in human tasks, what happens if the process instance is deleted or archived? – Can we still access task metadata (status, assignee, timestamps) via process reports or APIs?
What are the trade-offs between using Appian’s native task engine vs a custom task registry? – Especially in terms of auditability, lifecycle control, and cross-process reuse
Is it common practice in enterprise-grade implementations to build a custom task pool for traceability and reporting? – Or do most teams rely on Appian’s built-in task management?
For context: our vendor recommended the database-driven approach, citing limitations in Appian’s native task handling—particularly around long-term traceability, cross-process reuse, and lifecycle control once processes are deleted. That inspired us to explore a fully generic task registry that can support dynamic instantiation and stage-based progression across domains.
We’re aiming for a scalable, future-proof design that supports dynamic task instantiation based on business rules, stage-based progression, and full audit history. I’d love to hear how others have approached this, and what Appian recommends for long-term maintainability.
Thanks in advance!
Discussion posts and replies are publicly visible
If we rely on Appian’s built-in human tasks... You will need to store everything about the task metadata yourself.
What are the trade-offs...-
- It is more time to setup tasks for the very first database-driven task list you need on a project or environment. But, ultimately these are small investments of time. Database tables / records with the right task structure are easy to create. Common queries for tasks are also super easy to create. Having foreign keys to the task table is also far easier to manage than an Appian task id that is invalid after a process is deleted. So the tradeoff of time investment is negligible, IMO.
- Part of task assignment is assignment to groups. Sometimes a 'group' is best associated to a region, state, country, claim type, or some other categorization of the data model - i.e. they're not formal organizational groups or roles. It's not a great Appian practice to create an Appian group for every combination of category in the data which might determine task assignment. This complexity is far easier to manage from the data fabric using a combination of record-level security, query filters, and role-based Appian groups.
- Sometimes SLA's are data-driven (e.g. one state regulation might say 3 days whereas another says 7 days). If SLA data is embedded directly into the task data model, reporting on historical data is just a database query away rather than needing to explicitly store the SLA and its metadata after the fact during each process instance. In my experience it's also a roll of the dice for whether the business simply wants a report on what active tasks are delayed or if they want an active escalation / action item. In other words, there's no inherent advantage for one task management approach or the other, IMO. Complex SLA's are tough to deal with no matter how you spin it.
- It is easier to setup automated testing for data-coupled task workflows using expression rules when the tasks themselves can be injected into a database. For large complicated projects, automated testing is a key success factor to constant innovation for the business.
- If tasks are woven into the data fabric, then they can leverage the benefits of the data fabric more directly. -- The basic case use case is leveraging the User record for first & last name of an assignee, even if assignee's Appian account is deactivated due to company offboarding.
-- Another basic use case - leveraging custom record fields to add an easily-filterable column for a task
-- Yet another basic use case that's a huge UX win - given a record, it's easy to see all tasks associated to the record, what the task status/SLA is, and who the task is waiting on. The business gets this one almost "for free" since the only real development involved is determining where to add a record grid.
-- A more advanced use case that's worth experimenting with are the validations associated to record fields in 25.2 (https://docs.appian.com/suite/help/25.2/configure-record-data-source.html#add-reusable-validations )
-- An increasingly useful use case is leveraging AI using crafty prompts and appropriate queries to guide a user through the workflow independently of the current 'task'. This is easier to do if task management is in the data fabric already.
Is it common practice... The last time I made a purely process-model design for Appian tasks was 2018. Here's why:- At first it was because the processes I encountered had cycles lasting multiple months, so it made more sense to put task management in the database. Yet even for the 'faster' process cycles I've encountered since 2022, the data fabric has offered enough of a benefit that now it isn't extra time (over the early sprints) for my project teams to set up task management via the database.
- If you ever encounter modern UX designers, they will give you plenty of reasons why the concept of a task is irrelevant in some types of workflows. Instead, users need to know what information is needed about a "record" in order for someone to make a decision or submit something by a deadline. For example, turbo tax doesn't setup tasks for you to complete as part of your tax workflow. You simply complete the forms on your own time. I like to think of this as a "blob workflow". No one is telling a person what to do, but rather, they need to evaluate the information they see and determine what's next. For these types of workflows, automations are driven when the data changes, rather than when a user completes a task. Similarly, workflows around fraud detection, certain types of insurance claims processing, or workflows with many 'swivel chair' integrations can all have a UX centered around being "taskless", but also leverage a formal task when needed.
- The business situations I've encountered since 2018 require complexity around task management that gets extremely tedious to maintain in Appian's process modeler system. Hunting for all of the little checkboxes, setting up all the nuances needed for nightly jobs, making sure process variables don't use too much memory because they're long-lived, and getting process report data - it's all extremely tedious in a process modeler / process report IMO
- At larger companies it's somewhat common for organizational task reporting to be driven via non-Appian tools, since those tasks might be tied to data that Appian does not have access to at an organization. This means that I've needed a way to allow other applications to access task metadata - which is far simpler to do if the task metadata is already in a database.