The initial data feed question you raised is actually a data modeling and engineering problem disguised as a security one. Teams will ingest raw STIX/TAXII feeds with hundreds of attributes per indicator and immediately try to build dashboards and playbooks on top of it. That's like trying to run analytics on a raw JSON event stream; performance degrades immediately and the schema is a moving target.
Instead, treat the initial deployment like building a data mart. Define a transformed, purpose-built layer. For a phishing-focused team, that might mean flattening the feed into a table with only `indicator`, `confidence`, `first_seen`, `malware_family` (if present), and a boolean `is_actionable` based on your own internal threshold. Everything else is noise. You build playbooks against this clean table, not the raw ingestion. This approach forces the "so what" question upfront: if an attribute from the feed doesn't make it into your clean model, it has no business triggering an action.
On permissions, mirroring LDAP groups is critical, but I'd add a data-specific caveat. Create a separate, restricted role for anyone who can modify the data feed configurations or enrichment parameters. A junior analyst accidentally changing a confidence scoring weight or disabling a critical feed can corrupt your entire indicator dataset, and that data quality issue can propagate silently for weeks. Treat data pipeline controls as a higher privilege than operational playbook execution.
data is the product
You've hit on the two main categories, but the root pitfall I see ties them together: deploying the platform as a technology project instead of an operational one.
Teams will get the data feeds and playbooks technically correct, but they'll fail to define the single, measurable outcome the team must improve. If you can't state that outcome in terms of time saved, false positives reduced, or coverage increased for a specific threat, you're just installing software. The platform becomes an expensive reporting tool, not a workflow engine.
Start by locking down the one metric. Something like "reduce time from alert to enrichment from 15 minutes to under 5 for phishing indicators." Then every configuration choice, from feed selection to role permissions, gets tested against whether it serves that goal. This prevents the common fate where the deployment is declared "successful" based on vendor-defined metrics like volume of data ingested, while the actual analysts continue using their old, manual process.
Measure twice, spend once