The default in an Automated Workflow for an Analytics Index is to only update new documents.

Relativity project management isn’t just about moving pieces around. It’s about designing workflows that hum along, saving time, and letting analytics tell you what matters. One small but mighty setting comes up often when you’re setting up an Automated Workflow for Running an Analytics Index: what should be included by default? The answer, clean and practical, is: only update new documents.

Here’s the thing most teams discover quickly—this single choice shapes speed, resource use, and how fresh your insights feel in day-to-day work. Let me walk you through why this default matters and how it wires into the bigger picture of efficient document analytics.

• The default that quietly makes a difference

When you configure an Automated Workflow for an Analytics Index, you’re laying the groundwork for ongoing insight. By selecting “Only update new documents,” you’re telling the system: focus on what’s changed since the last run, not every document in the repository. It sounds obvious, but in practice it’s a big lever. Your workflow becomes a live pulse rather than a full house-clean every time.

Think of it like updating a playlist. If you re-scan your entire music library every hour, you waste bandwidth and time that could be spent adding fresh tracks. If you instead refresh only the new items, you keep the playlist current with minimal churn. The same logic applies here: you get timely analytics without reprocessing what’s already indexed.

• Why not include all documents by default?

It’s tempting to imagine a no-regrets approach: “Let’s treat everything as if it were new.” But the reality is different. Including all documents on every run means longer processing times, more CPU cycles, and heavier I/O. In environments with terabytes of data or rapidly evolving datasets, that overhead becomes a bottleneck. The goal of an analytics index is to surface meaning—patterns, trends, and anomalies—fast. Rebuilding the entire index every time can slow that purpose down and stretch resources thin.

Plus, not every document changes often. Some may sit idle for months, with only a handful of updates. In that context, chasing every item again is like sweeping the floor twice when there’s nothing new to pick up. The default helps you stay lean while staying current.

• When might you want to adjust this default?

There are scenarios where a broader sweep makes sense. If you’re performing a comprehensive audit of a repository where every document could have changed or if you’re troubleshooting a data integrity issue, you might temporarily broaden the scope. Or, during a new data migration or system upgrade, you could opt for a more inclusive run to accelerate reconciliation. The key is to balance the need for completeness with the cost of reprocessing.

Even then, it’s usually about short, purposeful adjustments rather than a long-term shift away from the default. After the moment passes, you return to updating only the new stuff and let the analytics engine resume its streamlined cadence.

• How this setting translates into real-world team impact

Let’s anchor this with a few everyday truths from teams that rely on Relativity for their analytics workflows.

1. Faster feedback loops: When you only update new documents, analytics results reflect changes quickly. You don’t wait for a full rebuild to see that a new set of memos contains a recurring keyword or a new pattern in communications. That speed changes how you triage, investigate, and decide.

2. Resource discipline: Compute power, storage I/O, and memory aren’t endless. By narrowing focus to new material, you conserve these precious resources for where they matter most—discoveries and decisions, not redundancy.

3. Better scalability: As your data grows, the cost of full reindexing scales up. The default helps your analytics program keep pace with growth without demanding exponential infrastructure investments.

4. Cleaner change tracking: You get a clearer signal about what actually moved or appeared since the last run. That makes QA easier and reduces the cognitive load when reviewing analytics outputs.

• A practical glimpse into the setup mindset

If you’re configuring an Automated Workflow in Relativity, keep the conversation around the default simple and purposeful. Start with a clear objective: you want timely, reliable analytics on new or updated material. Then align your settings to that aim.

A few connective steps often look like this:

• Define the scope: Which data sources feed into the Analytics Index? Where do new documents land, and how are updates flagged?

• Set the update rule: Choose “Only update new documents.” This keeps the engine focused on fresh input.

• Schedule thoughtfully: Pick run intervals that match data velocity. If new material arrives daily, a daily check-in might be ideal; if updates are rare, you might opt for a longer cadence.

• Monitor and tune: Track processing times, hit rates, and any anomalies. If you notice stale results, you can reassess the cadence or the filters around what counts as “new.”

• QA feeds back: Tie in a lightweight QA check that flags unexpected gaps. Even with a lean default, you want a safety net for surprises.

• Digressions worth a quick pause (then back to the point)

While we’re on the topic of efficiency, ever notice how small adjustments in a workflow can ripple outward in surprising ways? A quiet tweak—like how you filter documents for a certain workflow—can change what analysts see in dashboards, which in turn affects investigative priorities. That’s why the default isn’t just about the mechanics; it’s about how teams experience data in real time. It’s almost procedural poetry: fewer reprocesses, more insight, less wait.

And if you’re curious about the tech behind the scenes, a lot of it comes down to how incremental indexing works. The system tracks deltas—the new items and the modified ones since the last index. By focusing on those deltas, you get a portrait of change without painting the whole canvas anew each time. Cleaner, faster, and more human-friendly because you’re not staring at a wall of data that’s somehow both old and new at once.

• The bigger picture: accuracy, speed, and trust

An analytics index is more than a fancy search tool. It’s a signal system for teams that need to move quickly without sacrificing accuracy. The “Only update new documents” default helps maintain that equilibrium: you stay current, you stay efficient, and you keep your analytics trustworthy.

Trust matters here. If your updates are sporadic or inconsistent, results may become hard to rely on. Consistency is the quiet backbone of confidence. The default setting gives you a predictable rhythm—new material comes in, the index catches up, insights appear, answers emerge. It’s not the flashiest feature, but it’s exactly the kind of steady hand a project team benefits from.

• What this means for Relativity-driven projects

For teams juggling multiple matters, large document sets, and ongoing reviews, this default acts like a disciplined routine. It reduces the noise of constant reprocessing and makes room for the signal—the trends, entities, and patterns that matter for decision makers.

If your workflow includes dashboards, alerts, or automated reporting, the benefits compound. Fresh data flows into dashboards faster, alerts trigger sooner, and stakeholders feel more in sync with what’s happening in the repository. That alignment—without frantic back-and-forth—creates real breathing room for teams to focus on outcome, not process.

• Quick takeaways you can carry forward

• The default for including documents in an Analytics Index workflow is to Only update new documents.

• This choice emphasizes change over repetition, delivering faster analytics and saving resources.

• It’s especially valuable when datasets are large or dynamic, where full reprocessing would be wasteful.

• You can adjust the setting temporarily for special audits or migrations, but the long-term default tends to deliver a cleaner, faster rhythm.

• Pair this with thoughtful scheduling, ongoing QA, and clear data provenance to maximize reliability and impact.

• A final thought

The world of Relativity project management is full of small decisions that add up to big outcomes. The default setting on an automated analytics workflow is one of those deliberate choices that quietly powers clarity. By focusing on new documents, you keep the system lean, the insights sharp, and your team moving with purpose.

If you’re exploring this space, you’ll likely bump into a few related ideas—like how metadata quality affects search results, how to balance speed with accuracy, and how dashboards narrate the story your data is telling. All of those threads weave into the same fabric: a workflow that respects the data, the needs of the team, and the realities of everyday work.

So next time you’re setting up an Analytics Index workflow, remember the simplest rule that makes a tangible difference: update the new, and let the rest follow. It’s not flashy, but it’s effective—and in the world of project management and data analytics, that’s often the kind of efficiency you can feel in the room.