Understanding why the buffer for reviewers isn’t tied to the number of active reviewers in Relativity projects.

Outline / skeleton

• Opening hello: a quick reality check about reviewer buffers in Relativity workflows

• What really shapes the buffer

• Document complexity and variety

• Reviewer skills, experience, and availability

• Project needs, deadlines, and risk controls

• How work is organized: queues, batches, and quality checks

• A concrete picture: a couple of scenario snapshots

• High-complexity project vs simpler workload

• What changes when reviewers are partially out or assignments shift

• Practical takeaways for teams

• How to think about buffer size without chasing a fixed formula

• Ways to adjust in real time and keep bottlenecks from forming

• Simple tools and habits that help balance the load

• Closing thought: the buffer as a living part of the process, not a fixed number

Relativity buffers: not a straight math equation

Let me explain something that often surprises folks new to this space: the buffer of documents you hand to reviewers isn’t simply a function of how many reviewers are active. It’s tempting to think, “If we have N reviewers, then give each N documents,” but that misses the point entirely. The real engine here is rhythm. The buffer moves as the work moves—depending on what needs review, who is available, and how complex the material is. It’s a dynamic dance, not a rigid rule.

What actually shapes the buffer

• Complexity and type of documents

Some files sing, others grunt. Some come with many redactions, others with tricky privilege questions, or heavy metadata. The more complexity a document carries, the more time it requires to review. A stack of straightforward contracts can go out fast; a batch with mixed document types may need more careful screening. So, the buffer isn’t a flat count; it’s a mix that reflects how demanding each item is.

• Reviewers’ skills, disposition, and availability

Two reviewers aren’t identical. One may excel at near-duplicate detection; another shines with privilege reviews; yet another might be juggling other work or taking a short break. The goal is to match workload to capability, and to keep reviewers from feeling overwhelmed. When someone is tied up with research or a difficult issue, the system should adjust, not pretend nothing changed.

• Project needs and timing

Some projects have tight deadlines; others stretch out over weeks. A buffer in a fast-moving project often needs to be smaller but more predictable, with quick turnaround. In slower contexts, you can afford a larger buffer, but you still want balance so no one sits idle or gets buried. The project’s risk tolerance—what happens if a review slips—also nudges how large or small the buffer should be.

• How the work is organized

Think of queues, batches, and checks as the gears of a clock. Items might be placed in a primary review queue, then moved to a quality-control pass, and finally signed off. If the queue grows too long, you might re-prioritize items or reassign batches. If checks are too frequent, you slow the pendulum; if too lax, you risk overlooking issues. This structure matters as much as raw numbers.

• Availability and cadence

Sometimes a reviewer is traveling, or a team member is focusing on a high-priority task elsewhere. In those moments, the system should adapt. The buffer grows or contracts in sync with who’s present and who can jump in. It’s about keeping the flow steady, not about forcing a fixed load onto everyone.

A simple picture through two scenarios

• Scenario A: a high-complexity batch

Imagine a project where a few documents require intricate privilege reviews, multiple data sources, and cross-references to prior decisions. The team might deliberately keep the buffer smaller for each reviewer here. The idea is to preserve accuracy and avoid churn—where reviewers re-check things because context was missing or decisions were rushed. The result? A leaner buffer that moves more slowly but with higher confidence.

• Scenario B: a straightforward batch with steady pace

Now picture a lighter load—cleanly labeled documents, clear privilege decisions, minimal redactions. Here, the buffer can be larger, because reviewers can move quickly through the stack. The pace stays steady, and the work can flow with fewer hold-ups. The key is to feel the difference between a routine day and a demanding one and let the buffer adapt.

Why a fixed-per-reviewer rule doesn’t hold up

If you try to anchor the buffer to “X documents per reviewer,” you’ll end up either starving some reviewers or overloading others. Real life isn’t a single formula. People work at different speeds, and the documents vary in complexity. The outcome is a buffer that shifts with the wind—sometimes a few dozen items, sometimes far fewer, sometimes more—always tuned to avoid bottlenecks.

Practical takeaways you can use (without turning this into a rigid checklist)

• Start with a sense of capacity, not a hard count

Rather than multiplying active reviewers by a fixed number of documents, look at historical pace, average time per document for different types, and current complexity. Use that to set a flexible target range for the buffer. If the range starts to drift, you know something in the mix has changed.

• Prioritize by impact, not just order

A few items may unlock faster progress later—documents with broad dependencies, or those that decide a large portion of the review path. Put those near the front if possible. It’s not about piling up “easy wins”; it’s about keeping the critical path moving.

• Build in a cushion for variability

Things happen: a file is ambiguous, a reviewer needs clarifications, a batch is paused for a quick quality check. A small cushion protects the overall rhythm. It’s the difference between a stutter and a smooth glide.

• Use lightweight signals to guide adjustments

A simple dashboard: what’s in the buffer, what’s in review, what’s blocked. If the buffer swells without progress, you know you need to reassign, re-prioritize, or recheck the setup. If the buffer sits too lean, add a touch more in the queue so reviewers aren’t idle.

• Keep the workflow transparent

When the team understands how and why matters are reordered, it reduces friction. Communicate the shifts, the reasons behind them, and what’s changing. Clarity breeds calm, and calm keeps the work moving.

• Leverage structure without over-structuring

Relativity workflows thrive on order—batches, tags, roles—that help quick decisions. But avoid locking everything down into rigid rules. Leave room for human judgment, for mistakes, for rethinking a path when new information comes in.

A few practical phrases to keep in mind

• “What’s the complexity here?” helps recalibrate the buffer, fast.

• “Who’s available this week?” keeps staffing real.

• “Does this item change the path ahead?” flags priority tweaks.

• “Is the quality gate clear?” minimizes back-and-forth later.

A small, human note on the process

In any system where people review content, a little friction isn’t a flaw—it's a signal. It tells you where the gaps are, where the training might help, or where a tool tweak could save time. The buffer isn’t just a number; it’s a living gauge of how well the team understands the material, how smoothly the workflow runs, and how well the work is distributed. When you treat it as such, you get a more resilient, less exhausting process for everyone involved.

Bringing it together: a balanced, responsive approach

The buffer of documents for reviewers shouldn’t be read as a simple product of “how many reviewers are active.” It’s a nuanced outcome of document difficulty, reviewer capability, project timing, and workflow design. When teams stay attentive to these levers, they keep the review flow steady, reduce rework, and preserve focus on the work that matters most.

If you’re building or refining a Relativity-based workflow, here are the core ideas to carry forward:

• Acknowledge complexity and tailor the buffer accordingly.

• Align workload with skills and availability, not with a fixed quota.

• Treat the buffer as a flexible instrument that adapts to real-time conditions.

• Communicate openly about changes and keep the process transparent.

• Balance speed with accuracy, recognizing that both matter.

In the end, the aim is a workflow that feels almost inevitable—the kind where work glides from the queue to completion with just the right pace. The buffer serves that rhythm. Not as a rigid rule, but as a living, responsive part of the system. And when it works well, reviewers aren’t rushing, metadata stays clean, and the path through the documents stays clear.

If you’d like, I can tailor these ideas to a specific Relativity setup you’re exploring—talk me through the kinds of documents you handle and the typical review roles you use. We can sketch a more concrete picture of how the buffer might behave in your context, while keeping the principles tight and practical.