The most important eDiscovery data processing metrics include processing cost per usable file, time-to-first-facts, and review reduction rate. The first tracks how much value you get from every dollar spent on processing. The second shows how quickly you uncover useful facts, while the third measures how much unnecessary data you remove before review.

Picture a discovery deadline closing in while your team is buried in unfiltered data. Files keep piling up, costs rise, and no one can see where the slowdown began. With clear metrics guiding you, every step from collection to review becomes faster.

What Is Data Processing in eDiscovery?

Data processing in eDiscovery means turning collected digital files into information you can read and review for a case. The system takes emails, chats, and documents from many sources, opens them, extracts text, and makes them searchable. You end up with clean, usable data that supports better legal data management and faster reviews.

Processing removes duplicates, fixes file errors, and keeps important details like dates and senders intact. The main tasks of data processing include:

• Extracting text and metadata for search
• Converting unreadable files into usable formats
• Tracking each step for accuracy and defensibility

How Often Should You Revisit Your Metrics?

You should review your metrics every quarter so you can see how your process is changing over time. When you track results often, you start to notice where time or money is being lost.

Once you see the pattern, you can fix small problems before they grow. Each review builds a clear picture of your team's eDiscovery efficiency and helps you plan smarter for the next quarter.

Why eDiscovery Data Processing Metrics Matter

When you track the wrong metrics, you end up focusing on numbers that don't change results. Many teams look at how much data they collect instead of how much gets reviewed. If you only measure what's collected, you can't see how much time or money is spent cleaning and processing data that doesn't help your case.

Every gigabyte (GB) you handle costs something, for instance:

• Storage and hosting fees
• Vendor charges for processing or exports
• Review costs for larger data sets

If your process is slow, those costs pile up, and cases take longer to finish. By measuring real results like how long each step takes, you can see exactly where time is wasted and money leaks out, then focus on fixing those first.

The Core eDiscovery Data Processing Metrics

Understanding key metrics helps you see how well your eDiscovery data processing workflow performs from start to finish. The following are the main areas you should track to control cost, speed, and quality:

Processing Cost per Usable File

Processing costs rise when the data you collect is messy or too large. Common examples of files that slow things down include:

• Encrypted files
• Duplicate documents
• Files with missing metadata

A reliable data collection platform helps you avoid this problem by capturing cleaner and more organized data from the start. To find your true processing cost, divide the total spend on processing by the number of usable documents that reach review.

If your cost per usable file keeps dropping, that's a healthy sign. To improve, focus on better process optimization through:

• Better data collection rules
• Standardized file handling
• Cutting unnecessary reprocessing and manual fixes

Time-To-First-Facts

Time-to-first-facts measures how long it takes you to turn raw data into the first useful case insights. It starts when data collection ends and stops when reviewers identify the first facts they can act on. Effective information governance software helps shorten this time by organizing and tagging files right after collection.

You can measure time-to-first-facts by tracking the exact time when:

• Data collection ends
• Data processing finishes
• Reviewers mark the first relevant item

The gap between those steps shows how well your workflow performs.

Your goal is to shorten this time with each project until it becomes consistent. As your data review strategy improves, you'll reach useful facts faster.

Review Reduction Rate

Review reduction rate shows how much collected data you reduce before the review begins. The goal is to shrink the review set, so your legal team spends less time on irrelevant material. Advanced digital legal solutions support this by filtering duplicates and junk files early in the workflow.

You can measure it by comparing the total data collected to the data that reaches review. The difference between the two shows how much processing helped.

Focus on steady progress over time. As your digital communications governance process improves, your review set becomes smaller and cleaner each quarter.

Frequently Asked Questions

What Is the Best eDiscovery Software?

The best eDiscovery platform gives you faster insight and full control over your data. Look for software that:

• Connects directly to data sources for quicker access
• Automates processing and organizes information for review
• Uses AI to uncover facts and patterns faster
• Tracks accuracy and reduces review time
• Scales smoothly as your data grows

What Are the Trends in eDiscovery?

eDiscovery is shifting toward faster automation and smarter data analysis. Teams now use AI to organize large data sets and find key facts sooner in a case. Cloud tools are also expanding, giving you real-time access, stronger security, and smoother collaboration across legal and technical teams.

How Can AI Help to Efficiently Process and Analyze eDiscovery?

AI speeds up eDiscovery by managing large volumes of case data that would take people much longer to process. It helps you:

• Read and categorize large document sets in minutes
• Detect patterns and connect related information
• Rank files by relevance for quicker review

With machine learning, you spend less time tagging and more time focusing on the evidence that shapes your case.

Streamline Your Workflow With eDiscovery Data Processing

Tracking eDiscovery data processing metrics like processing cost, time-to-first-facts, and review reduction rate gives you a clear view of performance. When you measure the right points, you gain the insight needed to refine your process.

At Onna, our platform securely integrates unstructured data from sources like Slack, Google, Microsoft, and Confluence to give your team unified, searchable access. We also provide expert guidance and training to help you scale adoption and get measurable results faster. Contact us to modernize your eDiscovery operations and turn data into clear, defensible results.