The Gig is Up for Confusing Ediscovery Pricing

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Most legal professionals would liken comparing ediscovery price proposals to getting a root canal – only worse. Standardizing and deciphering the complex and opaque universe of ediscovery pricing is no easy task. It takes far too much effort and leaves buyers wondering if their estimates and projected total cost have any grounding in reality. And, let’s be honest: Sometimes there is some fairly sneaky stuff hidden in a proposal. 

Let’s debunk the top 15 pricing misconceptions that drive ediscovery buyers nuts.

1. When a GB isn’t just a GB 

Not all gigabytes (GBs) are created equal when it comes to expanded vs compressed data. There is nothing quite as stomach-churning as getting your first month’s ediscovery bill for processing 1 TB of data only to discover that your data volume and attendant costs are nearly double what was presented in the project estimate. Always double-check data expansion assumptions in each proposal, and normalize them across all estimates based on your experience with the vendor’s promises vs the vendor’s reality. Or better yet, work with a company that charges on compressed GB volume (hint, hint).

2. Not-so-“all-in” pricing

Many providers entice new business with an “all-in” model that purports to provide transparent, predictable pricing — that is, until you read the fine print that makes it much less inclusive. In one truly jaw-dropping instance, a vendor proposal included a flat per-doc rate for “everything” from processing through production. But on closer inspection, they were also charging monthly hosting for reviewed and unreviewed documents, analytic fees, and a fee per tag of $0.10/tag/doc. When the ridiculous proposal was calculated using all the sneaky line items, it came in nearly 70% higher than the next closest proposal — and the vendor was not only double-charging, they were triple-charging! 

3. Assumptions based on an alternate dimension

One part of a proposal that often leads to frustration is vendor-provided matter assumptions. In an effort to inch out the competition, providers will lose all grounding in reality by promising an expansion rate under 10% or claiming cull rates over 95%. Some will go as far as claiming deduplication rates of 75%. When normalized to appropriate standard parameters, the too-good-to-be-true estimates often become too bad to buy. Keep your own counsel and use metrics based on your experience.

4. Review rates for either the Flintstones or the Jetsons

Some firms offer unbelievable reviewer hourly rates — as much as 10-15% below market. This seems great until you realize they are committing to 35-40 documents per hour and/or capping reviewers from working overtime. In the event of a time-constrained review, this poses substantial problems and can lead to blown budgets. On the other hand, firms committing to leveraging tech and super reviewers to get rates double the industry standard should also be reviewed with a degree of skepticism. If workflow, tech, and reviewers are able to yield substantially better results (88/docs/hr) then the provider should have no issue putting their money where their mouth is and guaranteeing it!

5. QC overload 

Some proposals provide an estimate with line items for reviewer bill rate and QC rate without a total project estimate. Often, the QC rate assumption is far out of sync with actual need. On a matter that involves reviewing a million documents the difference between a 15% and 25% QC rate could amount to over $80,000. Find a level that you are comfortable with as a starting point and determine with your provider if there is a need to exceed that amount.

6. Mandating too much PM and MR time

In proposals without a total projected matter estimate, the line items and assumptions around project management for electronically stored information (ESI) and review also pose some costly pitfalls. Whether it is a monthly minimum or assumptions in the stratosphere for PM usage, the impact on total project cost is substantial. Either procure a prepaid volume of hours for the lifecycle of the matter or have a cap — which the provider cannot surpass without engaging with you.

7. Holding data hostage

One major source of friction in the market is needing to migrate a case (especially when due to vendor error) only to find that there was a line item in the statement of work stipulating steep charges to export or archive a database. It adds insult to injury, especially when tensions are high enough to necessitate switching providers midstream. Similarly, some providers charge a headache-inducing fee to decommission a matter at the end of a case.

8. Charging for things that should be self-service

Many providers charge clients for things that should be simple enough to handle themselves. It becomes costly and frustrating when a provider wants to charge $100 for each tag that is added or $150 for each password they reset. This often adds unnecessary steps and lag time to what is already a tedious process.

9. Paying for cutting-edge tech but getting legacy

There are few things quite as annoying as when a provider claims that their “cutting-edge” solution can parse data and uncover evidence in a fraction of the time and cost — if you pay a premium. Yet, when you log into their system, it is the same legacy platform everyone is using (with the same dreaded spinning wheel of death). There may or may not be middleware to address system gaps, but in general it is just another case of beige vs. taupe — but the client is footing a larger bill.

10. Paying an arm and a leg for “advanced analytics” 

At some point a few years ago, some providers began charging exorbitant rates ($150/GB) for analytic tools they used to offer for free. Basic functions like email threading were lumped in with advanced analytics, and if you wanted this workflow efficiency the only option was to pay — a lot. This money grab drove down adoption of more efficient workflows and defensible processes and increased the volume of data that had to be reviewed. This led to an entire cottage industry of lower-cost analytic middleware. Instead, work with tools that incorporate analytic costs into a single flat predictable fee.

11. Per-doc review pricing that (surprise) escalates based on the number of tags

One way that providers maximize profitability on all-in price models is by offering an attractive rate for a matter stripped down to bare bones. In the highly likely event that your matter requires more tagging than simply responsiveness and privilege, many providers upcharge on a per-doc basis based on the number of tags. Even a moderately simple matter may incur a 20-30% upcharge per document based on necessary additions to the coding tree. This is rarely (if ever) clearly disclosed and often comes as a shock to a client who based their budget on the bare minimum per doc rate.

12. Processing double dip

Another classic double dip is charging on both man hours and data volume for processing. A fair model ought to incorporate man hours for processing within the per GB or all-in pricing. Double charging like this is not industry standard barring an extremely bespoke workflow or very atypical data types and even then it is often incorporated into the processing cost. Another annoyance for legal professionals is being charged for waiting time and/or machine time in addition to unitized costs. 

13. Charging for your incompetence 

There are few things as annoying as an inefficient PM or data ops team that takes longer than expected for even simple tasks — and has the gall to charge you more for their ineptitude. Whether it is a bill for six hours of time to run a simple file listing report or claiming they can handle a certain atypical data type, failing, and then trying to bill nearly 100 PM hours, the result is infuriating.

14. Undisclosed different bill rates depending on the kind of review

Some review teams are composed of people with differing linguistic and technical expertise as well as team leads and project managers who may review in tandem with their management obligations. It is always irritating to receive a bill substantially higher than anticipated because reviewers of differing rates were used in an inefficient manner or for first level review, when their rates may be 2-3 times higher than a standard first level reviewer. Always clearly stipulate the roles and responsibilities of each category of reviewer at the front end.

15. Winning a managed review with AI, but then never using it

Some managed review providers use assumptions and estimates based on heavily leveraging advanced analytics — but after they win the matter, they proceed with business as usual liner reviews. The true shock is seeing the costs associated with leveraging the analytics in addition to the bloated managed review costs. Ensure that managed review partners clearly lay out their proposed workflow and that they provide metrics tracking to their estimated time and cost to completion throughout the review to prevent this unpleasant surprise.


At the end of the day, some providers will never provide truly transparent pricing. Thankfully, there are some steps you can take in reviewing proposals and normalizing assumptions. Developing long-term partnerships with providers who understand this is a marathon not a sprint fosters greater transparency and understanding. Do not be afraid to push back on your provider and ask for a structure that works with your cost recovery models and mirrors the assumptions you see in your ecosystem. When all else fails, bring in your ediscovery wonk (who likely has reviewed hundreds of these proposals) to decipher any confusing language. Or, choose a vendor with clear, transparent pricing that makes sense.

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