Determining the most cost-effective e-discovery vendor for ongoing or impending litigation can make your head spin.

Different pricing models and terminology make accurate price comparisons difficult to achieve. Knowing some basic parameters, such as the timeline and approximate data size, will assist with understanding the options and arriving at the most optimal arrangement. Additionally, knowledge of available pricing models can help make your decision easier.

Understanding Two Basic Pricing Models

A traditional ala carte (also known as “line item”) in/out model involves collecting data and doing early case assessment (ECA) processing on the entirety of the data collected—the “in” part of the in/out title.

That data is then culled by deduplication, or the elimination of duplicate or redundant information, as well as search terms and other methods to a smaller data set. This data set is then further processed for upload (sometimes called promotion) to a platform for review—the “out” of in/out.

After processing, monthly hosting fees are incurred during review on a per gigabyte basis, as well as user license fees. Analytics tools (email threading, near duplicates, concept clustering, etc.) can also be purchased. At production, charges for imaging or branding or native production will also be incurred.

These items are usually available on a menu when negotiating the e-discovery contract, hence the “ala carte” name. The early case assessment tools available vary greatly from vendor to vendor but traditionally have been based on Boolean search terms and search term “hit” reports.

“All-in,” or flat-rate, pricing began simply as a different data ingestion model, where instead of ECA the entirety of the data is processed for promotion to the review platform after basic deduplication and deNISTing (a process that removes non-user created files with no evidentiary value).

Generally, this data ingestion is done at a price point between the per-gigabyte cost of ECA and promotion to review. The advantage is that the entirety of the data can be analyzed with more advanced analytics tools than Boolean search terms, lowering the chances of missing relevant data initially and having to go back and promote more data later. The downside is that more data is processed at a higher cost.

A newer pricing model has emerged alongside the decrease in infrastructure costs surrounding new cloud-based SaaS (software as a service) platforms. Confusingly, it is sometimes also called “all-in” pricing (or bundled or flat-rate pricing). This model involves a per-gigabyte monthly rate including the equivalent of ECA ingestion, processing for review, data hosting and some review licenses, imaging and productions at minimum, and may also include analytics as well.

Which Model Is Optimal?

When comparing pricing based on these different models, it is important to keep in mind the anticipated length of time the matter will be active and the amount of data involved. A traditional ala carte model involves a high up-front cost for the data processing, lower month-to-month costs for hosting promoted data during review, and another high cost at production.

Using a flat-rate model can lessen the start-up costs of the review and smooth the month-to-month costs including eliminating the spike at production, which assists with monthly budgeting and managing risk. However, as a matter goes on, the costs of the all-in bundled pricing may end up costing more than the ala carte pricing long term.

It is important to ask questions about contractual minimum terms and removing non-promoted data from the platform or cold storage hosting rates to determine the long-term competitiveness of an all-in bundled-pricing model, as you will be charged for the all of the data uploaded to the platform, as opposed to just data promoted for review under the ala carte model. The minimum term of contract is also important in case a matter settles before the projected length of time.

Understanding These Options in Practice

As an example, assume a 500GB collection of data for a nine-month review for the following comparison. Using recently collected pricing survey data, assume the rates below apply for ala carte pricing:

  • $30/GB for ECA ingestion
  • $100/GB for promotion processing
  • $14/GB for monthly hosting
  • $25/GB per month for analytics
  • $200/GB for productions
  • 500 GB in X $30 per GB for ECA in = $15,000
  • 100 GB out X $100 per GB for promotion out = $10,000
  • 50 GB X $200 per GB for production = $10,000
  • 100 GB X $14 per GB per month X 9 months = $12,600 or
  • 100 GB X $25 per GB per month X 9 months for hosting with analytics = $22,500

In this example, the ala carte pricing model results in costs of approximately $47,600 to $57,500 over nine months without including monthly user fees, project management time or attorney review time. If this was charged at a steady monthly rate, it would be about $5,290 to $6,390.

To compare these numbers to a flat-rate pricing model, it is necessary to know the minimum length of contract and the options for removing data from the platform to accurately gauge the amount of data being paid for each month. If, for example, you had a minimum contract length of three months and you could not reduce the data size until after three months, then determining your cost would look like the following:

(500 GB X $Y per GB per month X 3 months) + (100 GB X $Y per GB per month X 6 months).

With no minimum contract length and the ability to remove data from the platform, it would be comparable to:

(500 GB X $Y per GB per month X 1 month) + (100 GB X $Y per GB per month X 8 months).

Once you determine the minimum contract term and information about cold storage or removal of data from the charged footprint, you can make an informed decision on whether flat rates will be competitive with the traditional ala carte rates.

Arming yourself with this basic understanding of the available pricing models for e-discovery processing, hosting and production will help you choose the most cost-effective pricing model and vendor for your project.


Author Information

Kelley J. Halliburton is an attorney in the litigation, construction, and government contracts groups at Shapiro, Lifschitz & Schram. She has extensive experience in all aspects of electronic discovery, including managing significant volumes of electronically stored information (ESI) utilizing various electronic review platforms and litigation support systems, and manages the firm’s electronic discovery department.