eDiscovery Software Pricing for Grownups

eDiscovery pricing has been problematic since, well, the onset of eDiscovery. 

Today's eDiscovery software buyers want clear, predictable and transparent pricing structures. In-house personnel in legal departments at corporations and government agencies need to prepare annual budgets they can adhere to for the next 12 months. Law firms need certainly as well, both to let clients know what to expect and so they can plan their own budgets. Service providers face similar challenges, especially when they enter into managed services agreements.

What consumers get, all too often, is the opposite of what they want. They run up against unpredictable base costs, add-on charges whose totals can be known only after they are incurred, vague numbers, and fees for additional third-party components. Layer these uncertainties on top of the challenges posed by pricing for eDiscovery services and related professional services, and you have the antithesis of clear, predictable, and transparent.

We know that no single price or price structure fits all situations. That is why we bring the same innovative thinking to pricing that we do to software design, implementation, and support.

Predictably Unpredictable Pricing

Unpredictable pricing is commonplace. Organizations often are offered pricing by the gigabyte or terabyte. With a known unit price, it is suggested, they can budget for upcoming eDiscovery software expenses. 

Corporations, law firms, and service providers, however, often face an unknown and frequently unknowable number of units. Rarely can legal teams predict how much data they will need to handle. While in-house personnel might have access to the number of custodians subject to legal hold now, they don't know how many they will put on hold in the coming year. And while they might know how many matters are on their docket today, predicting that number for the rest of the year can be challenging if not impossible. 

How can you predict it?

Typically, there is no ready access to information on how much data has been preserved or collected and little to no chance of reliably projecting how much ESI will need to be gathered in the next 12 months. In the same vein, historical information about data processing and hosting tends not to be available; even reports of past activity can be hard or impossible to obtain. 

With unknown unit numbers, known unit pricing does little support predictable pricing.

Complicated variable add-ons 

Total eDiscovery costs also can be difficult to predict because of additional variable costs. One prominent example of a hard-to-predict variable monthly cost is the user licensing fee. With the number of active cases changing from month to month, with review projects ramping up and scaling down, with lawsuits and investigations heating up and cooling down, the total number of users in a system can vary greatly from one month to another in the course of a year. 

If you were paying a user fee of $100/month and had an average of two users per month, that would be an extra $2,400 for the year. If you had 20 users per month on average, the annual cost would go up to $24,000, and if the user count climbed to 500 per month, the users' fees for the year would be $600,000. 

Similar variable costs can include: 

• prices based on the number of custodians whose data is preserved, collected, or processed
• the number of data collections performed or devices from which data is collected
• the number of processing, analytics, or production nodes used
• the amount of stored information
• the number and size of productions delivered
• any archiving involved

Don't forget 3rd-party integrations or burst pricing

Another type of common variable cost is the price sometimes needed to gain access to additional eDiscovery tool capabilities. Some platforms require third-party software or services to round out their offerings. If the default eDiscovery solution does not have sufficiently robust analytics or AI functionality, it might be necessary to license additional software from another provider. If the platform does not include translation, transcription, or image recognition, getting those functions could require turning elsewhere, perhaps to third-party eDiscovery software or possibly to a service provider that would, of course, charge an additional fee.

Paying extra to gain access to additional capabilities can be an issue even when that functionality is built into a platform. Some electronic discovery software providers, for example, charge extra fees to use their own analytics even though they market those analytics as an integral part of the platform.

Burst fees can be another form of unpredictable pricing. Some platform providers change burst fees if a pre-set data threshold is surpassed during the annual contract period. These might take the form, for example, of monthly per-gigabyte fees assessed for the remainder of the period. Modest burst fees can be managed as part of a routine budgetary process, but substantial ones can wreck a budget.

Opaque or Obscure Software Pricing

Like many others, I have had to take a metaphorical magnifying glass to proposed pricing structures. They can be challenging to parse. They can have numerous line items, where it can be difficult to determine which apply and under what circumstances. They can rely on hard-to-follow if-then-else scenarios. They can be built on detailed pricing structures that don't line up with the processes we intend to use and hence require translation.

These complex pricing structures also can contain 'gotchas' that need to be sussed out. In one proposal I encountered, a mandatory small per-unit fee mentioned only in a footnote - something like one-tenth of a penny - would have added over $1 million a year in costs. Fortunately, we caught that, rejected the proposal, and went with a different vendor.

Similarly, pricing agreements can include constraints that might not be immediately obvious, the so-called fine print - inconspicuous details or conditions that may be far from favorable but are buried deep in the agreement. Examples can include volume limits for on-premises implementations, storage capacity constraints, and prices that vary depending on specific workflows adopted.

Prioritizing Clients Before Profits

At Reveal, we take a different and, we think, better approach. Our philosophy is to invest in our clients, and one way we do that is through the eDiscovery software pricing models we offer.

We offer:

1. All-inclusive pricing. We aim for a single line item, not a laundry list of fees. And that item should be comprehensive; after all, no one wants to plunk down the cash for a car only to discover tires are extra.
2. Flexible models. We offer flexible models, such as one where data volumes ramp up over time. That way, customers don't pay for excess capacity upfront.
3. No user fees. We don't change user fees, additional fees for using analytics, artificial intelligence, or machine learning, or similar unpredictable variable costs.
4. Global infrastructure. If you choose our SaaS offering, our global infrastructure is included at no extra cost.
5. Hybrid models. You can choose our SaaS or deploy our platform in your cloud or on-premise environment, always with the same user experience. You can opt for a hybrid approach so that you can have on-premise and cloud-based options under a single subscription and with the same user experience. You also can deploy our platform on mobile appliance, should you be in a situation where sensitive data sets must not leave a certain jurisdiction, such as cross-border discovery, where sensitive data must not leave a physical location, such as source code review, or where the desired cloud or data center infrastructure are not available. (For more, see Which eDiscovery Platform Deployment Options Are Right for You? and eDiscovery In The Cloud or On-Premises? You Have Options with Reveal.)
6. AI Model Library. We include access to our AI Model Library, a collection of pre-built models you can use straight out of the box, extend or adapt to suit your specific needs, or stack and pack to achieve a larger objective. (For more, see What Is An AI Model? and Like Netflix for Legal AI Models: Reveal’s AI Model Marketplace Goes Deep.)
7. Translation, transcription, and image recognition. We have built AI-driven translation, transcription, and image recognition and tagging technology into our platform. You don't see a separate install, a third-party tool, or someone else's services to translate the contents of a document, transcribe audio files, or detect and label images. (For more, see Are You Spending Too Much For Foreign Language Document Review?, How Many Hurdles are in Your Foreign Language Document Review Process?, Image Recognition and Classification During Legal Review.)

Ready for Grownup Pricing?

eDiscovery software pricing does not need to be yet another problem consuming much-needed time and attention to resolve.

If your organization is interested in learning more about how Reveal can serve you better with our innovative approaches to eDiscovery software pricing as well as more about our AI-powered end-to-end document review platform, contact us to learn more.