This article was posted as original content on the ACEDS Blog and written by Gavin W. Manes.
What are your fear factors when it comes to eDiscovery software? Is it predictability of costs? Pricing in general? How to reduce your monthly gigabytes? These are issues that come up regularly in the eDiscovery sphere – whether social media, whitepapers, articles, or water cooler conversations.
Most of the industry uses one of two models for pricing, either user-based or per gigabyte. Below, we’ll dive into understanding fee structures and the benefits and drawbacks of each.
The most common method of billing in the eDiscovery world today is to charge per gigabyte of stored data. With the per-gigabyte pricing used by most vendors and software providers, monthly fees tend to vary widely. It is a good idea to get some sense of what a gigabyte means. Is it only the size of the natives? Does OCR text increase the size? How about productions? Does your billable gigabyte total go up every time you make a production? Also, when data is processed to be input into a database, it may expand based on what’s in the data set (i.e., zip files, other file containers). It’s difficult to get a good grasp on what the data will expand into once it is put into the database and worked with there. Similarly, productions can often exceed the actual size of the documents if images or OCR are needed.
Because the amount billed is based on a moving target, predictability can be compromised. And most vendors are not geared to helping firms reduce the amount of data being billed for, so the model can be one where costs are ever-growing.
Understanding Gigabyte Fee Structures
With gigabyte fees, it’s important for the system users to understand which portions of data contribute to the billable total for the month. The factors that can influence the size of the data could include data expansion, productions, image creation, and more. Another possible issue could arise if users need to establish a separate database using the same data.
There is some thought that user fees aren’t very predictable. Makes sense – the number of users accessing the tool could vary over time, particularly if it’s a large case. New law firm hires, turnover, additional attorneys added, or experts utilized could all change the access number which would mean a different monthly cost.
Bids for user-based systems can often have larger numbers, but it’s important to look at the entire quote. Other items may be included at no charge, or there may be additional fees.
But predictability is a multi-sided issue. You can be guaranteed a set fee for users by just picking the month you had the most users, which isn’t really fair but it is certain. The other side of predictability is flexibility. Within the user fee model, the most successful approach might be to pick a baseline of the average number of users you expect to use, and pay for extra users only when you need them.
Understanding User Fee Structures
This is where it’s important to know whether you’ll be charged for each user you add regardless of whether they log in. Because if you are, then you might be playing the cancel and then add them back in game. But if you are only charged for those that log in, then the total number of users you have at any given time isn’t as relevant. Also, a good thing to understand is whether a user can access multiple cases or if you’re paying for each user on a particular case.
For instance, if email@example.com logs into the Personal Injury case and the Intellectual Property Theft database, are you being charged for one or two users? If one, that means the core group of people from your firm accessing the eDiscovery databases can do so without fear of additional costs. With user fees, you may be able add or eliminate where you need – this is a good question for your service provider.
Both pricing models have their pros and cons, and ultimately the choice will depend on the specific needs and budget of the law firm. Some firms may prefer the predictability of a per-user pricing model, while others may prioritize the flexibility and scalability of a per-GB pricing model.
What do you think? Let us know here.