e-discovery 2.0

Judge Grimm’s Victor Stanley case was lauded by many as one of the most significant electronic discovery cases of 2008, mainly for its bold proclamation that e-discovery search is a much more complex and technical discipline than has been typically understood by litigators.

“[F]or lawyers and judges to dare opine that a certain search term or terms would be more likely to produce information than the terms that were used is truly to go where angels fear to tread.”

Despite, legions of articles and blogs on the topic, at least certain portions of the bench haven’t taken heed.  In the case In re: Zurn Pex Plumbing Products Liability Litigation, 2009 U.S. Dist. LEXIS 47636 (June, 5, 2009) (hereinafter “Zurn“), U.S. District Judge Ann Montgomery receives points for understanding some basic e-discovery tenants around recall and precision, but then mysteriously goes where “angels fear to tread” by suggesting her own search terms.

Examining the case facts in more detail,…  Zurn is a class action products liability case where discovery was bifurcated (as is often the case – see Spieker v. Quest Cherokee) to first cover the class “certification” component.  Initially, the Magistrate partially closed the door on broader ESI discovery, stating that “while ESI may prove to be relevant to the first stage of discovery, we cannot meaningfully make that prediction now, and require the parties to engage in what could be vastly more expensive, and yet utterly futile, discovery.”  However, the Magistrate didn’t shut the door entirely, suggesting that “should the parties uncover voids in the information disclosed in hard copy form, they are . . . at liberty to press for further discovery including electronically stored information.”

Despite complying with Sedona’s Cooperation Proclamation (”The parties have worked amicably throughout the discovery process”) opposing counsel still got to loggerheads when plaintiff found “voids” in the initial paper productions via third party discovery.  The plaintiff brought a motion to compel ESI discovery and the defendant objected, stated two primary arguments: (1) the Magistrate earlier ruled out ESI discovery and (2) if they had to perform ESI discovery it would be unduly burdensome/expensive.

Judge Montgomery summary rejected the first argument, but was concerned about the burden surrounding the proposed ESI discovery.  Here, the calculations get a bit confusing, but plaintiff’s request would have resulted in 361 gigabytes of ESI from employee email sources, as well as shared “J” and “K” drives.  The defendant multiplied the gigabyte number by 75,000 pages per gigabyte, which would have required “approximately seventeen weeks and cost $ 1,150,000, exclusive of vendor collection and processing costs, to review and process the data.”  Assuming a rather modest $1,000 per gigabyte for processing and hosting costs, defendants could’ve added another $400,000 for the project.

Ultimately, the court was not persuaded by the supporting affidavits, nor the attorney’s representations about the resulting burden:

“It is unclear whether Zurn’s cost and time numbers are based on a review of 27 million pages of documents, the 3.6 million pages of documents limited to the J Drive and custodians’ emails, or a smaller sample of document pages likely to be flagged as a result of a search for certain relevant terms pro-posed by Plaintiffs. The affidavit of Ms. Freestone, an attorney and not an expert on document search and retrieval, is not compelling evidence that the search will be as burdensome as Zurn avers.”

The 361 gigabytes apparently resulted from “hits” corresponding to plaintiff’s 26 search terms.  The court correctly identified that those terms had precision issues (”many of Plaintiffs’ proposed search terms will likely produce a large number of ‘hits’ that have limited relevance in the case.”)

Unfortunately, in an effort to increase the search precision, the Judge did not take heed of Judge Grimm’s warning and surprisingly took matters into her own hands: “the Court will limit the search to the following fourteen terms based on the likelihood that they will  produce relevant documents without including a vast number of documents that are likely irrelevant to the litigation.”  Here is the Judge’s list of keywords:

(1) AADFW,
(2) Corrosion,
(3) Corrosive,
(4) Corrosive Water,
(5) Crack,
(6) De-zinc,
(7) Dezincification,
(8) DZR,
(9) Fail,
(10) IMR,
(11) Leak,
(12) MES,
(13) SCC,
(14) Stress corrosion cracking

Without looking at the underlying data, it’s clear from the outset that Judge Montgomery didn’t craft a good search strategy (as Judge Grimm might have predicted).  For example, terms 2, 3, 4 and 14 could’ve been captured by a single stemmed search using the term “corros*.” Without such a stemmed search approach, the terms would probably have been run singly in the proposed protocol, meaning that each one would’ve had tremendous duplication, thereby resulting in wasted attorney review time and processing costs.

Judge Montgomery did recognize the potential error of her ways and gave the parties an out:

“The parties may decide on a different set of fourteen terms if they choose to do so. Additionally, if the search, as ordered by the Court, proves to be overly burdensome or costly, Zurn may renew its objection by presenting the Court with specific information including evidence from computer experts on applying the search terms, the number of documents identified, and the cost and time burdens of vetting documents.”

This “specific evidence” language seems to track notions from Sedona’s search best practices protocol, which prescribes sampling and iterative search term refinement.  What is surprising is that knowing this she would nevertheless blindly proffer the 14 term search strategy.  Instead, she should’ve quoted Victor Stanley and required the parties to come up with a data driven approach that met requisite precision and recall metrics.

Picking five out of the sea of electronic discovery cases isn’t as easy as it sounds.  Sure, a few, like our “Case of the Year” will be no-brainers, but others aren’t as clear cut.  And, they’re certainly open to debate.  But, in my humble opinion here’s THE list, counting down David Letterman style:

5) Mancia v. Mayflower Textile Servs. Co., 2008 WL 4595175 (D. Md. Oct. 15, 2008)

If there ever was an opinion written by a judge to make a larger societal point, Mancia was certainly it.  Judge Paul Grimm, who’ll appear on this list in another slot as well, has clearly taken the mantle from Judge Scheindlin as the leading electronic discovery jurist.  He’d heretofore authored a number of significant opinions in this area, including Hobson and Thompson. Now, in Mancia he used a garden variety discovery dispute, which was typically rife with boilerplate objections and other obstreperous tactics, to highlight the Sedona Conference’s Cooperation Proclamation.

The lasting takeaway from the opinion is the notion that “[c]ourts repeatedly have noted the need for attorneys to work cooperatively to conduct electronic discovery, and sanctioned lawyers and parties for failing to do so.” To support this notion he cites the Sedona Conference Proclamation and the little used FRCP 26(g).  This opinion is noteworthy because it gives precedent to bolster the Sedona initiative and should provide a ready citation for all those counsel who aren’t getting the level of cooperation they need from the opposition.  It remains to be seen if other judges will follow suit, but this could be the beachhead for a more cooperative electronic discovery process in 2009 and beyond.

4) Flagg v. City of Detroit, 252 F.R.D. 346 (E.D. Mich. 2008)

Flagg highlights the growing need to reconcile the electronic discovery landscape, which typically focuses somewhat myopically on email, with the larger informational trends which are now categorized by the use of blogs, social networking sites, instant messaging, and text messaging.  Flagg was one of the first to determine text messages (e.g., messages exchanged among certain officials and employees of the City of Detroit via city-issued text messaging devices) were discoverable under the standards of FRCP 26(b)(1).  The holding further demonstrated the challenges of conducting electronic discovery across information systems that mix personal information with business communications.  This type of information commingling will continue to escalate, causing significant long term electronic discovery challenges due to thorny privacy, privilege and policy implications.

3) Rhoads Indus., Inc. v. Bldg. Materials Corp. of Am., 2008 WL 4916026 (E.D. Pa. Nov. 14, 2008)

Rhoads is one of the first cases post Federal Rule of Evidence (FRE) 502, which recently created a national standard (versus the previous split in jurisdictions) and now states a “middle ground” for the determining of inadvertent disclosure during electronic discovery.  The key provision is (b)(2) which provides protection only if “the holder of the privilege or protection took reasonable steps to prevent disclosure.”  So, Rhoads took that “reasonableness” question head on in a scenario where the plaintiff Rhoads admittedly (yet inadvertently) produced over eight hundred privileged, electronic documents.  The decision is significant because it used the five-factor test stated in Fidelity, but put an undue weighting on the final test which was: “whether the overriding interests of justice would be served by relieving the party of its errors.”   This approach potentially threatens the development of sound case law that will be necessary to help the deployment of FRE 502 into practice because it casts too much uncertainty with its weighting of “fairness” (a problematically vague notion) in the analysis.  It will be interesting to see if/how this approach is subsequently adopted as we enter the New Year.

2) Qualcomm Inc. v. Broadcom Corp., 2008 WL 66932 (S.D. Cal. Jan. 7, 2008)

This for many was the case of the year given it’s far reaching implications for the legal community.  Some have argued that this isn’t an e-discovery abuse case per se, but more of an example of discovery abuses that just so happened to be centered around ESI.  In either case, the fraud, resulting cover-up, sanctions, ethical issues and privilege discussions made for insightful and thought provoking reading throughout 2008.  The lasting takeaway from Qualcomm appears to be the implications of not just committing discovery abuses, but the failure of having a well thought out e-discovery plan that is actively executed/monitored by outside counsel.  The resulting tension between outside counsel, inside counsel and the internal IT department may continue to escalate if more cases like this make the headlines in 2009.

1)  E-Discovery Case of the Year: Victor Stanley, Inc. v. Creative Pipe, Inc., 2008 WL 2221841 (D. Md. May 29, 2008)

Judge Grimm’s hallmark opinion has had the legal community buzzing over the past several months and the reason appears pretty straight forward.  In Victor Stanley Grimm builds on the holdings in Seroquel, O’Keefe and Equity Analytics, to boldly cast doubt on a practice so routine that it’s literally shocked the legal community into reevaluation:

(”[D]etermining whether a particular search methodology, such as keywords, will or will not be effective certainly requires knowledge beyond the ken of a lay person (and a lay lawyer) . . . .”

The notion that electronic discovery search is beyond the ability of most attorneys has caused tremors within the litigation support community who had a long history of blindly receiving keywords from counsel, running them and turning back over the results – often blissfully unaware of the extent to which those keyword searches actually located relevant information.  Victor Stanley’s analysis of the “reasonableness” of search protocols also has impact on the FRE 502 and therefore cements its place alongside other e-discovery “must reads” such as Zubulake and Morgan Stanley.

The cases above are my Top 5.  What additional cases do you think were important?  Please let me know by commenting on the cases you think shaped electronic discovery in 2008 and why.

Concept or content search continues to be a hot topic within the e-discovery community.  There’s a continuous stream of articles that discuss it.  Some that point out the positive.  Others that point out the limitations.  The courts have also gotten involved in the discussion.  Judge Grimm refers to concept search in e-discovery in Victor Stanley, Inc. v. Creative Pipe, Inc., 2008 WL 2221841 (D. Md. May 29, 2008).  Judge Facciola discusses concept search in Disability Rights Council of Greater Washington v. Washington Metropolitan Transit Authority, 242 F.R.D. 139 and other opinions.  Despite (or maybe because of) all the commentary on this topic, I find that while a lot of people think that concept search in e-discovery is good, many are not fully sure of exactly what concept search is, and how it is practically useful in e-discovery.   It’s pretty clear that after several years of commentary and hype, concept search has become something of a buzzword associated with many myths and misconceptions.  In an effort to better understand what concept search is and how it can help in e-discovery, I want to dispel two of the most common myths I have heard.

The “Concept Search is Concept Search” Myth

The first myth around concept search actually revolves around what it is.  In my experience, people tend to lump two different technologies together when talking about concept search: concept search and concept categorization.  It’s very common, for example, to see commentators say concept search even when what they are really talking about is concept categorization.  To make matters more confusing, people also use a plethora of other names including content search, content clustering or concept clustering when what they really mean is concept categorization.

So, what are the differences between concept search and concept categorization?  First, let’s start with concept search.  Concept search technologies find documents containing “concepts”.  I think that the Sedona Conference’s “Best Practices Commentary on the Use of Search & Information Retrieval Methods in E-Discovery“, provides a good definition of “concept” when used in a search context: “the combination of [a] query term and the additional terms identified by the thesaurus.”  In other words, concept search technologies find documents containing a specified term plus additional terms with similar meanings derived from a thesaurus.

Concept categorization, on the other hand, is actually not a search technology at all.  Concept categorization technologies do not “find” documents.  Rather, they categorize or group documents based on their similarity.   There are many different ways to group documents based on similarity.  Techniques include statistical (which assesses similarity based on word frequency), Bayesian classification (which weights words differently depending on factors in addition to statistical frequency, such as where the terms appear in a document), and semantic indexing (which takes into account the fact that many words used in a similar context may have a similar meaning).  It would take more time to describe these technologies in detail but the Sedona commentary has a good summary of these different technologies if you are interested in learning more.

As should now be apparent, these technologies are very different and using the same words to describe them is confusing.  It’s why it’s not surprising that a lot of the users of e-discovery services and software don’t have a strong understanding of what these technologies are or what benefits they can actually provide in practice.  Dispelling the myth that they can be lumped together is a critical first step in any conversation about concept search and how it can help in e-discovery.  This leads us to a second myth, that Concept Search is better than Keyword Search.  I’ll discuss this in my next blog post.

I was recently asked: “what are the first things you do when your client calls you about a case requiring e-discovery?”  So, for the benefit of all, I’ll post my answer.

My first caveat to the advice was context.  Since, while a lot of attorneys have attended CLEs or have read about e-discovery, it’s not the same in the real world.  As the old Spanish Proverb goes:

It’s not the same to talk of bulls as to be in the bullring.

Keeping in mind that reality may differ significantly from academics, here are some things to consider when the next e-discovery case comes up.   Please also keep in mind that these steps (like the EDRM workflow) aren’t linear and may in fact occur cyclically or in parallel:

1. Preserve, preserve, preserve

Nothing is more important than meeting the initial preservation obligation, which begins when litigation is “reasonably likely” – as opposed to just when the complaint is filed.  This first step in the long journey can easily be a trap for the unwary/unprepared.

The challenge once you’re past the trigger issue is to then identify the boundaries of the duty to preserve, i.e., what evidence must be preserved?   This inquiry is often initially comprised of identifying key players, date ranges and data types.

Another significant challenge in this step is to monitor and update the legal hold process.  And, given that litigation more often than not spans years, it’s easy to initially succeed at the preservation effort, but then later fail on execution.  The best way to minimize risk in this step is to move quickly from preservation to collection.  See Is Preservation in E-Discovery Overrated?

2. Work backwards

Once preservation (and ideally collection) is adequately covered, the next step is to start thinking about the end of the process and what success (or lack of failure) looks like.  The exposure and profile of the matter are important to consider when you embark upon an e-discovery project since it’s critical to scale discovery efforts appropriately.

One thing, in particular, that is very important to consider early in the process is the type of production format that will be preferred by reviewing counsel and the opposition.  TIFF-based image productions (which are historically well accepted) are often pitted against native file ESI reviews.  Either format may or may not be acceptable given the situation and the applicability of FRCP Rule 34.

3. Understand the technical landscape

Most attorneys, but for a rare few, aren’t capable of really comprehending technical nuances of the complex and interrelated IT systems found at most Fortune 2,500 enterprises.  Fortunately, they are quite adept at working with experts (either consulting or testifying) to help them get to the bottom of difficult to comprehend and explain issues.  The key is find the right technical people who understand IT systems and who can explain it to judges, juries, and attorneys alike, especially for some of the most common ESI repositories like: email servers, archival systems, shared network drives, instant messaging servers, archival repositories (e.g., tape libraries, real time back-up systems, etc.), records management systems, knowledge management systems, proprietary, but highly leveraged, internal applications, offsite repositories (e.g., hosted IT or email systems) and significant partner or subsidiary data stores.  In many instances it will make sense to leverage or create a map of the data universe so that nothing is missed and inaccessibility arguments can be cogently detailed.

4. Get your lingo straight

Assumptions, whether in e-discovery or not, are often dangerous.  In the complex undertaking where multiple parties are handling ESI it’s critical to make sure that everyone is on the same page especially since every company handles IT, records management, ILM and information security differently.  So, when working with these disparate constituents the outset of an engagement is the right time to make sure everyone is on the same page.  Therefore, standardize on a set of commonly used terms. Examples of potentially ambiguous topics include “imaging” ,“archive”, and “records.”

5. Don’t assume your client will really be helpful

I’ve been involved with hundreds of e-discovery engagements and I’ve found that almost universally the end client professes a profound willingness to help out.  And yet, actual “help” is relatively rare.  To qualify this, it may be prudent to ask several additional questions:

• Does the Client have the time to actually help?  Everyone at the client’s site has a day job that they’re tasked with above and beyond transient e-discovery needs.  So, while bandwidth generally is important, what’s more critical is the ability to comply with aggressive judicial deadlines.
• Are the people helping the ones you’d want to see on the stand?  It’s often not realistic to have internal folks (especially IT and Records Managers) stay isolated during the various pre-trial events – meet & confer conferences and potentially 30(b)(6) depositions so it’s important to evaluate how a given witness will fare when providing testimony.
• How likely is it that you client would throw you under the bus if things went wrong?  In my opinion, there is now more reason for outside counsel to manage the risks of an e-discovery project going awry.  See, Sullivan and Cromwell’s suit against EED.  Some will wisely bring in 3rd party consultants/experts to have a neutral, unbiased constituent in the process.

6. Build a budget and team (internal/external)

Everyone is probably now aware of how expensive e-discovery can be if managed improperly.  This makes it all that more imperative to work quickly to get a rough sense of the scope (which will lead to a budget) and the client’s willingness to absorb associated charges.  The most important step is to right-size the e-discovery effort with the risks inherent in the corresponding litigation/investigation.  Otherwise, there’s a high likelihood that e-discovery process will be over-engineered (too expensive) or under-scoped (cutting dangerous corners).

7. Figure out your risk profile

Similar to right-sizing the budget, it also makes sense to adopt a “horses for courses” approach to e-discovery since there is no singular way to handle a given matter.  For example, in one case you make take forensic images, restore backup tapes, capture instant messaging data, harness metadata, or decide to do an automated review with a with a “clawback” provision. In either case, the only mistake is to assume that an approach from another, dissimilar matter is warranted in the instant case.

8. Assume the opposition is better informed than you are

While this actually may not be the case, it’s a safer bet that assuming a level of naiveté that may not exist.  What is certain is that the Plaintiff’s bar is increasingly well informed and can be very aggressive.  They’ve seen the playbook that calls for baiting the opposition into a discovery misstep that can result in significant, case altering sanctions.  According to a recent survey, 63% of the polled attorneys said that e-discovery is being abused by counsel, so it’s important to be wary initially.

It’s also important to consider the potential reciprocity of a given matter and adjust your position accordingly.  In many instances it’s easy to consider your role only as a producing party, but with cross/counter claims it may be possible to simultaneously be propounding discovery and in the opposition’s shoes.

9. Prepare for an early case assessment

A recent industry survey found that effective early case assessment (ECA) approaches reduced overall litigation in half of the cases evaluated, and resulted in favorable outcomes for 76 percent of the cases.   The key to this methodology is to use the available next generation case analysis solutions earlier in the process, not just to review data for relevancy and privilege, but to:

• Identify the key players. This is critical in order to have a defensible legal hold process
• Evaluate the posture of the case to determine how it looks on the merits
• Diagnose potential outliers in the e-discovery process to facilitate meet and confer discussions and help create “inaccessibility” arguments
• Conduct a search term analysis for keyword negotiations during meet and confer discussions.  Objectively demonstrating the results of proposed search queries can go a long way in speeding up keyword negotiations

10. Don’t take search for granted

For many attorneys, e-discovery search is just like Lexis or Google.  Unfortunately, that isn’t the case.  Instead, it’s become highly complex and is now receiving significant judicial scrutiny.  In Victor Stanley v. Creative Pipe Judge Grimm suggested that attorneys need to rethink how they’ve traditionally managed the search process:  “[F]or lawyers and judges to dare opine that a certain search term or terms would be more likely to produce information than the terms that were used is truly to go where angels fear to tread.”  It’s now important to devise (and share at early meet & confer conferences) a defensible search strategy that can withstand judicial scrutiny.

In my last post, I discussed how the “black box” design of enterprise search engines makes it challenging to defensibly use keyword search in e-discovery and follow Judge Grimm’s guidance in Victor Stanley, Inc. v. Creative Pipe, Inc., 2008 WL 2221841 (D. Md. May 29, 2008).  In Victor Stanley, Judge Grimm notes that because keyword search technology is prone to producing over- and under-inclusive results, attorneys using keyword search should adopt one of two approaches: either collaborate with the opposing party to agree on keyword search methodology, or utilize best practices that demonstrate they have taken reasonable measures to reduce over- and under-inclusiveness.  However, the black box search technologies that are used in e-discovery today make following this guidance difficult.  They can’t reduce under-inclusiveness without increasing over-inclusiveness.  And they make it expensive to utilize collaborative or best practices methodologies including testing, sampling, refining and documenting searches.  All of which begs an obvious question: what can be done to improve search for e-discovery?

In my opinion, the answer is simple: e-discovery search needs to become more transparent.  Instead of being forced to feed one search query at a time into a “black box” search engine and then getting results  with no idea how those results were generated, lawyers and litigation support professionals need technology that provides them with greater visibility into the search process. They need to understand how the results were obtained, so they can reduce both the over- and under-inclusiveness of keyword search, and easily follow Judge Grimm’s advice to improve the defensibility of their search methodology.

A transparent search solution should have four key elements:

1. Transparent query expansion.  Query expansion is the process by which search engines take the query that the user submitted and expand or convert it into a new and improved form.  Wildcard, stemming, concept and fuzzy searches all follow this query expansion process.  For example, the search “divers*,” would be expanded to search for all the words that start with “divers” in the data set, such as “diverse,” “diversity,” “diversion,” “diversification,” etc.  In transparent search, query expansion would be exposed to users, allowing them to include or exclude expanded keywords. To continue with the previous example, a user that is searching for documents related to diversity would then have the ability to exclude false positive expanded terms, such as “divers”, “diversion,” and “diversification” from the search.  Making query expansion transparent can significantly reduce the over-inclusiveness of keyword search.  It also makes it practical to use technologies, such as concept and fuzzy search, that have not been used to date because of their complexity and tendency to produce massively over-inclusive results.
2. Multiple query support. When a search contains multiple keyword queries, such as “hiring” and “interview,” transparent search should provide visibility into the results for each individual query as well as the combination of all the queries. For example, with the search “hiring OR interview,” users should have separate visibility into the results for “hiring” and “interview” as well as “hiring OR interview.”  They should know that out of the 100 documents that match “hiring OR interview”, only 5 match interview and 95 match hiring.  This kind of visibility is critical if you want to either collaborate or follow search testing, sampling, and refinement best practices when there are a large number of queries.
3. Rapid sampling. Transparent search should support the ability to rapidly sample the results from all of the individual queries, such as “hiring” and “interview”, contained within a search. It should also be easy to take a random sample of non-matching documents in order to assess whether one or more searches have identified as many of the relevant documents as possible.  As Judge Grimm states in Victor Stanley when assessing keyword searches used to find privileged documents, “The only prudent way to test the reliability of the keyword search is to perform some appropriate sampling of the documents determined to be privileged and those determined not to be in order to arrive at a comfort level that the categories are neither over-inclusive nor under-inclusive.”
4. Automated documentation. Transparent search technology needs to document all aspects of the search process including (but not limited to) any keyword that has been excluded during transparent query expansion, the combined results of a search containing multiple individual queries, and the results for each of the individual queries within that search.  Automatically documenting the search methodology used and the results obtained is critical so that users can “show their work” if their search methodology is ever called into question.

Benefits of Transparent Search

By addressing the main technology challenges of keyword search, transparent search provides significant benefits to attorneys and litigation support professionals using search for e-discovery. First, parties that adopt transparent search can improve the defensibility of their e-discovery search practices. By enabling iterative testing, sampling and refinement, transparent search allows users to adopt the approaches recommended by Judge Grimm when it was previously impractical to do so.  At the end of the day, this means less risk.

Second, the use of transparent search can substantially reduce downstream production and review costs by removing false positives. For example, it is not uncommon for certain wildcard searches to generate results where 20-40% of the included documents are false positives that can be removed by transparent query expansion.  This can result in thousands of dollars of savings on a single search query.

Finally, transparent search can dramatically reduce the time and cost required to complete the search and culling stage of e-discovery. Currently, it can take hundreds of hours to run a significant number of searches one at a time, document the results of each search, and sample and refine each individual query. With transparent search, running multiple queries and documenting each of the individual results takes minutes. Sampling each of the individual queries takes seconds.

When it comes to e-discovery search, it’s important to recognize that there are no “silver bullets.”  Search will remain an imperfect science with the possibility of over- and under-inclusive results.  But equally, there is no doubt that search remains the best solution for reducing the vast quantities of electronic information that are a part of every e-discovery process down to a reasonable level for human review. While attorneys and litigation support professionals can’t completely remove the imperfections of keyword search, they can, with transparent search, take action to minimize the impact of these imperfections and defensibly meet the requirements of new case law.  In doing so, they will be able to turn their attention to where it should be: the substance of the case.