Response in Opposition re 564 Motion to Exclude the Purported Expert Opinions — In re BofA Unemployment Litigation (Dkt. 614)

Record facts

U.S. District Court for the Southern District of California · No. 3:21-md-02992-GPC-MSB · Doc. 614 · 2026-04-17 · Docket on CourtListener

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Opposition to Def’s Motion to Exclude Opinions of Jay Minnucci; 
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JOSEPH W. COTCHETT (SBN 36324) 
jcotchett@cpmlegal.com 
BRIAN DANITZ (SBN 247403) 
bdanitz@cpmlegal.com 
KARIN B. SWOPE (Pro Hac Vice) 
kswope@cpmlegal.com 
VASTI S. MONTIEL (SBN 346409) 
vmontiel@cpmlegal.com 
CAROLINE A. YUEN (SBN 354388) 
cyuen@cpmlegal.com 
COTCHETT, PITRE & McCARTHY, LLP 
840 Malcolm Road, Suite 200 
Burlingame, CA 94010 
Telephone: (650) 697-6000 
Fax: (650) 697-0577 
MICHAEL RUBIN (SBN 80618) 
mrubin@altber.com 
STACEY M. LEYTON (SBN 203827) 
sleyton@altber.com 
CONNIE K. CHAN (SBN 284230) 
cchan@altber.com 
JAMES BALTZER (SBN 332232) 
jbaltzer@altber.com 
KATHERINE BASS (SBN 344748) 
kbass@altber.com 
ALTSHULER BERZON LLP 
177 Post Street, Suite 300 
San Francisco, CA 94108 
Telephone: (415) 421-7151 
Fax: (415) 362-8064 
Co-Lead Counsel for Plaintiffs and the Class 
UNITED STATES DISTRICT COURT 
SOUTHERN DISTRICT OF CALIFORNIA 
IN RE BANK OF AMERICA 
CALIFORNIA UNEMPLOYMENT 
BENEFITS LITIGATION 
Case No. 3:21-md-02992-GPC-MSB 
PLAINTIFFS’ MEMORANDUM OF 
POINTS AND AUTHORITIES IN 
OPPOSITION TO DEFENDANT’S 
MOTION TO EXCLUDE CERTAIN 
EXPERT OPINIONS OF JAY 
MINNUCCI 
This Document Relates to All Actions 
Date: 
April 17, 2026 
Time: 
1:30 p.m. 
Judge: 
Hon. Gonzalo P. Curiel 
Ctrm: 
2D (2nd Floor) 
REDACTED PUBLIC VERSION
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Table of Contents 
Page 
I. 
INTRODUCTION ...................................................................................................... 1 
II. BACKGROUND ........................................................................................................ 2 
III. LEGAL STANDARDS .............................................................................................. 6 
IV. ARGUMENT .............................................................................................................. 7 
A. 
Minnucci’s opinions on excess wait time are well supported by the 
evidence and his extensive industry experience. ................................................... 7 
1. Minnucci’s opinions regarding industry standards are well-supported. ........ 8 
a. Minnucci was not required to review ContactBabel’s underlying data 
because the survey is well accepted as reliable within the industry. ...... 8 
b. Minnucci had sufficient justification to use the ContactBabel 
benchmark as one basis for evaluating the Bank’s Claims Call  
Center call wait-time performance. ................................................................. 10 
2. Minnucci’s analysis of the Bank’s Claims Call Center data is reliable. ...... 15 
B. 
Minnucci’s Avoided-Cost Opinions Are Reliable. ............................................. 17 
1. Minnucci permissibly relies on his own clients’ sample data......................... 17 
2. Minnucci’s avoided workload calculations are reliable. .................................. 20 
3. Minnucci’s idle hour charges calculations are reliable. .................................... 21 
C. 
Minnucci’s Workforce Management opinion is well-supported and 
helpful. ................................................................................................................................ 23 
D. 
Minnucci’s Opinions on the Deliberateness of the Bank’s Staffing  
Decision Are Based on Extensive Industry Experience and Will  
Assist the Trier of Fact. ................................................................................................ 24 
V. CONCLUSION......................................................................................................... 25 
 
 
 
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Table of Authorities 
Cases 
Page(s) 
Alaska Rent-A-Car, Inc. v. Avis Budget Grp., Inc., 
738 F.3d 960 (9th Cir. 2013) .................................................................................... 7, 16 
Brighton Collectibles, Inc. v. RK Tex. Leather Mfg., 
923 F. Supp. 2d 1245 (S.D. Cal. 2013)......................................................................... 24 
Camenisch v. Umpqua Bank, 
763 F. Supp. 3d 871 (N.D. Cal. 2025) .............................................................. 11, 20, 25 
Cholakyan v. Mercedes-Benz USA, LLC, 
281 F.R.D. 534 (C.D. Cal. 2012) .................................................................................. 19 
Christensen v. Lemaster, 
2006 WL 753227 (D. Idaho Mar. 21, 2006) ................................................................... 9 
City of Pomona v. SQM N. Am. Corp., 
750 F.3d 1036 (9th Cir. 2014) ...................................................................................... 11 
Claar v. Burlington N. R. Co., 
29 F.3d 499 (9th Cir. 1994) .......................................................................................... 16 
Daubert v. Merrell Dow Pharms., Inc., 
509 U.S. 579 (1993) ............................................................................................... passim 
Daubert v. Merrell Dow Pharms., Inc. (Daubert II), 
43 F.3d 1311 (9th Cir. 1995) .................................................................................... 6, 22 
Diaz v. United States, 
602 U.S. 526 (2024) ...................................................................................................... 24 
Elosu v. Middlefork Ranch Inc., 
26 F.4th 1017 (9th Cir. 2022) ....................................................................................... 22 
Faust v. Comcast Cable Commc’ns Mgmt., LLC, 
2014 WL 3534008 (D. Md. July 15, 2014) .................................................................. 14 
Fortune Dynamic, Inc. v. Victoria's Secret Stores Brand Mgmt., Inc., 
618 F.3d 1025 (9th Cir. 2010) ...................................................................................... 15 
Goodness Films, LLC v. TV One, LLC, 
2014 WL 12780291 (C.D. Cal. May 19, 2014) ...................................................... 14, 18 
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Griffo v. Oculus VR, Inc., 
2018 WL 6265067 (C.D. Cal. Sept. 18, 2018) ............................................................. 10 
Hangarter v. Provident Life & Acc. Ins. Co., 
373 F.3d 998 (9th Cir. 2004) ................................................................................. passim 
Hemmings v. Tidyman's Inc., 
285 F.3d 1174 (9th Cir. 2002) .................................................................................. 2, 20 
Hyer v. City & Cnty. of Honolulu, 
118 F.4th 1044 (9th Cir. 2024) ..................................................................................... 22 
JH Kelly, LLC v. AECOM Tech. Servs., Inc., 
605 F. Supp. 3d 1295 (N.D. Cal. 2022) ........................................................................ 22 
Johnson v. Nat. Gas Fuel Sys., Inc., 
No. 1:19-CV-00105-SAB, 2024 WL 3718097 (E.D. Cal. Aug. 8, 2024) .................. 8, 9 
Kennedy v. Collagen Corp., 
161 F.3d 1226 (9th Cir. 1998) ........................................................................................ 2 
Khadera v. ABM Industries Inc., 
2011 WL 6813454 (W.D. Wash. Dec. 28, 2011) ......................................................... 15 
Kim v. Benihana, Inc., 
2024 WL 3550390 (C.D. Cal. May 20, 2024) .............................................................. 20 
King v. GEICO Indem. Co., 
712 Fed. App’x 649 (9th Cir. 2017) ............................................................................... 8 
Krommenhock v. Post Foods, LLC, 
334 F.R.D. 552 (N.D. Cal. 2020) .................................................................................. 12 
Kumho Tire Co., Ltd. v. Carmichael, 
526 U.S. 137 (1999) ........................................................................................................ 6 
Legendary Art, LLC v. Godard, 
2012 WL 3550040 (E.D. Pa. Aug. 17, 2012) ............................................................... 19 
In re Live Concert Antitrust Litig., 
863 F. Supp. 2d 966 (C.D. Cal. 2012) .......................................................................... 20 
Lloyd v. Conseco Fin. Corp., 
2001 WL 36097624 (C.D. Cal. Oct. 19, 2001) ...................................................... 17, 20 
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Loeffel Steel Prods., Inc. v. Delta Brands, Inc., 
387 F.Supp.2d 794 (N.D. Ill. 2005) .............................................................................. 18 
McCoy v. DePuy Orthopaedics, Inc., 
2024 WL 1705952 (S.D. Cal. Apr. 19, 2024) ........................................................ 10, 19 
Messick v. Novartis Pharm. Corp., 
747 F.3d 1193 (9th Cir. 2014) ........................................................................................ 6 
Mighty Enters., Inc. v. She Hong Indus. Co., 
745 F. App’x 706 (9th Cir. 2018) ................................................................................. 19 
Multimedia Pat. Tr. v. Apple Inc., 
2012 WL 5873711 (S.D. Cal. Nov. 20, 2012) .............................................................. 14 
N. Wind Constr. Servs., LLC v. Campos EPC, LLC, 
2023 WL 196618 (D. Idaho Jan. 13, 2023) .................................................................. 24 
Ngethpharat v. State Farm Mut. Auto. Ins. Co., 
2025 WL 2161754 (W.D. Wash. July 29, 2025), amended, 2025 WL 
2372904 (W.D. Wash. Aug. 14, 2025) ......................................................................... 15 
Primiano v. Cook, 
598 F.3d 558 (9th Cir. 2010), as amended (Apr. 27, 2010) ........................................... 9 
Pyramid Techs., Inc. v. Hartford Cas. Ins. Co., 
752 F.3d 807 (9th Cir. 2014) ........................................................................................ 11 
Remien v. EMC Corp., 
2008 WL 597439 (N.D. Ill. Mar. 3, 2008) ................................................................... 14 
Roblox Corp. v. WowWee Grp. Ltd., 
2024 WL 4057418 (N.D. Cal. Sept. 3, 2024) ............................................................... 12 
Ruiz v. XPO Last Mile, Inc., 
2017 WL 2263046 (S.D. Cal. May 23, 2017) .............................................................. 16 
Snead v. Wright, 
625 F. Supp. 3d 936 (D. Alaska 2022) ........................................................................... 9 
Sonos, Inc. v. Google LLC, 
2023 WL 3933071 (N.D. Cal. June 9, 2023) ................................................................ 12 
Southland Sod Farms v. Stover Seed Co., 
108 F.3d 1134 (9th Cir. 1997) ...................................................................................... 19 
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Stephens v. Union Pac. R.R. Co., 
935 F.3d 852 (9th Cir. 2019) .................................................................................... 9, 10 
United States Equal Emp. Opportunity Comm’n v. Placer ARC, 
147 F. Supp. 3d 1053 (E.D. Cal. 2015) .......................................................................... 7 
United States Fid. & Guar. Co. v. Ulbricht, 
576 F. Supp. 3d 850 (W.D. Wash. 2021) ....................................................................... 9 
United States v. Nichols, 
786 F. App’x 624 (9th Cir. 2019) ........................................................................... 22, 23 
United States v. Sandoval-Mendoza, 
472 F.3d 645 (9th Cir. 2006) .......................................................................................... 7 
United States v. W.R. Grace, 
504 F.3d 745 (9th Cir. 2007) ........................................................................................ 10 
United States v. Zafaranchi, 
2024 WL 3924705 (W.D. Wash. Aug. 23, 2024) ......................................................... 24 
Other Authorities 
Federal Rule of Evidence 702 .............................................................................. 2, 6, 22, 25 
Federal Rule of Evidence 703 .............................................................................................. 8 
Federal Rule of Evidence 704 (a)–(b) ................................................................................ 24 
Federal Rule of Evidence 705 ............................................................................................ 10 
“Workforce Management” (“WFM”) ................................................................................ 23 
 
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I. 
INTRODUCTION 
Jay Minnucci is an expert on the call center industry. Based on his more than four 
decades of industry experience and his personal review of the Bank’s documents, data, and 
testimony and other evidence in the record, Minnucci reached a series of well-supported 
opinions. See Ex. 1 (Minnucci Rep) ¶¶ 12-17 (summary of opinions).1 Among these were 
his principal opinion that during the applicable two-month class period (September 13, 
2020 to November 21, 2020), members of the Customer Service Class who telephoned the 
Bank’s Claims Call Center to pursue unauthorized ATM transaction claims were forced to 
wait on hold for an average of 
, an extraordinarily long wait time that far 
exceeded any average wait time in the call center industry, where the industry standard 
metric, Average Speed to Answer (“ASA”), is customarily measured in seconds, not 
minutes. Id. ¶¶ 12, 36, 52. 
Minnucci also concluded, again based on a combination of his industry experience 
and his review of the relevant evidence, that the Bank’s extraordinarily lengthy ASA of 
 was driven by the Bank’s inadequate staffing at its Claims Call Center 
during periods of 
. Id. ¶¶ 15, 58-81. Finally, Minnucci 
calculated the likely “avoided cost” financial savings to the Bank resulting from its gross 
understaffing of its Claims Call Center during the class period. Id. ¶¶ 106-113.  
The Bank does not challenge Minnucci’s expertise or his extensive call center 
industry experience. Nor can it dispute that its Claims Call Center’s ASA was nearly 
 
 during the class period, a figure based on the Bank’s own data. Instead, the Bank 
seeks to exclude Minnucci’s testimony because it disagrees with his opinion about the 
“industry standard” call wait time, to which Minnucci compared the 
 that 
Customer Service Class members had to wait, on average, before someone would pick up 
the telephone at the designated (800) number to respond to them. Bank Mot. at 4, 3-15; Ex. 
1 ¶¶12, 52. According to the Bank, Minnucci cannot consider the call center performance 
 
1 “Ex.” refers to Exhibits to the Declaration of Regina Wang. 
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data of 214 call centers in 2020, as aggregated and published by ContactBabel, because he 
did not personally analyze and verify all of the supporting data provided by that well-
respected publication. Bank Mot. 9-11; see Ex. 1 ¶ 12. But “objections to the inadequacies 
of a study are more appropriately considered an objection going to the weight of the 
evidence rather than its admissibility.” Hemmings v. Tidyman's Inc., 285 F.3d 1174, 1188 
(9th Cir. 2002). Under Federal Rule of Evidence 702 and Daubert v. Merrell Dow Pharms., 
Inc., 509 U.S. 579 (1993), the trial judge must determine only “whether or not the reasoning 
is scientific and will assist the jury. If it satisfies these two requirements, then it is a matter 
for the finder of fact to decide what weight to accord the expert’s testimony.” Kennedy v. 
Collagen Corp., 161 F.3d 1226, 1230 (9th Cir. 1998).  
The Bank’s remaining challenges likewise question whether certain aspects of 
Minnucci’s opinions are sufficiently supported. For example, the Bank disputes whether 
Minnucci properly disaggregated the data he received from the Bank to evaluate its 
performance (even though the only reason disaggregation was necessary was because the 
Bank did not maintain and produce more granular data), whether the Bank’s forecasting 
models could be accurately relied upon to predict call demand, and whether Minnucci’s 
evidence-based assessment of the grounds for the Bank’s staffing decisions impermissibly 
veered into testimony about the Bank’s state of mind. None of these are valid grounds for 
excluding Minnucci’s expert analysis in its entirety. 
II. 
BACKGROUND 
Minnucci’s expert opinions principally apply to the claims of the Customer Service 
Class, i.e., members of the Claim Denial Class and Credit Recission Class who telephoned 
the Bank’s customer service telephone number for EDD cardholders (in accordance with 
the instructions on the back of their Bank-issued debit cards) at any time from September 
13, 2020 through November 21, 2020 and had their call routed to the Bank’s Claims Call 
Center. ECF 494 at 96-97; ECF 324 at 1:27-2:2.  
Jay Minnucci has worked in the call center industry for more than 40 years. Ex. 1 
¶5. He was retained by Plaintiffs to review Bank data related to its Claims Call Center and 
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to evaluate the Call Center’s performance during 2020 and 2021, in particular, to assess: 
whether and to what extent that performance fell below industry standards; whether the 
Call Center’s operational processes and technology fell below industry standards; whether 
there were reasonable alternatives the Bank could have implemented to anticipate call 
volumes and increase staffing or otherwise reduce ASA wait times; and how to determine 
the Bank’s “avoided costs” savings resulting from its understaffing decisions. Id. ¶ 2. In 
formulating his opinions, Minnucci considered hundreds of Bank documents, the Bank’s 
2020-2021 Call Metrics, Claims Call Center data in the Bank’s Avaya database, 
ContactBabel publications from 2012 to 2020, declarations and depositions of the Bank’s 
30(b)(6) designees and other Claims Call Center personnel, and call center industry 
documents and other external sources. Id. ¶ 5, n.1, App. D, E, F, G, H, I.  
Minnucci’s principal opinion was that the Bank’s Claims Call Center subjected 
callers to extremely long wait times, resulting in performance “far below” the industry 
standard: in contrast to the 
 
, the industry standard ASA was 75 seconds. Id. ¶¶ 12 
& n.1, 48, 51-52. Minnucci reached this conclusion based on extensive review of Bank 
Call Center data, comparison of the Bank’s performance to aggregate data in the 2021 
ContactBabel U.S. Contact Center Decision-Makers’ Guide (the “2021 ContactBabel 
Report”), which included performance data from 214 U.S.-based call centers, and on his 
own industry experience. Id. ¶ 12 & n.1. Minnucci also noted that because 
 
 
 
 
. Id. ¶¶ 49-50. Even worse, because the ASA data only accounts for 
the time spent waiting on calls that are eventually answered and not the time spent by 
callers who eventually hang up while till on hold, 
 
 
. Id. ¶¶ 14, 53, 55-57.  
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Next, Minnucci analyzed whether there were reasonable alternative procedures the 
Bank could have implemented to 
 
. In 
conducting this analysis, Minnucci drew on his own significant and direct experience with 
call center staffing, industry publications, relevant Bank documents, including call center 
staffing reports, and deposition testimony of Bank employees. Id. ¶¶ 61-66. He determined 
that in 2020, the 
 
 
. Id. ¶¶ 64-65. The Bank nonetheless ignored this 
 
 
–a 
practice Minnucci concluded was completely inconsistent with industry practice and was 
known to result in 
. Id. ¶¶ 
1-66. Despite delays caused by this 
 
 
 
 
 
. Id. ¶¶ 67-76. Minnucci accordingly concluded, given the 
 
 
 
 
. Id. ¶¶ 15, 68-76.2 
 
2 Minnucci also surveyed the then-available call center technology and determined that 
there were 
 
 
 
. Id. ¶¶ 78-80. 
 
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Minnucci also made a series of straightforward calculations regarding the money the 
Bank likely saved by 
. See 
Id. § VII.D. These calculations also rested on Minnucci’s extensive industry experience 
and the data obtained through discovery and otherwise. Id.  
First, to calculate the total number of excess hours that Customer Service Class 
members had to wait for their calls to be answered, Minnucci subtracted the industry 
standard ASA wait time from the Bank’s average ASA wait time. Id. ¶ 107. He then 
multiplied the resulting average excess wait time per call (
) by the total 
number of calls made by Customer Service Class members to the Bank’s Claims Call 
Center during the class period. Id.  
Second, to calculate the Bank’s “avoided cost” savings resulting from understaffing, 
Minnucci calculated the number of additional calls the Bank would have answered and 
handled with adequate staffing and the total estimated duration of all of those avoided calls, 
and compared that time to the Bank’s actual call center hours to determine the difference, 
i.e., the time saved due to understaffing. Id. ¶¶ 107-113. To perform these calculations, 
 (i.e., callers who called and hung up before their calls 
were answered and then called again), Minnucci first estimated the distinct caller demand, 
or the estimated total number of unique individuals who called the Bank but whose calls 
were not answered. Id. ¶ 109. While the distinct caller demand number would have been 
easily determined from review of the Bank’s own records if the Bank had maintained 
individual call record data from that period, the Bank insists that it kept no such records. 
Id. ¶ 110. In the absence of direct Bank data, Minnucci relied upon data created in the 
ordinary course of business from his own call center clients as a basis for estimating the 
likely proportion of Claims Call Center callers who did not call the Bank multiple times, 
and he explained in his Report why it was reasonable for him to use his own clients’ data 
to make that comparison. Id. ¶ 110, Tbl. 9, App. H. Minnucci then multiplied the likely 
percentage of distinct callers by the total number of calls that were not answered before the 
caller hung up to calculate the total distinct caller demand. Id. To calculate the Bank’s cost 
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savings resulting from its failure to provide industry-standard service, Minnucci multiplied 
the distinct caller demand number by the average length of call time, yielding the total 
workload hours the Bank should have provided, and he subtracted from that number the 
Bank’s actual paid workload hours to determine its net savings. Id. ¶ 111, Tbl. 10.  
Minnucci also explained that call centers must build in and pay for agent idle time 
to achieve industry-standard ASA. Id. 112-113. In order to factor in the appropriate amount 
of idle time that should be built into his calculations, Minnucci applied the industry-
standard Erlang-C formula, a methodology for determining staffing requirements based on 
distinct call volume and average call length. Id. Finally, to calculate the Bank’s savings 
from avoided costs associated with agent idle time, Minnucci applied the Erlang-C formula 
to the Bank’s distinct call volume and call lengths separately for each week during the class 
period. Id. ¶ 113, App. I, Tbl. 11.  
III. LEGAL STANDARDS 
Under Federal Rule of Evidence 702, a witness who is “qualified as an expert by 
knowledge, skill, experience, training, or education” may testify if the proponent of the 
expert’s testimony demonstrates it is more likely than not that (1) “the expert’s scientific, 
technical, or other specialized knowledge will help the trier of fact to understand the 
evidence or to determine a fact in issue;” (2) “the testimony is based on sufficient facts or 
data;” (3) “the testimony is the product of reliable principles and methods;” and (4) “the 
expert’s opinion reflects a reliable application of the principles and methods to the facts of 
the case.” “Rule 702 should be applied with a ‘liberal thrust’ favoring admission.” Messick 
v. Novartis Pharm. Corp., 747 F.3d 1193, 1196 (9th Cir. 2014). 
The trial judge has “the task of ensuring that an expert’s testimony both rests on a 
reliable foundation and is relevant to the task at hand.” Daubert, 509 U.S. at 597; accord 
Kumho Tire Co., Ltd. v. Carmichael, 526 U.S. 137, 141 (1999). “[T]he test under Daubert 
is not the correctness of the expert’s conclusions but the soundness of his methodology.” 
Daubert v. Merrell Dow Pharms., Inc. (Daubert II), 43 F.3d 1311, 1318 (9th Cir. 1995). 
“Expert opinion testimony is relevant if the knowledge underlying it has a valid connection 
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to the pertinent inquiry. And it is reliable if the knowledge underlying it has a reliable basis 
in the knowledge and experience of the relevant discipline.” Alaska Rent-A-Car, Inc. v. 
Avis Budget Grp., Inc., 738 F.3d 960, 969 (9th Cir. 2013). “‘[T]he factual basis of an expert 
opinion goes to the credibility of the testimony, not [] admissibility.’” United States Equal 
Emp. Opportunity Comm’n v. Placer ARC, 147 F. Supp. 3d 1053, 1060 (E.D. Cal. 2015) 
(quoting Hangarter v. Provident Life & Acc. Ins. Co., 373 F.3d 998, 1017 n.14 (9th Cir. 
2004)); see also United States v. Sandoval-Mendoza, 472 F.3d 645, 654–56 (9th Cir. 2006).  
IV. ARGUMENT 
Unable to dispute Minnucci’s qualifications, the Bank first seeks to exclude 
Minnucci’s “inputs and calculations” and then attacks his specific opinions on its avoided 
costs and whether the Bank acted deliberately. None of these challenges should succeed. 
A. 
Minnucci’s opinions on excess wait time are well supported by the 
evidence and his extensive industry experience.  
Minnucci’s principal opinion is that the wait times to which the Bank subjected 
Customer Service class members during the class period, an extraordinary 
 on 
average, far exceeded industry standards. Ex. 1 § VII.A. That opinion is fully supported by 
(1) Minnucci’s analysis of the Claims Call Center performance data, which includes 
industry-standard performance metrics like average speed to answer and call abandonment 
rates, and (2) his understanding of call center industry performance standards, based on 
over 40 years of call center industry experience (including firsthand observation and 
analysis of hundreds of call center operations and performance metrics) as well as his 
review of the relevant industry literature and survey data, including data from the 2021 
ContactBabel Report, a well-respected survey widely used throughout the call center 
industry that included performance metrics from 214 call centers, as well as other years of 
ContactBabel data. Ex. 1 ¶¶ 12 & n.1, 48, App. F. The Bank does not challenge Minnucci’s 
analysis of the Bank’s own call center data or his expertise to opine on the industry 
standard. Nor does the Bank seriously dispute Minnucci’s conclusion that the Bank’s ASA 
during the claims period 
. Instead, the Bank mostly 
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challenges the accuracy of the data used by Minnucci to quantify that difference, 
contending that the ContactBabel survey is not a sufficiently reliable source of information 
about what constitutes the industry standard. Bank Mot. 10-16. Those challenges go to 
weight, not admissibility. 
1. Minnucci’s opinions regarding industry standards are well-supported.  
It is well established that “experts may testify about industry standards.” King v. 
GEICO Indem. Co., 712 Fed. App’x 649, 651 (9th Cir. 2017). The Bank nonetheless 
challenges Minnucci’s use of the ContactBabel report to supplement his experience in 
determining the applicable industry standard for average call wait time. Bank Mot. 10-11. 
For “testimony about industry standards,” though, “reliability depends heavily on the 
knowledge and experience of the expert rather than the methodology or theory behind the 
testimony.” Johnson v. Nat. Gas Fuel Sys., Inc., No. 1:19-CV-00105-SAB, 2024 WL 
3718097, at *6 (E.D. Cal. Aug. 8, 2024). As Minnucci has explained, the results set forth 
in the ContactBabel report are fully consistent with his knowledge of the industry and his 
client experiences. Ex. 1 ¶¶ 12, 59. 
The Bank contends that Minnucci should not be allowed to rest his opinion on the 
ContactBabel report, even in part, because he did not personally analyze the data 
underlying the ContactBabel survey results, and it further contends that the ContactBabel 
industry standard is not an appropriate benchmark for the Bank’s performance. But “[t]he 
factual basis of an expert opinion goes to the credibility of the testimony, not the 
admissibility, and it is up to the opposing party to examine the factual basis for the opinion 
in cross-examination.” Hangarter, 373 F.3d at 1017 n.14 (citation omitted).  
a. Minnucci was not required to review ContactBabel’s 
underlying data because the survey is well accepted as reliable 
within the industry.  
Federal Rule of Evidence 703 allows experts to rely on the kinds of facts or data that 
“experts in the particular field would reasonably rely on . . . in forming an opinion on the 
subject,” whether or not those facts and data would otherwise be admissible. Indeed for 
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“testimony about industry standards, . . . reliability depends heavily on the knowledge and 
experience of the expert rather than the methodology or theory behind the testimony.” 
Johnson, 2024 WL 3718097, at *6; Snead v. Wright, 625 F. Supp. 3d 936, 939 (D. Alaska 
2022) (same); United States Fid. & Guar. Co. v. Ulbricht, 576 F. Supp. 3d 850, 856-57 
(W.D. Wash. 2021) (admitting evidence supported by knowledge and experience); 
Christensen v. Lemaster, 2006 WL 753227, at *3 (D. Idaho Mar. 21, 2006) (allowing 
expert on industry standards to “render an opinion on how far [defendant] strayed from 
those standards”). Here, the Bank does not challenge Minnucci’s knowledge and 
experience from his 40 years in the industry. Instead, the Bank criticizes Minnucci for not 
having personally analyzed the data underlying ContactBabel’s industry survey results 
even though “an expert is permitted wide latitude to offer opinions, including those that 
are not based on firsthand knowledge or observation.” Daubert, 509 U.S. at 592; see also 
Hangarter, 373 F.3d at 1022, n.14 (“questions regarding the nature of [the expert’s] 
evidence went more to the ‘weight’ of his testimony—an issue properly explored during 
direct and cross-examination”); Primiano v. Cook, 598 F.3d 558, 567 (9th Cir. 2010), as 
amended (Apr. 27, 2010) (expert’s decision not to speak to party “might be useful to the 
jury as impeachment, but [did not] furnish[] an adequate basis for excluding his opinion”). 
Minnucci also explained that when his own clients ask him how their wait times compare 
with others, he turns to the ContactBabel survey for a benchmark. Ex. 2 (Minnucci Depo.) 
at 209:19-210:22. He also explained that the ContactBabel performance metrics were 
consistent with the industry standards that he was familiar with based on his own 
professional experience. Ex. 1 ¶ 40. 
The Bank challenges Minnucci’s opinions as conclusory and speculative, but its 
cited cases are inapposite. In Stephens v. Union Pac. R.R. Co., 935 F.3d 852, 855-57 (9th 
Cir. 2019), for example, the court excluded expert testimony about secondary exposure to 
asbestos because the testimony depended on an assumption (that the plaintiff’s father had 
been repeatedly exposed to asbestos at work and carried residue on his clothes back home), 
yet there was no evidence of significant exposure at his father’s work and thus no basis for 
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that assumption. Id. Stephens explicitly distinguished cases in which expert opinions “rest 
on actual data, not unfounded assumptions.” Id. at 858. Here, the Bank does not and cannot 
argue that Minnucci has no basis for his conclusions; rather, it objects to the persuasiveness 
of his analysis. Such an argument is for a jury, not a Daubert motion.  
Similarly, the Bank cites McCoy v. DePuy Orthopaedics, Inc., 2024 WL 1705952, 
at *11 (S.D. Cal. Apr. 19, 2024), where the court excluded an expert who merely parroted 
the opinions of the hiring party’s other experts. Unlike the expert in McCoy, Minnucci did 
not adopt another expert’s conclusions as his own; he reviewed the Bank’s call center data 
and analyzed it in comparison with the ContactBabel industry baseline. The Daubert 
inquiry is about the reliability of the method by which Minnucci conducted that analysis. 
The Bank may raise any perceived deficiencies on cross-examination, F.R.E. 705, but those 
arguments go to the weight a jury should place on Minnucci’s opinion, not whether his 
methodology was reliable. See United States v. W.R. Grace, 504 F.3d 745, 765 (9th Cir. 
2007) (argument about limitations of study relied on by expert “goes to the weight it should 
be accorded, but does not mean that an expert could not rely on it in forming an opinion”).3   
b. Minnucci had sufficient justification to use the ContactBabel 
benchmark as one basis for evaluating the Bank’s Claims Call 
Center call wait-time performance. 
The Bank’s specific challenges to the ContactBabel survey as a comparator for 
evaluating the Bank’s Claims Call Center performance also fail.  
The Bank objects that the data underlying that survey is derived from call centers 
servicing multiple industries, not just banks or other financial institutions. Bank Mot. 12-
15. As Minnucci explained, though, call center experts routinely rely on multi-industry 
 
3 The Bank’s citation to Griffo v. Oculus VR, Inc., 2018 WL 6265067 (C.D. Cal. Sept. 18, 
2018), is similarly inapplicable. In Griffo, the court excluded an expert who made the 
completely unsupported assertion that a copyright infringement led to 20% of the 
defendant’s revenue. Id. at *5-6 (citing Daubert, 509, U.S. at 597). Minnucci’s conclusions 
about the applicable industry standards are based on an identifiable source reasonably 
relied on by the field, not mere speculation.  
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data.4 In his report, Minnucci explained that “it is standard practice for call center leaders 
to compare across industries when establishing performance targets” and that “multi-
industry call center performance data is the best source for identifying ASA and 
abandonment rate benchmarks applicable to the Bank’s Claims call center.” Ex. 1 ¶¶ 41-
43. At his deposition, he further explained that customers “don’t pigeonhole their 
experience on a industry-by-industry basis,” which is why call center leaders do not ask 
for targets “specific to the Finance and Outsourcing industries.” Ex. 2 at 200:23–202:5.5 In 
his rebuttal report, Minnucci further explained that “[b]ecause callers compare their 
experiences—and form their reasonable expectations—based on interactions with call 
centers in different industries, it is standard practice for call center leaders to compare 
across industries when establishing performance targets,” and for that reason, “multi-
industry call center performance data across call center types, like the data contained in the 
2021 ContactBabel Report, is the best source for identifying industry-standard 
performance benchmarks that apply to even specialty call centers like the Bank’s Claims 
call center.” Ex. 3 (Minnucci Class Cert Rebuttal Rep.) ¶ 9; see City of Pomona v. SQM N. 
Am. Corp., 750 F.3d 1036, 1044 (9th Cir. 2014) (test for inclusion “is not the correctness 
of the expert’s conclusions but the soundness of his methodology”) (citations omitted).  
 
4 Contrary to the Bank’s mischaracterization, Minnucci never conceded that multi-
industry averages should not be used to set call wait-time performance targets for a 
company operating in a single industry. Mot. at 12. Rather, he consistently reiterated, in 
both his report and his deposition, that it is common for call centers to rely on inter-
industry data for establishing benchmarks and setting performance targets. Ex. 1 ¶¶ 41-
42; Ex. 2 (Minnucci Dep) 200:15-202:17.  
5 Even if there were “evidence in the record from which a reasonable factfinder could 
discredit [Minnucci’s] conclusion,” “[i]t is the jury’s province to determine how much 
weight, if any, to give the conclusions reached by [Minnucci] or any of the experts at trial.” 
Pyramid Techs., Inc. v. Hartford Cas. Ins. Co., 752 F.3d 807, 821 (9th Cir. 2014). 
“Weakness in the factual basis of an expert witness’ opinion generally ‘bear on the weight 
of the evidence rather than the admissibility.’” Camenisch v. Umpqua Bank, 763 F. Supp. 
3d 871, 884 (N.D. Cal. 2025) (citation omitted). 
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In any event, Minnucci has explained that, “[a]lthough it is my opinion, for the 
reasons stated above, that multi-industry call center performance data is the best source 
for identifying an ASA benchmark applicable to the Bank’s Claims call center, 
performance data specific to the Finance … industr[y] is available,” and that industry-
specific data shows that “[t]he average ASA reported in 2020 across the 29 Finance call 
centers surveyed by ContactBabel was 145 seconds (2.42 minutes).” Ex. 1 ¶ 43; Ex. 3 ¶ 
33. “Even if one were to limit the comparison group to the 29 Finance call centers in the 
survey, the Bank subjected EDD cardholders to an average wait time that was 
 
—longer than the 2 minute 25 second average of the Finance 
call center peer group.” Id. ¶ 34. Thus, “[r]egardless of whether one compares the Bank’s 
Claims call center to the Finance group … or all call centers, the performance of the 
Bank’s Claims call center is exceptionally poor and impacted all or nearly all CA EDD 
callers.” Id.  
Next, the Bank points to supposed differences between the call centers surveyed by 
ContactBabel and the Claims Call Center. Bank Mot. 12-15. But disputes about the 
appropriateness of a benchmark go to weight, not admissibility, as a party “can cross-
examine [the expert] on whether he accounted for all the relevant differences between the 
benchmark and [the circumstances] in this case.” Roblox Corp. v. WowWee Grp. Ltd., 
2024 WL 4057418, at *14 (N.D. Cal. Sept. 3, 2024).6 Moreover, Minnucci has explained 
why he believes the Bank’s performance during the class period was indicative of its 
performance throughout 2020 and 2021, making data from all of 2020 an appropriate 
baseline industry standard. Ex. 1 ¶¶ 82-105.  
 
6 See also Sonos, Inc. v. Google LLC, 2023 WL 3933071, at *6 (N.D. Cal. June 9, 2023) 
(“that a benchmark product is an imperfect benchmark product, or that there exists a 
better benchmark product, goes to evidentiary weight, not admissibility”); Krommenhock 
v. Post Foods, LLC, 334 F.R.D. 552, 576 (N.D. Cal. 2020) (failure to account for certain 
variables “go to weight and not admissibility”). In particular, these questions do not go to 
admissibility because, if the Bank’s position were adopted, a jury that found the fact of 
damage (based on the 
 average wait time) would be deprived of 
any basis for determining the resulting amount of damages. 
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The Bank next argues that Minnucci should not be permitted to place any reliance 
on pre-pandemic ContactBabel survey data because the Bank’s Claims Call Center 
experienced an 
 during part of the class period. Bank 
Mot. 13-14. Minnucci explained, though, that the data was relevant because there was 
considerable evidence that the Bank 
 
 
 (as 
shown in Figure 3 from his report, pasted below). Ex. 1 ¶¶ 52-53, 58-60; Ex. 2 at 76:8-
77:8. Indeed, Minnucci’s testimony is undisputed that by July 2020, the Bank had 
 
.” Ex. 1 ¶ 67.7  
 
7 Additionally, the Bank points to the EDD’s decision to waive the Bank’s ASA and 
related call center service-level obligations. Bank Mot. 14. That waiver language has 
nothing to do with Minnucci’s ability to testify as an industry expert concerning 
excessive wait times during the class period. Moreover, the actual waiver language falls 
far short of the Bank’s characterization. What the contract actually stated was that the 
Bank’s failure to perform its ASA obligations “will be excused if such failure occurs 
despite the Bank’s use of efforts that are commercially reasonable in the context of the 
COVID-19 pandemic.” Ex. 4 (Bank Letter to EDD) (emphasis added). As previously 
discussed and shown in Figure 3, the Bank’s failure to adjust its staffing to manage its 
call volume was far from commercially reasonable. Moreover, Minnucci has also 
testified that the Bank also failed to use readily available technology and procedures that 
would have substantially improved waiting time performance. Ex. 1 ¶¶ 74-81.  
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The Bank cites several cases to support its challenge to Minnucci’s reliance on pre-
pandemic ContactBable survey data as an appropriate comparator. Those cases are readily 
distinguishable and unpersuasive.  
The Bank first cites the tentative ruling in Goodness Films, LLC v. TV One, LLC, 
2014 WL 12780291, at *2 (C.D. Cal. May 19, 2014), where the party offering the expert 
testimony expressly conceded that the examples cited were not meant to be comparators. 
Id. The Bank then cites Multimedia Pat. Tr. v. Apple Inc., 2012 WL 5873711, at *9 (S.D. 
Cal. Nov. 20, 2012), where the court’s decision was narrowly tailored to the requirements 
for calculating reasonable royalty damages under patent case law. The citation to Faust v. 
Comcast Cable Commc’ns Mgmt., LLC, 2014 WL 3534008, at *5 (D. Md. July 15, 2014), 
is inapposite because the plaintiffs had represented they would not offer expert testimony 
and the offered report was prepared for a different action. Finally, Remien v. EMC Corp., 
2008 WL 597439, at *1 (N.D. Ill. Mar. 3, 2008), is not analogous because the expert there 
conceded that none of his studies assessed the relevant practice and that he “chose to 
arbitrarily eliminate relevant portions of data.” Id. In contrast, Minnucci has explained that 
the ContactBabel survey provided an industry-standard ASA, and he has explained why 
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this standard provides an appropriate comparison for the Bank’s performance. Ex. 1 ¶¶ 
12-14, 40-43, supra § IV(A)(1)(b). 
For these reasons, the Bank’s purported justifications for its Claims Call Center’s 
deplorable performance metrics do not require the exclusion of any of Minnucci’s 
opinions, let alone all of them. See Fortune Dynamic, Inc. v. Victoria's Secret Stores Brand 
Mgmt., Inc., 618 F.3d 1025, 1037–38 (9th Cir. 2010) (admitting results from survey 
although it “failed to replicate real world conditions, failed to properly screen participants, 
and was ‘highly suggestive,’” because “these criticisms, valid as they may be, go to ‘issues 
of methodology, survey design, reliability, ... [and] critique of conclusions,’ and therefore 
‘go to the weight of the survey rather than its admissibility’”).  
2. Minnucci’s analysis of the Bank’s Claims Call Center data is reliable.  
In assessing the impact of the Bank’s excessive call wait times on Customer Service 
class members during the class period, Minnucci relied on the Bank’s own data. Ex. 1 ¶ 
107. The Bank challenges Minnucci’s use of that data to establish average Claims Call 
Center wait times because (1) some class members experienced shorter wait times, so they 
would be overcompensated (while others would presumably be undercompensated), and 
(2) the Bank’s aggregate Claims Call Center data includes data from non-class members. 
Bank Mot. 15. Both arguments fail. 
First, while it of course true that some class members waited shorter or longer times 
than the average, at issue is the Bank’s aggregate damages liability, which is permissibly 
based on averages. See, e.g., Khadera v. ABM Industries Inc., 2011 WL 6813454, at *1, 6 
(W.D. Wash. Dec. 28, 2011) (allowing expert testimony calculating damages by applying 
average amount for representative group to the whole class); Ngethpharat v. State Farm 
Mut. Auto. Ins. Co., 2025 WL 2161754, at *11 (W.D. Wash. July 29, 2025), amended, 
2025 WL 2372904 (W.D. Wash. Aug. 14, 2025) (permitting expert to calculate classwide 
damages based on average damages amount and class size).  
Second, Minnucci explained why, based on his experience and expertise, he believed 
that the Bank’s ASA data appropriately captured the class members’ experiences. Contra 
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Bank Mot. 15–16. According to Minnucci, it was reasonable for him to conclude that “EDD 
cardholders experienced the same average wait times as all prepaid cardholders routed to 
the same call centers,” because those EDD cardholders accounted for most of the Claims 
Call Center’s call volume after the pandemic began and because all callers to the Bank’s 
Claims Call Center were routed in the same manner. Ex. 1 ¶¶ 29-30. Minnucci further 
explained that to the extent EDD cardholders’ experiences differed from the experiences 
of other callers, those class member cardholders would likely have experienced longer wait 
times because they were in California and thus were unlikely to receive the faster early 
morning service available when the Bank first opened at 8:00 a.m. Eastern/5:00 am Pacific. 
Id. ¶ 31. Where, as here, an expert has explained why a dataset is comparable to class 
members’ experience, challenges to the reasonableness of that opinion go to weight, not 
admissibility. See Alaska Rent-A-Car, Inc. v. Avis Budget Grp., Inc., 738 F.3d 960, 968–
69 (9th Cir. 2013) (admitting opinion extrapolating data from City of Juneau to estimate 
entire Alaska car market and applying a national market share comparison to Alaska).  
It was particularly reasonable for Minnucci to rely on the Bank’s aggregated Claims 
Call Center data because that was the only data the Bank kept and provided. The Bank 
failed to maintain that data on an individual caller basis, and it did not 
 
. Ex. 2 at 134:20–
135:5, 398:20-399:11; Ruiz v. XPO Last Mile, Inc., 2017 WL 2263046, at *2 (S.D. Cal. 
May 23, 2017) (admitting expert’s use of averages because a defendant “cannot be heard 
to complain that the damages [calculations] lack the exactness and precision of 
measurement that would be possible had he kept records”) (citation omitted).  
The Bank’s cited cases are again inapposite. In Claar v. Burlington N. R. Co., 29 
F.3d 499, 500-02 (9th Cir. 1994), the court found the experts’ conclusions were based only 
on subjective belief and unsupported speculation because they never explained their 
reasons and methods despite repeated orders from the court to do so and they made no 
effort to rule out other possible explanations. In contrast, Minnucci has explained his 
methods and why the aggregated data reliably describes the class members’ experiences. 
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Ex. 1 ¶¶ 29-31. Again, “[t]he factual basis of an expert opinion goes to the credibility of 
the testimony, not the admissibility.” Hangarter, 373 F.3d at 1017 n.14 (citation omitted).8  
B. 
Minnucci’s Avoided-Cost Opinions Are Reliable. 
The Bank challenges Minnucci’s calculations of the Bank’s avoided costs due to 
understaffing as unreliable, repeating its unfounded and legally incorrect critiques of 
Minnucci’s reliance on the 2021 ContactBabel Report and his own clients’ sample data, 
Claims Call Center data that was 
 
, and the industry-standard Erlang-C formula to calculate idle time. Bank Mot. 16-
22. The Bank’s disagreements with Minnucci’s well-reasoned and supported 
methodologies are not grounds for their exclusion. 
1. Minnucci permissibly relies on his own clients’ sample data. 
The Bank first argues that Minnucci’s distinct, i.e., non-repeat, caller calculation 
must be excluded because it rests in part on undisclosed data from unspecified clients of 
Minnucci’s operating in different industries pre-pandemic. Bank Mot. 17-19.9 As Minnucci 
explained, an exact determination of the distinct caller demand number could have been 
made using the Bank’s own call record data to isolate phone numbers that called once, 
abandoned the call, and then never called back, but the Bank stated that it did not maintain 
that data. Ex 1 ¶ 110. Minnucci explained that the next best thing was to use data from 
other clients, which is why he relied on data from his own clients which he had previously 
 
8 The Bank also cites Lloyd v. Conseco Fin. Corp., 2001 WL 36097624, *6 (C.D. Cal. Oct. 
19, 2001), in which the court rejected an expert opinion as irrelevant (not unreliable), 
because it did not speak to the issue in dispute and made no effort to screen for other 
variables. In contrast, the 
 
 
. 
9 Plaintiffs did not produce Minnucci’s underlying client data because it included client 
names and was proprietary. The Bank did not object, request a meet and confer, or move 
to compel for Plaintiffs to produce Minnucci’s clients’ data.  
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shared with other clients interested in distinct caller analyses. Id.; Ex. 2 at 407:7–13, 
410:22–411:13. 
The Bank contends that any opinion given by Minnucci that relies in whole or in 
part on his distinct caller calculations must be rejected because his clients did not operate 
call centers in exactly the same industry or time period as the Claims Call Center during 
the class period. But Minnucci explained that distinct caller calculations are typically based 
on abandonment and re-call rates, that he used the Bank’s own abandonment rate, and that 
he was able to calculate the relationship between abandonment rate and re-call rate using 
his clients’ data because this relationship remains fairly constant across industries and time. 
Ex. 1 ¶¶ 36, 53, App. H; Ex. 2 408:2-23, 409:3-10, 413:24-414:5, 414:7-20, 415:1-8, 
419:11-420:6.  
The Bank challenges that explanation, based on its reading of two trial court rulings, 
Goodness Films, 2014 WL 12780291, and Loeffel Steel Prods., Inc. v. Delta Brands, Inc., 
387 F.Supp.2d 794, 812-13 (N.D. Ill. 2005). But as previously explained, the court in 
Goodness Films, 2014 WL 12780291, at *2, excluded an expert’s opinion because it was 
based only on his experience rather than any principle or method, and because it provided 
comparisons even though the plaintiff had specifically “argue[d] that the examples in the 
[] report [were] not meant to be comparisons.” Here, Minnucci has explained that the data 
supplied by his consulting clients is an appropriate comparison because of the consistency 
in re-call rates across industries; indeed, he bills his own consulting clients for similar 
analyses using this cross-industry data. See Ex. 2 at 411:1-13, 414:7-415:8, 419:19-22.  
Loeffel also does not help the Bank’s argument. In that case, the court rejected 
comparators that the expert determined were comparable by tacitly assuming that “each 
participant in ‘an industry’ necessarily competes with every other participant in the 
industry,” even though this assumption itself was “demonstrably false, as [the expert]’s 
own report show[ed].” 387 F. Supp. 2d at 812-13. Here, by contrast, Minnucci explained 
that re-call rates from his clients’ call centers are appropriate comparators for the Bank’s 
Claims Call Center because those rates tend not to change much between industries, and 
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because the specific data he used has already proven effective as a benchmark for other 
clients. Ex. 2 at 411:1-13, 419:19-420:6. To the extent the Bank disputes these factual 
premises, “[t]he factual basis of an expert opinion goes to the credibility of the testimony, 
not the admissibility.” Hangarter, 373 F.3d at 1017 n.14 (citation omitted).  
Next, the Bank challenges Minnucci’s reliance on his clients’ re-call statistics 
because he did not personally verify their accuracy. The Bank cannot dispute that Minnucci 
came up with his own regression analysis to apply to that data, Ex. 2 at 405:6-13, so it takes 
issue with the fact that Minnucci relied on the re-call rates his clients determined by 
identifying which abandoned calls resulted in re-calls. Bank Mot. 18 (citing Ex. 2 at 
407:17-23, 408:2-5). But “[t]he fact that [an expert]’s opinions are based on data collected 
by others is immaterial.” Southland Sod Farms v. Stover Seed Co., 108 F.3d 1134, 1142 
(9th Cir. 1997). The Bank again cites cases where an expert adopted the hiring party or its 
other experts’ conclusions without analysis. See supra at 10 (distinguishing McCoy, 2024 
WL 1705952, at *11).10 These cases are clearly distinguishable because Minnucci did not 
parrot anyone else’s opinions but prepared his own calculations using data from his other 
clients. Ex. 1 App. H, Ex. 2 at 407:3-8. “Experts can rely on data provided to them without 
independent verification because the ‘factual basis of an expert opinion goes to the 
credibility of the testimony, not the admissibility, and it is up to the opposing party to 
examine the factual basis for the opinion in cross-examination.’” Mighty Enters., Inc. v. 
She Hong Indus. Co., 745 F. App’x 706, 709 (9th Cir. 2018) (quoting Hangarter, 373 F.3d 
at 1018 n.14).  
The Bank also rehashes its earlier argument that Minnucci’s model failed to account 
for significant variables that may have affected the Bank’s re-call rates such as the 
 
 
10 See also Cholakyan v. Mercedes-Benz USA, LLC, 281 F.R.D. 534, 546 (C.D. Cal. 
2012) (excluding opinion of expert who “reproduced [the hiring party’s other expert’s] 
declaration wholesale (including its typographical errors) as his own work”) (emphasis 
in original); Legendary Art, LLC v. Godard, 2012 WL 3550040, *4 (E.D. Pa. Aug. 17, 
2012) (rejecting breach of contract damages opinion as unreliable because it merely 
adopted an interested party’s unsupported, subjective opinion of the business’ estimated 
profit/loss and the expert disclaimed any familiarity with the industry). 
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. But the Bank’s own cases acknowledge the general rule that “flaws 
in a proffered expert’s analysis typically go to the weight, rather than the admissibility, of 
the expert’s testimony.” In re Live Concert Antitrust Litig., 863 F. Supp. 2d 966, 973 (C.D. 
Cal. 2012) (citing Hemmings v. Tidyman’s Inc., 285 F.3d 1174, 1188 (9th Cir. 2002). Only 
if the analysis is “so incomplete as to be inadmissible as irrelevant” should the opinion be 
excluded. Id. (citation omitted).11 And the party challenging the relevance must show the 
variables omitted from the analysis were “major factors” and their inclusion would have 
impacted the results. Id. at 974. The Bank’s mere assertion of possible other variables is 
not enough, and its failure to proffer counterevidence supporting its claims distinguishes 
the present case from those it cites. Cf. Camenisch v. Umpqua Bank, 763 F.Supp.3d 871, 
884 (N.D. Cal. 2025) (arguments about assumptions underlying expert conclusion go to 
impeachment not admission).  
2. Minnucci’s avoided workload calculations are reliable.  
After calculating distinct caller demand, Minnucci multiplied this number by 
average call length to determine the total workload hours needed to provide those callers 
with industry-standard performance levels. Ex. 1 ¶ 111. To determine the Bank’s avoided 
workload charges, he then subtracted the workload hours the Bank actually incurred. Ex. 
1 Tbl. 10. The Bank contends that Minnucci’s opinion about avoided workload charges is 
flawed because he relied on 
 
. 
Bank Mot. 19-20. But Minnucci appropriately relied on 
 
 
. Ex. 3 (Minnucci Reb) ¶ 24; Ex. 2 
 
11 For instance, in Kim v. Benihana, Inc., 2024 WL 3550390, *5-6 (C.D. Cal. May 20, 
2024), the court excluded conclusions that were blindly reliant on a study about an 
entirely different type of sushi than the one at issue in the case. In contrast, here, 
Minnucci has carefully explained why his sources appropriately inform his conclusions 
about the call center waits at issue here and are not so incomplete as to be irrelevant. See 
also supra n.7 (distinguishing Lloyd).   
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(Minnucci Dep) at 450:9-451:9. Thus, 
 
 
. Ex. 
1 ¶¶ 106-112. 
3. Minnucci’s idle hour charges calculations are reliable.   
The Bank also attacks Minnucci’s calculated avoided costs associated with agent 
idle time. To calculate the minimum number of idle hours required to achieve the industry 
standard ASA, Minnucci input the Claims Call Center data into the industry standard 
measure of the Erlang-C formula, which is frequently used by call centers to estimate 
upcoming staffing needs. Ex. 1 ¶¶ 112–13, Tbl. 11, App. I. The Bank contends that this 
methodology is so unreliable and so unsupported by the record that it must be stricken. 
The Bank starts by asserting that Minnucci’s reliance on Erlang-C is not consistent 
with the industry’s typical use of that formula. But Minnucci explained that the Erlang-C 
formula is in fact “most commonly employed by call centers to estimate staffing needs.” 
Ex. 1 ¶ 112. He also explained at his deposition that many call centers, including call 
centers operated by own clients, have used the Erlang-C for this purpose: 
Defendant: Have you advised any of your clients to use the 
Erlang-C formula?  
Minnucci: Absolutely. It’s -- it’s almost -- it really is assumed -
- I don’t have to say it, if they’re using workforce management 
system, they’re – they’re using it, or a slightly modified version 
of it. If they’re using a calculator, it’s Erlang-C. If they’re using 
an add-in to Excel, it’s Erlang-C. It is the standard beyond 
question in – in any call center that does this kind of work. 
Ex. 2 at 440:13–24.  
Unable to contest the general reliability of Erlang-C, the Bank argues that 
Minnucci’s methodology is improper because he applied Erlang-C retrospectively to 
model and predict past staffing needs, even though call centers generally use Erlang-C 
prospectively to forecast future staffing requirements. Bank Mot. 20–21. But the Bank 
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acknowledges that Erlang-C is regularly used by call centers to predict the number of 
agents a call center may need, and there is no reason it cannot be applied to historical data 
to show what the outcome would have been had it been properly used earlier. After all, 
Minnucci simply used the Erlang-C to calculate the amount of staffing that the Bank could 
and should have projected (and then hired and paid for) based on the 
 
. Ex. 1 ¶¶ 112-113. “Rule 702 is satisfied where the proffered 
testimony is based on scientifically valid principles.’” Daubert II, 43 F.3d at 1316. To the 
extent the Bank is arguing this valid method is “‘not appropriate for or used in [this 
circumstance,]’ [t]his challenge plainly goes to the weight of the evidence.” JH Kelly, LLC 
v. AECOM Tech. Servs., Inc., 605 F. Supp. 3d 1295, 1311 (N.D. Cal. 2022). 
The Bank also points to several websites about Erlang-C that the Bank has not 
indicated are properly subject to judicial notice and to a supposed concession at 
Minnucci’s deposition to argue that Erlang-C is not reliable here because its underlying 
assumptions were not present during the class period. Bank Mot. 21-22. The Bank has not 
explained why the Court may properly consider the websites it cites, or why its 
interpretation of the facts trumps Minnucci’s expert opinion. “Rule 702 does not license a 
court to engage in freeform factfinding, to select between competing versions of the 
evidence, or to determine the veracity of the expert’s conclusions at the admissibility 
stage.” Hyer v. City & Cnty. of Honolulu, 118 F.4th 1044, 1058 (9th Cir. 2024) (quoting 
Elosu v. Middlefork Ranch Inc., 26 F.4th 1017, 1026 (9th Cir. 2022)). 
Even if the Bank had presented its competing views on the applicability of Erlang-
C through the testimony of its own expert, that could not change the result because the 
Bank “fails to cite any cases holding that an expert’s opinion is unreliable and should be 
excluded merely because it differs from other expert opinions.” United States v. Nichols, 
786 F. App’x 624, 628 (9th Cir. 2019). Instead, “cross-examination, presentation of 
contrary evidence, and careful instruction on the burden of proof, rather than wholesale 
exclusion under an uncompromising ‘general acceptance' standard, is the appropriate 
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means by which evidence based on valid principles may be challenged.” Daubert, 507 
U.S. at 596.  
C. 
Minnucci’s Workforce Management opinion is well-supported and 
helpful. 
In support of his opinion that the Bank’s understaffing of its Claims Call Center in 
the face of foreseeable call volume surges was inconsistent with industry standards, 
Minnucci explained that the Bank could have relied on the forecasts of the 
 
. Ex. 1 ¶¶ 63-65. A WFM team in a 
call center is responsible for forecasting incoming call volumes and associated average 
handling times and projecting the number of staff needed to meet performance goals. Ex. 
1 ¶¶7(c), 63. Here, the record shows 
 
 
 
 
. 
 
The Bank’s assertion that Minnucci’s opinion is not supported by the record is 
therefore incorrect. Bank Mot. 22-23. The Bank contends that it used its 
 
 
 
 Ex. 1 ¶ 65; 
Bank Mot. 23 (citing Ex. 5). Moreover, the 
 
 Ex. 5. Even though 
the Bank’s expert Steve Hindle had a different view of the 
, the Ninth Circuit 
has rejected the notion that “an expert’s opinion is unreliable and should be excluded 
merely because it differs from other expert opinions.” Nichols, 786 F. App’x at 628. While 
the Bank also tries to gain traction for its argument by asserting that the 
 
 
, that assertion again goes to weight, not admissibility. Daubert, 507 U.S. at 596. 
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The Bank’s assertion that Minnucci did not adequately explain how the 
 
, Bank 
Mot. 23, also goes to weight but carries little, since the 
 
 
. Ex. 1 ¶ 64. (
 
 
 
) Minnucci’s opinion is thus clearly supported by the record, while it is the 
Bank’s own “expert [who] has not grounded his assumption with the real world facts of 
this case.” Brighton Collectibles, Inc. v. RK Tex. Leather Mfg., 923 F. Supp. 2d 1245, 
1255 (S.D. Cal. 2013). 
D. 
Minnucci’s Opinions on the Deliberateness of the Bank’s Staffing 
Decision Are Based on Extensive Industry Experience and Will Assist 
the Trier of Fact. 
At various points in his report, Minnucci refers to evidence that the Bank allowed 
its 
 
. See, e.g., Ex. 1 (Minnucci Rep) ¶¶ 68-74). The 
Bank argues that these straightforward assessments must be stricken as inadmissible state-
of-mind opinions. Bank Mot. 24-25. While Federal Rule of Evidence 704(b) provides that 
“[i]n a criminal case, an expert witness must not state an opinion about whether the 
defendant did or did not have a mental state or condition that constitutes an element of the 
crime charged or of a defense,” that Rule “does not apply in civil cases.” Diaz v. United 
States, 602 U.S. 526, 534 (2024). Instead, “generally, experts may offer testimony about 
a person’s state of mind in civil cases.” N. Wind Constr. Servs., LLC v. Campos EPC, 
LLC, 2023 WL 196618, at *5 (D. Idaho Jan. 13, 2023) (citing Fed. R. Evid. 704 (a)–(b)). 
Even in criminal cases, courts have rejected Rule 704(b) challenges to experts opining on 
industry practice and, for instance, “how [a defendant’s] call center and its practices 
aligned (or did not align) with [industry] norms.” United States v. Zafaranchi, 2024 WL 
3924705, at *4 (W.D. Wash. Aug. 23, 2024) (citations omitted).  
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The Bank cites cases excluding experts who did not have relevant knowledge or 
expertise allowing them to opine on the subjective state of mind or motives of the 
defendant. Bank Mot. 24-25. Those cases are not analogous because Minnucci is not 
speculating unjustifiably about a party’s subjective motive but rather applying his 
expertise about the industry to reach reasoned conclusions. See Camenisch, 763 F. Supp. 
3d at 882 (distinguishing inadmissible state of mind opinions from admissible testimony 
about industry practices and atypical behaviors that assist jury in evaluating whether to 
draw an inference of knowledge). Minnucci clarified in his deposition that he is “not in 
any way commenting on somebody’s state of mind.” Ex. 2 at 356:4-7. Instead, his opinion 
that the Bank “deliberately” understaffed the call center is based on his analysis of the 
Bank’s staff data, which shows that the 
 
 
 
 
. Ex. 1 ¶¶ 67-68; Ex. 2 at 354:4-
22, 355:16. That opinion is also based on his observation of the 
 
 
 
. Ex. 1 ¶¶ 59-71. These are not opinions on the Bank’s “state of mind,” 
but are permissible opinions rooted in Minnucci’s 40+ years of relevant industry 
experience and his analysis of the Bank’s own records and data.  
V. 
CONCLUSION 
Minnucci’s opinions are relevant, reliable and will assist the trier of fact. They 
should be admitted under Rule 702. Accordingly, Plaintiffs respectfully request that the 
Court deny the Bank’s motion to exclude his expert opinion testimony.  
 
 
 
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Respectfully submitted, 
Dated: January 8, 2026  
COTCHETT, PITRE & McCARTHY, LLP 
 
By:  /s/ Brian Danitz 
 
 
 
JOSEPH W. COTCHETT  
BRIAN DANITZ  
KARIN B. SWOPE  
BLAIR V. KITTLE 
VASTI S. MONTIEL 
CAROLINE A. YUEN 
REGINA WANG 
 
 
Dated: January 8, 2026  
ALTSHULER BERZON LLP 
 
By:  /s/ Michael Rubin  
 
 
 
 
 
 
  
 
MICHAEL RUBIN  
STACEY M. LEYTON  
CONNIE K. CHAN 
 
 
 
 
 
 
JAMES BALTZER 
 
 
 
 
 
 
KATHERINE BASS 
 
 
Co-Lead Counsel for Plaintiffs and  
the Class   
 
 
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SIGNATURE ATTESTATION 
Pursuant to section 2(f)(4) of the Electronic Case Filing Administrative Policies and 
Procedures Manual, I, Brian Danitz, attest that the other signatories listed, and on whose 
behalf this filing is submitted, concur in the filing content and have authorized this filing. 
 
Dated: January 8, 2026  
 
 
/s/ Brian Danitz 
 
 
BRIAN DANITZ 
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