Memo of Points and Authorities — Bofa Ca Unemployment (Dkt. 564.1)

Record facts

U.S. District Court for the Southern District of California · No. 3:21-md-02992-GPC-MSB · Doc. 564-1 · 2025-10-17 · Docket on CourtListener

Summary

A memorandum of points and authorities filed October 17, 2025 as Document 564-1 by defendant Bank of America, N.A. in In re: Bank of America California Unemployment Benefits Litigation, Case No. 21-MD-02992-GPC-MSB, in the U.S. District Court for the Southern District of California. It supports a motion to exclude the opinions of a call center consultant the plaintiffs proffer for their Customer Service Class damages inputs, arguing under FED. R. EVID. 702 that his industry standard, avoided cost, WFM model and state of mind opinions are unreliable or improper. The memorandum states that the benchmark rests on two figures from a 2021 ContactBabel survey, a 75-second average speed to answer and a 6.1% abandonment rate, whose underlying data the consultant did not review. It requests oral argument and notes a hearing set for April 17, 2026. The filing is 32 pages.

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BANA’S MEM. ISO MOT. TO EXCLUDE MINNUCCI 
CASE NO. 21-MD-02992-GPC-MSB            
 
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JAMES W. MCGARRY (pro hac vice) 
JMcGarry@goodwinlaw.com 
GOODWIN PROCTER LLP 
100 Northern Avenue 
Boston, MA  02210 
Tel.: +1 617 570 1000 
Fax: +1 617 523 1231 
SABRINA M. ROSE-SMITH (pro hac vice) 
SRoseSmith@goodwinlaw.com 
MATTHEW L. RIFFEE (pro hac vice) 
MRiffee@goodwinlaw.com 
GOODWIN PROCTER LLP 
1900 N Street, NW 
Washington, DC 20036 
Tel.: +1 202 346 4000 
Fax: +1 202 346 4444 
Attorneys for Defendant  
BANK OF AMERICA, N.A. 
[ADDITIONAL COUNSEL LISTED IN SIGNATURE BLOCK] 
 
UNITED STATES DISTRICT COURT 
FOR THE SOUTHERN DISTRICT OF CALIFORNIA  
SAN DIEGO DIVISION 
IN RE: BANK OF AMERICA 
CALIFORNIA UNEMPLOYMENT 
BENEFITS LITIGATION 
Case No. 21-MD-02992-GPC-MSB 
DEFENDANT BANK OF 
AMERICA, N.A.’S 
MEMORANDUM OF POINTS AND 
AUTHORITIES IN SUPPORT OF 
MOTION TO EXCLUDE 
PURPORTED EXPERT OPINIONS 
OF JAY MINNUCCI 
   
Date: 
April 17, 2026 
Time: 
1:30 p.m. 
Ctrm: 
12A – 12th Floor 
Judge: 
Hon. Gonzalo P. Curiel 
 
ORAL ARGUMENT REQUESTED 
 
FILED PROVISIONALLY UNDER SEAL 
PURSUANT TO STIPULATED PROTECTIVE 
ORDER 
 
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TABLE OF CONTENTS 
Page 
INTRODUCTION. .................................................................................................... 1 
BACKGROUND ....................................................................................................... 2 
I. 
BANA’s Claims Call Center ........................................................................... 2 
II. 
Plaintiffs’ Customer Service Claims ............................................................... 3 
III. 
Minnucci’s Inadmissible Damages Inputs and Opinions ................................ 3 
IV. 
Minnucci’s Other Inadmissible Opinions ....................................................... 7 
STANDARD OF LAW ............................................................................................. 8 
ARGUMENT ............................................................................................................. 9 
I. 
Minnucci’s Damages Inputs and Calculations Must Be Excluded. .............. 10 
A. 
Minnucci’s industry standard opinion should be excluded. ............... 10 
B. 
Minnucci’s use of aggregate call center data is unreliable. ................ 15 
II. 
Minnucci’s Avoided Cost Opinions Are Unreliable. .................................... 16 
A. 
Minnucci’s distinct caller demand calculations are unreliable. .......... 17 
B. 
Minnucci’s avoided workload calculations are unreliable. ................ 19 
C. 
Minnucci’s idle hour charges calculations are unreliable. .................. 20 
III. 
Minnucci’s WFM Model Opinions Are Uninformed And Unhelpful. ......... 22 
IV. 
Minnucci’s State of Mind Opinions Are Improper. ...................................... 24 
CONCLUSION. ....................................................................................................... 25 
 
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TABLE OF AUTHORITIES 
 
Page(s) 
Cases 
A.B. v. Cnty. of San Diego, 
2020 WL 4431982 (S.D. Cal. July 31, 2020) ..................................................... 24 
Aya Healthcare Servs., Inc. v. AMN Healthcare, Inc., 
613 F. Supp. 3d 1308 (S.D. Cal. 2020) .............................................................. 24 
Bakst v. Cmty. Mem’l Health Sys., Inc., 
2011 WL 13214315 (C.D. Cal. Mar. 7, 2011) ................................................... 22 
Brighton Collectibles, Inc. v. RK Tex. Leather Mfg., 
923 F. Supp. 2d 1245 (S.D. Cal. 2013) (Curiel, J.) .................................... 8, 9, 23 
Cholakyan v. Mercedes-Benz USA, LLC, 
281 F.R.D. 534 (C.D. Cal. 2012) ....................................................................... 18 
Claar v. Burlington N. R. Co., 
29 F.3d 499 (9th Cir. 1994) .......................................................................... 14, 16 
Daubert v. Merrell Dow Pharms., Inc., 
509 U.S. 579 (1993) ....................................................................................... 8, 20 
Daubert v. Merrell Dow Pharms, Inc. (Daubert II), 
43 F.3d 1311 (9th Cir. 1995) .......................................................................... 9, 21 
Domingo v. T.K., 
289 F.3d 600 (9th Cir. 2002) ................................................................................ 8 
Faust v. Comcast Cable Commc’ns Mgmt., LLC, 
2014 WL 3534008 (D. Md. July 15, 2014) .................................................. 13, 14 
Gold v. Lumber Liquidators, Inc., 
323 F.R.D. 280 (N.D. Cal. 2017) ....................................................................... 25 
Goodness Films, LLC v. TV One, LLC, 
2014 WL 12780291 (C.D. Cal. May 19, 2014) ...................................... 12, 15, 18 
Griffo v. Oculus VR, Inc., 
2018 WL 6265067 (C.D. Cal. Sept. 18, 2018) ................................................... 12 
In re Incretin-Based Therapies Prods. Liab. Litig., 
524 F. Supp. 3d (9th Cir. 2022) .................................................................... 12, 24 
JMJ Enters., Inc. v. Via Veneto Italian Ice, Inc., 
1998 WL 175888 (E.D. Pa. Apr. 15, 1998)  ...................................................... 17 
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Kawasaki Jukogyo Kabushiki Kaisha v. Rorze Corp., 
2025 WL 1407350 (N.D. Cal. May 12, 2025) ................................................... 25 
Kim v. Benihana, Inc., 
2024 WL 3550390 (C.D. Cal. May 20, 2024) .................................................... 19 
Kumho Tire Co. v. Carmichael, 
526 U.S. 137 (1999) ..................................................................................... 12, 20 
Legendary Art, LLC v. Godard, 
2012 WL 3550040 (E.D. Pa. Aug. 17, 2012) ..................................................... 18 
In re Live Concert Antitrust Litig., 
863 F. Supp. 2d 966 (C.D. Cal. 2012) ................................................................ 19 
Lloyd v. Conseco Fin. Corp., 
2001 WL 36097624 (C.D. Cal. Oct. 19, 2001) ...................................... 16, 19, 20 
Loeffel Steel Prods., Inc. v. Delta Brands, Inc., 
387 F. Supp. 2d 794 (N.D. Ill. 2005), amended, 2005 WL 8178971 
(N.D. Ill. Sept. 8, 2005) ...................................................................................... 18 
Malletier v. Dooney & Bourke, Inc., 
525 F. Supp. 2d 558 (S.D.N.Y. 2007) ................................................................ 17 
McCoy v. DePuy Orthopaedics, Inc., 
2024 WL 1705952 (S.D. Cal. Apr. 19, 2024) ........................................ 10, 11, 18 
McMorrow v. Mondelez Int’l, Inc., 
2020 WL 1157191 (S.D. Cal. Mar. 9, 2020) ...................................................... 20 
Multimedia Pat. Tr. v. Apple Inc., 
2012 WL 5873711 (S.D. Cal. Nov. 20, 2012) ................................. 12, 13, 14, 15 
Payan v. Los Angeles Cmty. Coll. Dist., 
2019 WL 8163479 (C.D. Cal. June 13, 2019) .................................................... 22 
Remien v. EMC Corp., 
2008 WL 597439 (N.D. Ill. Mar. 3, 2008) ......................................................... 15 
Robinson v. G.D. Searle & Co., 
286 F. Supp. 2d 1216 (N.D. Cal. 2003) .............................................................. 23 
Rodman v. Otsuka Am. Pharm., Inc., 
564 F. Supp. 3d 879 (N.D. Cal. 2020), aff’d 2021 WL 5850914 (9th 
Cir. Dec. 9, 2021) ......................................................................................... 12, 14 
Rosenfeld v. JPMorgan Chase Bank, N.A., 
732 F. Supp. 2d 952 (N.D. Cal. 2010) .................................................................. 3 
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Sabicer v. Ford Motor Co., 
362 F. Supp. 3d 837 (C.D. Cal. 2019) .................................................................. 3 
Stephens v. Union Pac. R.R. Co., 
935 F.3d 852 (9th Cir. 2019) .............................................................................. 10 
United States v. Rushing, 
388 F.3d 1153 (8th Cir. 2004) ............................................................................ 22 
Rules 
FED. R. EVID. 702 ................................................................................................. 8, 17 
 
 
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Plaintiffs cannot survive summary judgment without producing evidence of 
actual damages incurred by themselves and their classes. To help shoulder that 
burden for their Customer Service Class, they rely on the opinions of Jay Minnucci, 
an independent consultant in the call center industry. See ECF 494 at 97. Minnucci 
is not designated as a damages expert, nor is he qualified to serve as one, so his report 
does not calculate damages outright. Instead, Minnucci proposes and generates inputs 
for Plaintiffs’ Customer Service Class damages calculation.  
Specifically, Minnucci claims that a third-party survey of unspecified call 
centers in different industries spanning periods before the COVID-19 pandemic and 
after the class period should serve as the “industry standard” and performance 
benchmark for Bank of America (BANA)’s Claims Call Center. He does so even 
though BANA’s call center indisputably experienced a 
 
, 
while the call demand decreased or remained flat for many survey participants.  
Minnucci further opines that BANA’s Claims Call Center’s performance, and 
the Customer Service Class’s purported damages, should be measured based on that 
metric and the average call wait times for the Claims Call Center even though (1) 
Minnucci has never seen the underlying data for the survey, (2) Minnucci does not 
know how those call centers and the circumstances they faced compared to BANA’s, 
(3) the wait times varied among class members, and (4) 
 
. Having no knowledge of the data underlying 
the survey or its averages, Minnucci is in no position to opine that they reflect 
industry standards or appropriate benchmarks, much less damages for the class. Thus, 
his opinions, and any damages calculations relying on them, must be excluded as 
unreliable and irrelevant.   
To the extent Minnucci purports to calculate BANA’s purported cost savings, 
those opinions also must be excluded because they improperly rely on the survey as 
the “industry average and benchmark” and 
 
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 rendering it unreliable and inflated. The 
opinions also must be excluded because they rely on undisclosed, decades-old data, 
that Minnucci did not verify, from a handful of clients in other industries, and because 
they apply a formula (Erlang-C) for which the underlying assumptions are 
inapplicable here.   
To the extent Minnucci opines that 
 
 
 
 his opinion and assumptions should be excluded 
because they are refuted by the record and his own testimony. Further, they should 
be excluded because his suggestion that 
 
 is at odds with his own experience and forecasting activities of 
his clients. Finally, to the extent Minnucci seeks to opine on BANA’s intent, those 
opinions are improper and must be excluded under well-established law.  
BACKGROUND 
I. 
BANA’s Claims Call Center 
During the COVID-19 pandemic, BANA call centers performed three 
functions: 
 
 
 
 
 HX1 10 at 14. 
 
 HX 11A. 
By contrast, 
 
. Id. 
 
 
 See id. 
 
 
1 Exhibits to the Declaration of Lindsay E. Hoyle shall be referred to as “HX.” 
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. Id. These 
efforts were complicated as call center agents transitioned to work-from-home, 
 
. HX 12 . Further 
complicating matters, many state and local governments shut down, 
 
 HX 13 at 273:7–19. 
 
 
 See HX 14 .  
II. 
Plaintiffs’ Customer Service Claims  
Plaintiffs assert that they received UI benefits from EDD via prepaid cards 
issued by BANA, and that they experienced unauthorized transactions on their cards. 
ECF 406 (TAMCC) at 2; ECF 324-1 at 1. Plaintiffs allege, among other things and 
with the benefit of hindsight, that BANA failed to provide “reasonable and adequate 
customer service” to certain callers by deliberately understaffing the Claims Call 
Center to achieve cost savings and “forcing” callers “to wait for hours on hold” 
causing “significant foreseeable harm.” See TAMCC ¶ 582(d)(i)(E). They further 
allege that BANA could “forecast customer service call volume and adequately staff 
its call centers” yet did not do so. Id. They allege on behalf of the Customer Service 
Class that these actions were negligent and breached an implied covenant of good 
faith and fair dealing. TAMCC ¶¶ 585–593; 619–624. Both causes of action, among 
other things, require Plaintiffs to prove damages resulting from the purported 
misconduct.2   
III. 
Minnucci’s Inadmissible Damages Inputs and Opinions 
In support of their Customer Service claims, Plaintiffs proffer Minnucci as an 
 
2 See Sabicer v. Ford Motor Co., 362 F. Supp. 3d 837, 840 (C.D. Cal. 2019) 
(negligence claim requires damages); Rosenfeld v. JPMorgan Chase Bank, N.A., 732 
F. Supp. 2d 952, 968 (N.D. Cal. 2010) (good faith and fair dealing requires showing 
that “plaintiff was harmed by the defendant's conduct”). 
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expert in the call center industry where he has been a consultant since 2000. HX 11 
¶ 8. Plaintiffs rely on Minnucci to provide the inputs for their damages calculations. 
Specifically, they rely on his opinions that (1) virtually all EDD prepaid cardholders 
who had their calls routed to the Claims Call Center during the class period waited 
 
 (id. ¶ 107); (2) “[t]he total number of excess 
hours” that class members waited to speak to a Claims Call Center agent can be 
calculated by multiplying 
 by the number of calls class members made 
to the Claims Call Center during the class period (id.); and (3) understaffing the 
Claims Call Center allowed BANA to avoid 
 
 which it would have had to incur if it 
had provided “industry standard” service (id., Tables 10, 11; see id. ¶ 17). 
For his “industry standard” opinion, Minnucci relies entirely on two data 
points as the building blocks for Plaintiffs’ damages inputs: a 75-second average 
speed to answer (“ASA”) and a 6.1% abandonment rate. Id. ¶¶ 12, 14. He sources 
these figures from the 2021 iteration of an annual publication by ContactBabel 
designed to “study[] the performance, operations, technology and HR aspects of US 
contact center operations” using survey responses from certain call centers. HX 15 at 
13. Minnucci opines that the survey averages are “industry-standard performance 
benchmarks” for “all call centers, including specialty call centers like” the Claims 
Call Center. HX 11 ¶ 42; see id. ¶¶ 40, 49. Minnucci offers this opinion despite the 
fact that: (1) he did not review the data on which the averages are based (HX 16 at 
220:16–19); (2) he does not know who the survey respondents are, what type of call 
centers or services they offered, or whether their data included multiple or aggregated 
call centers (id. at 205:3–15, 205:23–206:4, 220:16–19, 221:3–18); (3) he does not 
know whether any respondent experienced call volumes spikes or fraud attacks 
similar to BANA’s (see id. at 220:11–18, 222:14–223:1); and (4) he does not even 
know what specific timeframe the respondents used to compile their data (id. at 
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222:2-11).  
For his “excess hours” opinion, Minnucci takes the purported “industry 
average” ASA from the ContactBabel survey and subtracts it from the ASA for all 
individuals who called the Claims Call Center during the class period. HX 11 ¶ 107. 
He does so even though he admits that the 
 HX 16 at 398:1-18. Further, he agrees that 
some class members would have experienced shorter wait times depending on when 
they called. Id. at 139:22-140:2. And he admits that he does not know if or the extent 
to which the experience of an individual, or the class as a whole, differed from the 
aggregate average. Id. at 135:8-136:4. Plaintiffs then take Minnucci’s excess hours 
opinion and propose that they would multiply it by (1) the number of calls made by 
Customer Service Class members and (2) the minimum wage even though each caller 
was collecting UI benefits (and therefore claiming to be unemployed and not earning 
wages at the time). See ECF 324-1 at 39–40. 
For his “avoided workload” opinion, Minnucci claims he can estimate the 
total workload avoided costs from BANA’s alleged understaffing by estimating the 
number of agents and related costs that would have been needed to achieve the 
ContactBabel “industry standard” 75-second ASA and 6.1% abandonment rate. HX 
11 ¶¶ 109-111. To do so, he first attempts to estimate the amount of distinct caller 
demand in the Claims Call Center using unproduced data from “probably about eight 
clients.” HX 16 at 408:16-17; see HX 11 ¶ 110 & Table 9. Minnucci claims these 
clients included members of the property and casualty industry, health insurance 
clients, utilities, and a membership organization, and says that the data was collected 
over a six-to-eight year period beginning in 2005. See HX 16 at 411:21-413:1. 
Minnucci uses his clients’ data to develop a regression formula that purports to 
calculate an expected recall percentage for abandoned calls based on call 
abandonment percentages. See HX 11 ¶ 110, Table 9 & App’x H. He then applies 
that formula to BANA’s 
 which includes 
 
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 to estimate the number of 
callers to the Claims Call Center who abandoned their calls and did not call back in 
an effort to remove duplicates who may have called and abandoned their calls 
multiple times. See HX 11 Table 9 & App’x H. Next he adds this estimate to the 
number of answered calls to compute the total distinct caller demand. Id. Table 9.  
Finally, to estimate workload charges avoided, he multiplies his distinct caller 
demand calculations by 93.9% (based on the ContactBabel 6.1% abandonment rate), 
and then multiplies that figure by BANA’s average call length to calculate the 
number of paid workload hours required to achieve a purported industry standard 
rate. Id. Table 10. From this figure he 
 
 
 Id. Minnucci admits this 
calculation, which relies on 
, does not 
reflect workload charges solely attributable to the class. See HX 16 at 449:11–21. 
For his “avoided idle charge” opinion, Minnucci claims he can estimate 
avoided costs associated with times between calls when call center agents are waiting 
to service new customers. To do so, Minnucci apportions his distinct caller demand 
figures across 30-minute intervals using call distribution percentages experienced by 
some of his consulting clients that he describes as having a “majority West Coast 
calling base.” See HX 11 App’x I.3 He next uses a formula, Erlang-C, to generate a 
retroactive estimate of the staffing requirements for the Claims Call Center during 
each interval necessary for BANA to achieve the ContactBabel 75-second ASA. Id. 
¶ 113 & Table 11. He does so even though he admits that Erlang-C is not typically 
used in this fashion as it is typically used for forecasting (not ex post modeling), and 
even though its key assumptions were not actually present at the Claims Call Center 
during the class period. See HX 16 at 438:1-9. 
 
3 Minnucci’s Report does not provide any other information about his clients, or 
indicate when this data was collected or compiled, or whether it reflects call 
percentages during the class period. 
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Minnucci then subtracts the number of minutes he claims would need to be 
staffed from the number of minutes he claims agents would have spent answering 
calls and divides the result by 60 to compute idle hours. HX 11 ¶ 113, App’x I & 
Table 11. He then 
 
. Id. Table 11. 
Like his workload charges calculation, this calculation uses 
 
and therefore does not reflect avoided costs solely attributable to 
class members. HX 16 at 449:23–450:7. 
IV. 
Minnucci’s Other Inadmissible Opinions 
Minnucci opines that 
 
 
. HX 11 ¶¶ 63–65. In 
support, he points to 
 
 
 
 
 Id. ¶ 64. Minnucci further surmises, in hindsight, that because 
 
 
 
 
 Id. ¶ 65. Minnucci makes these claims despite the fact that his 
own analysis showed a 
 
. HX 16 at 288:12–20. He further concedes 
that he cannot recall ever forecasting call volumes in this way. Id. at 291:21–292:14. 
Nor has he ever attempted to 
 
 
 
 See id. at 292:5–14; HX 11 ¶ 61. 
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Finally, based on his selective review of the record, Minnucci opines that 
 
 HX 11 ¶ 81; see 
also id. ¶¶ 15, 51, 58–61, 63, 66, 69–70, 74, 78, 82, 101. To do so, Minnucci relies 
on 
 
 See HX 17 at 14:20–16:19, 
20:25–21:6. He concedes that he did not review her testimony or the testimony of the 
individual who allegedly understaffed the call center prior to issuing his report. See 
HX 16 at 145:9–146:3, 357:17–358:18. 
STANDARD OF LAW 
Federal Rule of Evidence 702 and Daubert v. Merrell Dow Pharms., Inc., 509 
U.S. 579 (1993), “impose[] a special ‘gatekeeping obligation’ on trial judges” 
presented with expert testimony. Brighton Collectibles, Inc. v. RK Tex. Leather Mfg., 
923 F. Supp. 2d 1245, 1253 (S.D. Cal. 2013) (Curiel, J.). Under Rule 702, a witness 
proffered as an expert must satisfy the following requirements: 
(a) 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; (b) 
the testimony is based on sufficient facts or data; (c) the testimony is the 
product of reliable principles and methods; and (d) the expert has reliably 
applied the principles and methods to the facts of the case. 
Under Daubert, district courts must “carefully apply[] Federal Rule of Evidence 702 
to ensure that specialized and technical evidence is ‘not only relevant, but reliable.’” 
Brighton Collectibles, 923 F. Supp. 2d at 1253. The reliability standard tests: 
(1) whether the scientific theory or technique can (and has been) be tested; (2) 
whether the theory or technique has been subjected to peer review and 
publication; (3) whether there is a known or potential error rate; and (4) 
whether the theory or technique is generally accepted in the relevant scientific 
community. 
Domingo v. T.K., 289 F.3d 600, 605 (9th Cir. 2002). In addition, “[o]ne very 
significant fact to be considered is whether the experts are proposing to testify about 
matters growing naturally and directly out of research they have conducted 
independent of the litigation, or whether they have developed their opinions 
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expressly for purposes of testifying.” Daubert v. Merrell Dow Pharms, Inc. (Daubert 
II), 43 F.3d 1311, 1317 (9th Cir. 1995). 
“[T]he burden of proving the expert’s testimony satisfies Rule 702” and the 
Daubert standard rests on the Plaintiffs, as “[t]he proponent of the evidence.” 
Brighton Collectibles, 923 F. Supp. 2d at 1253. 
ARGUMENT 
None of the opinions discussed above passes muster under Fed. R. Evid. 702 
or Daubert. As set forth below, Minnucci has no basis to opine that the ContactBabel 
survey provides appropriate industry averages or performance benchmarks for the 
Claims Call Center during the class period, making his opinions—and the Customer 
Service damages and cost savings models that rely on ContactBabel to assess 
purported harm and cost savings—unreliable. Minnucci’s opinions and Plaintiffs’ 
calculations of Customer Service Class “harm” and “cost savings” are also unreliable 
and irrelevant because they rely on 
. Thus, they cannot serve 
as a reliable measure of any purported harm or cost savings for the Customer Service 
Class or any individual class member. Minnucci’s purported “cost savings” measures 
are further unreliable and irrelevant because they rely on (1) cherry-picked data (that 
he did not check for accuracy) from eight unidentified clients from decades before 
the class period, and (2) a formula whose assumptions were not met during the class 
period and that is not used in the industry to assess staffing or measure damages ex 
post. For each and all of these reasons, Minnucci’s damages inputs and any related 
opinions must be excluded and cannot serve as evidence in support of Plaintiffs’ 
Customer Service Class damages claims. 
As for Minnucci’s opinion that BANA could and should have used the 
 
 the opinion is unreliable and 
irrelevant because it is contradicted by the record, his own forecasting experience, 
and the practice of his consulting clients. And to the extent Minnucci repeatedly 
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attempts to offer an opinion as to BANA’s intent or state of mind, those opinions 
must be excluded because they are not proper bases for expert opinion.   
I. 
Minnucci’s Damages Inputs and Calculations Must Be Excluded.  
A. 
Minnucci’s industry standard opinion should be excluded.  
Minnucci opines that 
 
 
 
 HX 11 ¶¶ 12, 107. Further, he opines that the average industry abandonment 
rate was 6.1%. Id. ¶¶ 14, 40. He derives both averages from a 2021 report issued by 
ContactBabel, which surveyed call centers from various industries providing various 
services and levels of customer support over periods that include time before the 
pandemic and after the class period ended in November 21, 2020. Id. ¶ 12 n.1; HX 
16 at 208:7–14. Plaintiffs then use Minnucci’s opinion, and the survey specifically, 
to calculate damages for the Customer Service Class by subtracting the “industry 
average” from the aggregate average wait for callers to the Claims Call Center during 
the class period, and multiplying it by the minimum wage in California. See ECF 
324-1 at 39–40.4 Minnucci’s opinion, and any damages calculations based on them, 
must be excluded for at least three reasons.  
First, Minnucci’s opinions must be excluded because they are conclusory, 
speculative, and not based on any analysis of the data from which ContactBabel’s 
averages were derived. An “expert’s opinion must rest on ‘facts or data in the case 
that the expert has been made aware of or personally observed,’ not merely 
assumptions and speculation.” Stephens v. Union Pac. R.R. Co., 935 F.3d 852, 856 
(9th Cir. 2019) (quoting Fed. R. Evid. 703); see also McCoy v. DePuy Orthopaedics, 
Inc., 2024 WL 1705952, *11 (S.D. Cal. Apr. 19, 2024) (excluding expert opinion 
where expert “simply parrot[ed] the opinions of other experts . . . without conducting 
 
4 As discussed above and further below, Minnucci also improperly relies on the 
ContactBabel abandonment average to estimate avoided costs. Supra at 5-6; infra 16.  
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an independent investigation of the underlying evidence.”) (internal quotations 
omitted). Yet Minnucci concedes he did not review any of the data on which these 
numbers are based. See HX 16 at 220:16–19. Nor does he know “how each individual 
call center responded” to ContactBabel’s questionnaire, or who the respondents are 
or “what . . . makes up their call center[s] and what different divisions and 
departments they may have.” Id. at 206:1–4, 220:16–19, 221:3–9. Nor does he know 
whether any respondent experienced a dramatic increase in call volumes in 2020 
similar to that experienced by the Claims Call Center (see id. at 220:11–19), which 
was experiencing a 
 
 See HX 11A. Nor does he know how many survey respondents were 
a 
, or whether any survey 
respondents provided general customer service or more complex services such as 
fraud claims processing. HX 16 at 220:21–221:18. Nor does he know whether any 
respondent experienced a 
 (id. at 
222:14–223:1), as the Claims Call Center did. See HX 18 ¶ 46; HX 19 at 60:23–61:9; 
HX 20 at -6783–84. And most basically, Minnucci does not even know what 
timeframe the respondents used to compile their data, or whether respondents with 
more than one call center provided aggregate data to ContactBabel. HX 16 at 222:2–
11.  
These admissions, and others, confirm that Minnucci has no basis to assert that 
the ContactBabel numbers are even accurate, much less that they constitute an 
appropriate “industry average” or performance benchmark for a call center facing 
similar facts and circumstances as BANA’s Claims Call Center during the class 
period. Thus, they must be excluded. See, e.g., McCoy, 2024 WL 1705952, *11 
(excluding expert opinion where expert conducted no “independent investigation of 
the underlying evidence”) (internal quotations omitted).5 
 
5 See also Griffo v. Oculus VR, Inc., 2018 WL 6265067, *6 (C.D. Cal. Sept. 18, 2018) 
(expert report failing to provide “facts underlying [a particular] calculation” 
inadmissible as “[t]he conclusions do not ‘rest[] on a reliable foundation.’”) (quoting 
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Second, Minnucci’s “industry average” and performance benchmark opinions 
also should be excluded because he concedes that neither he, nor any other industry 
participant, uses or relies on aggregate data across various industries or call center 
functions to set performance targets. Minnucci cites no source to show that other call 
center industry professionals use the ContactBabel survey averages as performance 
benchmarks. And at his deposition, Minnucci conceded that he does not even use 
them as such in his own consulting business. See HX 16 at 202:3–5. Rather, Minnucci 
testified that he relies on multi-industry averages to answer client questions about 
how a call center’s existing performance targets “compare to what others are doing,” 
not to set the targets in the first instance. See id. at 210:2–22. Thus, Minnucci has no 
basis to rely on the ContactBabel averages to set performance standards for BANA 
because that is not consistent with the industry’s use or “the practice of an expert in 
the relevant field.” Kumho Tire Co. v. Carmichael, 526 U.S. 137, 152 (1999); see 
also In re Incretin-Based Therapies Prods. Liab. Litig., 524 F. Supp. 3d, 1001, 1044 
(9th Cir. 2022) (excluding opinion due to “discrepancy between what [expert] 
endorses in this litigation and in the scientific community”). 
Third, Minnucci’s “industry average” and performance benchmarks should be 
excluded because what little Minnucci does know about the ContactBabel survey 
confirms that the respondents are not apt comparators for BANA’s Claims Call 
Center during the class period. See, e.g., Goodness Films, LLC v. TV One, LLC, 2014 
WL 12780291, *2–3 (C.D. Cal. May 19, 2014) (excluding damages opinion based 
on comparisons where experts failed to show comparators were sufficiently similar 
to be relevant); Multimedia Pat. Tr. v. Apple Inc., 2012 WL 5873711, *9 (S.D. Cal. 
Nov. 20, 2012) (excluding opinion based on “generic industry data [that] is not 
tethered to the relevant facts and circumstances of the present case”); Faust v. 
 
Daubert, 509 U.S. at 597); Rodman v. Otsuka Am. Pharm., Inc., 564 F. Supp. 3d 879, 
889–91 (N.D. Cal. 2020) (excluding opinion where expert “exceed[ed] the 
boundaries of the sources she relie[d] on by going beyond what the sources 
concluded”), aff’d 2021 WL 5850914 (9th Cir. Dec. 9, 2021). 
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Comcast Cable Commc’ns Mgmt., LLC, 2014 WL 3534008, *5 (D. Md. July 15, 
2014) (refusing to allow extrapolation of conclusions concerning employees working 
in one set of call centers to employees working in a different call center).  
Most basically, the ContactBabel survey includes periods of time outside the 
narrow class period (September 13, 2020 through November 21, 2020), including 
data from January and February 2020 (before the pandemic impacted U.S. call 
centers). See HX 16 at 208:7-14; HX 15 at 13. Minnucci does not explain how pre-
pandemic data could be relevant or serve as an appropriate yardstick against which 
to measure BANA’s performance during the class period (which was at the height of 
the pandemic). Nor could he, as it is widely acknowledged that the contact center 
industry experienced “enormous upheaval … as a result of the pandemic.” Id. at 34.6 
Minnucci conceded as much, admitting that the pandemic caused 
 
 HX 11 ¶ 59; 
HX 16 at 215:18–21. Because the circumstances call centers faced before and during 
the pandemic were vastly different, it is unreasonable for Minnucci to rely on 
ContactBabel’s ASA and call abandonment figures to define pandemic-era 
performance standards. See Multimedia, 2012 WL 5873711, *9; Faust, 2014 WL 
3534008, *8.  
Minnucci’s reliance on the ContactBabel survey is also unreliable and 
misplaced because, as stated in the report, its averages incorporate data from a 
significant number of respondents (approximately 40%) that experienced flat or 
decreased call volumes from March 2020 to November 2020. See HX 15 Fig. 2. 
 
 
 HX 11A. 
 
. Id. Minnucci does not, and 
 
6 See also Paul Stockford, “Automation Key to COVID-19 Contact Center Crisis” 
Contact Ctr. Pipeline (Mar. 25, 2020), https://blog.contactcenterpipeline.com 
/2020/03/automation-key-to-covid-19-contact-center-crisis/ 
(COVID 
“put 
the 
contact center industry in a manner of disarrayed motion the likes of which have 
never been seen before”). 
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industry as a whole, being higher than the overall average for all of the past nine 
years, and seeing major increases in the years of the pandemic” (id.). Despite this, 
Minnucci still opines that the lower, 75-second ASA was the appropriate average and 
benchmark. See HX 11 ¶ 107. This also requires exclusion of his opinions. See, e.g., 
Goodness Films, 2014 WL 12780291, *2–3; Multimedia, 2012 WL 5873711, *9.9  
B. 
Minnucci’s use of aggregate call center data is unreliable. 
Minnucci further opines that the Customer Service Class’s damages can be 
calculated based on the assumption that every class member experienced the average 
ASA irrespective of when they called. See HX 11 ¶ 107; HX 16 at 400:10–19. 
Relying on this assumption, Plaintiffs then propose to calculate damages for the 
Customer Service Class by multiplying the number of calls made by class members 
to the Claims Call Center during the class period by (1) 
 (the 
approximate difference between the ContactBabel industry average ASA and the 
average call wait time), and (2) the California minimum wage at the time. See 
generally ECF 324-1 at 39-40. Minnucci’s assumption, and any damages calculations 
based on them, also must be excluded because they are purely speculative and have 
no reliable basis in fact or the record.  
Minnucci concedes that not all callers to the Claims Call Center experienced 
the same wait times. See HX 16 at 135:8–16. Further, he acknowledges (as he must) 
that some callers waited less than the average amount. See id. Thus, he necessarily 
acknowledges that relying on the aggregate data and averages would overcompensate 
some Customer Service Class members (to the extent they are entitled to any 
compensation at all, which they are not).  
Additionally, Minnucci concedes that 
 
 
. 
 
9 See also Remien v. EMC Corp., 2008 WL 597439, *1 (N.D. Ill. Mar. 3, 2008) 
(striking opinion where expert “arbitrarily eliminate[d] relevant portions of data that 
could have been used to arrive at more complete and accurate assessments”). 
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Minnucci admits that he cannot distinguish the class members’ experience from any 
of these callers, or whether the class members’ experience was the same or similar 
or skewed by others included in this population. Id. at 135:18–136:23. And he did 
not review any individual caller data or call recordings to assess how the class 
members’ experiences compared to the average or to each other. Id.at 137:21–138:4; 
see also HX 11 App’x D. He simply throws his hands up and assumes for damages 
that they all experienced the average ASA. See HX 16 at 400:10–19. Such speculative 
and conclusory assumptions are not reliable expert opinion and must be excluded. 
See Claar, 29 F.3d at 502 (affirming exclusion of expert testimony because no 
evidence that the expert’s conclusions were “based on anything more than subjective 
belief and unsupported speculation”); Lloyd v. Conseco Fin. Corp., 2001 WL 
36097624, *6 (C.D. Cal. Oct. 19, 2001) (excluding expert opinion that “does not 
speak clearly and directly to the issue in dispute”) (citation modified). 
II. 
Minnucci’s Avoided Cost Opinions Are Unreliable. 
Minnucci’s avoided cost opinions also must be excluded for the reasons 
discussed above, as they too rely on ContactBabel and 
 
, rendering them unreliable 
and inflating the purported avoided costs. Supra Section I.A. Separately, and in 
addition, Minnucci’s avoided workload opinions must be excluded as unreliable 
because he relies on undisclosed data from unspecified clients from different 
industries during periods long before the pandemic, and he cannot explain how or 
why that data correlates to BANA’s Claims Call Center and the call volume spikes it 
experienced during the class period. HX 11 App’x H; HX 16 at 411:21–413:1. 
Similarly, Minnucci’s avoided idle time opinions also must be excluded because 
there is no basis for the use of Erlang-C to calculate call center demand or damages 
ex post, as he does to estimate avoided costs. Further, and in any event, Erlang-C is 
not a reliable methodology here because the record shows that its underlying 
assumptions were not present during the class period. 
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Each of these fatal defects warrants exclusion of Minnucci’s opinions. 
Moreover, even if the Court were to find that some of these flaws could be addressed 
on cross-examination, their cumulative effect would still justify exclusion. See 
Malletier v. Dooney & Bourke, Inc., 525 F. Supp. 2d 558, 570 (S.D.N.Y. 2007) 
(finding expert report and testimony unreliable “considering the cumulative effect of 
the numerous flaws identified”); see also JMJ Enters., Inc. v. Via Veneto Italian Ice, 
Inc., 1998 WL 175888, *9 (E.D. Pa. Apr. 15, 1998), (granting motion to disallow 
expert report where expert analysis suffered from methodological flaw and 
significant errors), aff’d, 178 F.3d 1279 (3d Cir. 1999). 
A. 
Minnucci’s distinct caller demand calculations are unreliable. 
Minnucci attempts to estimate the amount of distinct caller demand in the 
Claims Call Center—which he uses as an input to calculate BANA’s purported 
avoided costs (see supra at 5-6)—by using call data that has not been produced in 
this case that he says he obtained from his consulting clients. HX 16 407:17–23; see 
also HX 11 App’x H. Minnucci’s report provides no information about these clients 
or how their data was compiled. However, he subsequently testified that he obtained 
the data from “probably about eight clients” that included members of the property 
and casualty industry, health insurance clients, utilities, and a membership 
organization—no financial institutions. HX 16 408:16–17, 411:21–412:7. He further 
testified that the data was collected over a six-to-eight year period (beginning in 
2005), that the data covered single days (not a two-month period like the class 
period), and that he relied on his clients to determine their own recall rates. Id. at 
407:7–408:10, 412:17–413:1, 455:20–456:1. Minnucci’s reliance on his client’s data 
renders his caller demand estimate, as well as any purported avoided costs derived 
from it, unreliable for at least three reasons.  
First, the aggregated client data points Minnucci relies on to estimate distinct 
caller demand are unreliable and cannot be used for this purpose because none of the 
clients operated call centers in the same industry, much less the same time period (at 
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the height of the COVID-19 pandemic), as BANA’s Claims Call Center. It is well-
established that “[r]esearch begins with a clear formulation of a research question” 
and the “data to be collected and analyzed must relate directly to this question; 
otherwise, appropriate inferences cannot be drawn.”10 For this reason, courts hold 
that for a comparison “to have the requisite predictive capacity and the reliability 
Daubert demands,” the samples selected must be “truly comparable.” Loeffel Steel 
Prods., Inc. v. Delta Brands, Inc., 387 F. Supp. 2d 794, 812 (N.D. Ill. 2005), 
amended, 2005 WL 8178971 (N.D. Ill. Sept. 8, 2005) (internal quotation omitted); 
Goodness Films, 2014 WL 12780291, *2-3 (excluding opinion for failure to 
demonstrate comparators were sufficiently similar). Minnucci’s use of his 
undisclosed, non-financial industry clients’ data from 2005-2013 in no way satisfies 
this requirement. See supra at 5-6. 
Second, Minnucci relied on his clients to crunch their own data and provide 
him with recall statistics without verifying their work. See HX 16 407:17–23, 408:2–
5. This defect further renders his distinct demand calculation unreliable, as he did not 
and cannot verify the accuracy of the data on which his opinions rest. See McCoy, 
2024 WL 1705952, *11 (excluding testimony where report adopted conclusions 
reached by others without reviewing supporting documents); Cholakyan v. 
Mercedes-Benz USA, LLC, 281 F.R.D. 534, 546 (C.D. Cal. 2012) (excluding expert 
declarations because expert used reports prepared by others and “engaged in little, if 
any evaluation of their merits”); Legendary Art, LLC v. Godard, 2012 WL 3550040, 
*4 (E.D. Pa. Aug. 17, 2012) (expert’s reliance on figures generated by another 
“without independent verification, renders his analysis unreliable”). 
Third, Minnucci’s regression model fails to account for significant variables 
that likely impacted BANA’s recall rates that were not present in his clients’ data. 
Most obviously, BANA’s call center was impacted by the onset of the pandemic and 
 
10 Reference Manual on Scientific Evidence: Third Edition at 311 (Washington DC: 
The National Academies Press) available at https://doi.org.10.17226/13163 (the 
“Manual on Scientific Evidence”). 
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. See HX 11A; HX 18 ¶ 46; HX 19 60:25–
61:9; HX 20 . Minnucci cannot claim that any of his unspecified clients experienced 
such unprecedented challenges in the decades prior when the data was obtained. See 
HX 16 at 68:12–15, 115:22–116:12. This, again, renders his analysis both irrelevant 
and unreliable. See Kim v. Benihana, Inc., 2024 WL 3550390, *5 (C.D. Cal. May 20, 
2024) (finding “regression model should have controlled for several independent 
variables” but did not and therefore model was “unreliable and unhelpful to the trier 
of fact under Rule 702 and under Daubert); In re Live Concert Antitrust Litig., 863 
F. Supp. 2d 966, 975–76 (C.D. Cal. 2012) (excluding expert analysis that assumed 
disparity was attributable to defendant’s conduct alone and did not account for other 
explanations); Lloyd, 2001 WL 36097624, *6 (excluding opinion that “fails to 
account adequately for potentially explanatory variables”).  
For each and all of these reasons, Minnucci’s regression analysis and any 
related avoided cost opinions should be excluded as unreliable and irrelevant. 
B. 
Minnucci’s avoided workload calculations are unreliable. 
Minnucci’s computation of avoided workload charges is also flawed because 
it is not based on the number of avoided workload hours attributable to class 
members, and thus overestimates BANA’s purported avoided costs. To estimate 
BANA’s purported avoided workload costs, Minnucci takes the distinct caller 
demand he calculated based on his clients’ data (which must be excluded for the 
reasons discussed above, supra Section II.A) and multiplies the figure by the average 
call length for the Claims Call Center during the class period. HX 11 ¶ 111 & Table 
10. From this figure he subtracts the workload hours BANA actually incurred and 
multiplies the difference by the hourly rate BANA paid its vendors to compute total 
workload charges allegedly avoided. Id. Yet Minnucci admits that this avoided 
workload calculation relies on 
 
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. HX 16 449:11–21. 
Accordingly, Minnucci’s cost savings calculation does not and cannot measure the 
cost savings attributable to Customer Service Class members. Id. Further, Minnucci 
admits that using only class member data would decrease his cost savings calculation, 
but he has no way to disaggregate the data to determine what portion of the purported 
cost savings he attributes to the class members as opposed to other callers. Id. at 
451:20–452:4. This further counsels exclusion of Minnucci’s purported cost savings 
opinions. See McMorrow v. Mondelez Int’l, Inc., 2020 WL 1157191, *1 n.2 (S.D. 
Cal. Mar. 9, 2020) (excluding damages opinion because model “does not measure 
only the damages attributable to [plaintiffs’] liability theory”). 
C. 
Minnucci’s idle hour charges calculations are unreliable. 
Minnucci purports to calculate costs BANA may have avoided associated with 
“idle” call center agent hours. See HX 11 ¶¶ 112–113. To do so, he takes the distinct 
caller demand estimates, which must be excluded for the reasons discussed above, 
supra Section II.A, and applies a formula called “Erlang-C” to generate a retroactive 
estimate of BANA’s purported staffing requirements for the actual call volume 
necessary to achieve the purported ContactBabel “industry-standard” ASA. HX 11 ¶ 
113, Table 11. In addition to the reasons above (supra at 17-20), Minnucci’s avoided 
idle hour charge opinions must be excluded because his reliance on Erlang-C is 
unreliable and unsupported by the record. 
First, Minnucci’s reliance on Erlang-C is not consistent with the industry’s use 
or “the practice of an expert in the relevant field,” and therefore is unreliable. Kumho 
Tire, 526 U.S. at 152. As Daubert recognizes, scientific validity for one purpose does 
not automatically confer scientific validity for all purposes. See Daubert, 509 U.S. at 
591–92. Erlang-C is a mathematical equation that is sometimes used to predict the 
number of agents a call center may need to service a given number of calls while 
achieving a specific service level.11 But that is not how Minnucci uses it here; rather, 
 
11 
See 
Rahul 
Awati, 
Erlang 
C, 
Tech 
Target 
(Mar. 
3, 
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he applies Erlang-C post hoc to compute purported cost savings. See HX 11 ¶¶ 112–
13. Yet he and Plaintiffs have no “verifiable evidence” that could show that Erlang-
C has ever been used in this manner by the scientific community. Daubert, 43 F.3d 
at 1317-18. Absent such evidence—and the record contains none—his idle work 
hours calculation should be excluded. See Daubert II, 43 F.3d at 1316 (“objective, 
independent validation of the expert’s methodology” is required). 
Second, Minnucci’s idle hours cost savings calculation is unreliable because 
the assumptions built into the Erlang-C model run counter to the facts of this case. 
For example, Erlang-C assumes independent and random call arrivals (i.e., a 
“Poisson process”), but “doesn’t work if customer requests are not independent or 
triggered by a common event [like] natural disasters.”12 This makes Erlang-C 
particularly inappropriate to use during times when call volumes are spiking as a 
result of common causes like a pandemic, or 
 
—as was the case here. See supra at 2-3. 
Similarly, as Minnucci conceded at his deposition, Erlang-C “assumes infinite caller 
patience,” meaning a caller will stay on hold for as long as it takes to have her call 
answered. HX 16 at 442:14–17. But Minnucci admits that 
 
 
 HX 11 ¶¶ 
48, 109; HX 16 at 442:4–5. And as published studies have found, Erlang-C error rates 
are “highly correlated” with realized abandonment rates.13  
Erlang-C further assumes that all customer service representatives handling 
calls are “statistically identical” and equally skilled.14 HX 16 at 436:5–437:10. But 
 
https://www.techtarget.com/searchunifiedcommunications/definition/Erlang-C 
12 What is Erlang, and Why Does it Matter, cxtoday (Nov. 25, 2022) 
https://cxtoday.com/contact-center/what-is-erlang-and-why-does-it-matter/.  
13 Thomas R. Robbins, Evaluating the Performance of the Erlang Models for Call 
Centers, at 14, 24, https://myweb.ecu.edu/robbinst/PDFs/S-12130-TR.pdf; see also 
Thomas R. Robbins, D.J. Medeiros and Terry P. Harrison, Working Paper “Does the 
Erlang C Model Fit in Real Call Centers?” (2010) §§ 2, 4.3, 5. 
14 See Robbins, “Evaluating the Performance of the Erlang Models for Call Centers” 
at 4.  
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Minnucci admits this was not the case, and that more experienced agents are often 
able to handle calls more efficiently than newer agents. See id. at 437:12–15 
(testifying that representatives in “every call center” vary as to speed and level of 
performance). And regardless of skill, some calls and caller issues take longer to 
resolve than others, which Erlang-C also cannot account for.15 Thus, because the 
assumptions built into the Erlang-C model are hopelessly at odds with the actual 
facts, Minnucci’s idle hours cost savings calculation should be excluded. See Bakst 
v. Cmty. Mem’l Health Sys., Inc., 2011 WL 13214315, *20 (C.D. Cal. Mar. 7, 2011) 
(excluding damages calculation based on expert’s “factual assumptions that are 
entirely unsupported in the record”); United States v. Rushing, 388 F.3d 1153, 1156 
(8th Cir. 2004) (upholding exclusion where expert made “assumptions contrary to 
the established facts of the case”).  
III. 
Minnucci’s WFM Model Opinions Are Uninformed And Unhelpful.  
Minnucci opines that 
 
 See HX 11 ¶¶ 63–66. Specifically, 
Minnucci opines that 
 
 
 
 Id. ¶¶ 63–65. His opinion is based on a 
 
 
. See id. These 
opinions should also be excluded because they are contradicted by the record, 
Minnucci’s own professional practice, and the practices of his clients.  
As a threshold matter, Minnucci’s opinion is not supported by the record, and 
therefore is unreliable and irrelevant. See Payan v. Los Angeles Cmty. Coll. Dist., 
2019 WL 8163479, *3–4 (C.D. Cal. June 13, 2019) (excluding expert report based 
on factual assumptions contradicting the record as “entirely speculative . . . [and] 
 
15 See Robbins, supra note 14 at 4.  
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unhelpful to the jury”). 
 
 
 
See HX 23 Ex. 15; HX 11 ¶ 65; see also HX 24 ¶¶ 18(a)(ii), 42. Minnucci 
acknowledges this discrepancy, and concedes the model would be 
 
 HX 11 ¶ 65. 
Nevertheless, he opines—with the benefit of hindsight—that it could have been used 
to generate forecasts for the Claims Call Center that “would likely still meet industry 
standard accuracy rates.” Id. ¶ 65; HX 16 at 284:13–17. This is not reliable expert 
testimony. 
Indeed, Minnucci’s report cites no support for the proposition that 
 
 
 And the record 
shows it did not, as Minnucci admitted his own analysis revealed that 
 
 
 HX 16 at 288:7–13, 288:19–20. Further, and in any event, 
Minnucci does not explain exactly how the purported 
 would have 
permitted 
 
 
 See HX 11 ¶ 61 (accepting five-to-seven week lead time required for 
new agents). For each and all of these reasons, Minnucci’s characterization of the 
 is highly 
speculative, unsupported, and unreliable. See Brighton, 923 F. Supp. 2d at 1255 
(excluding opinion because “expert has not grounded his assumption with the real 
world facts of this case”); Robinson v. G.D. Searle & Co., 286 F. Supp. 2d 1216, 
1221 (N.D. Cal. 2003) (opinion “lacks sufficient factual basis as required . . . and is 
therefore inadmissible” where contradicted by record). 
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 Minnucci’s contention that 
 
 should also be 
excluded because it is contrary to his own experience and otherwise devoid of 
support. See U.S. Aviation Underwriters, 2024 WL 2948626, *25 (excluding expert 
testimony on this basis). Minnucci’s report cites nothing to indicate that single-
variable forecasting is an accepted industry practice, much less that it can and would 
have accurately achieved the results he says BANA’s call center should have 
achieved. Further, at his deposition, Minnucci testified that he could not recall a 
single instance in which he or anyone else generated staffing forecasts using a single 
variable. HX 16 at 291:21–292:4. He further conceded that planning staffing needs 
for his own clients during the pandemic was “not just simple forecasting,” but instead 
relied on “a lot of factors,” including “any factors that you can identify and quantify 
to be able to forecast.” Id. at 76:12–17, 242:11–15. Because Minnucci’s hindsight 
opinions are once again contrary to what he (and others) do in the field, they should 
be excluded. See In re Incretin-Based Therapies, 524 F. Supp. 3d at 1044 (excluding 
opinion due to “discrepancy between what [expert] endorses in this litigation and in 
the scientific community”). 
IV. 
Minnucci’s State of Mind Opinions Are Improper. 
It is well-established that, absent personal knowledge, an expert’s testimony 
on another’s “subjective state of mind and motives [is] impermissible.” A.B. v. Cnty. 
of San Diego, 2020 WL 4431982, *3 (S.D. Cal. July 31, 2020); Aya Healthcare 
Servs., Inc. v. AMN Healthcare, Inc., 613 F. Supp. 3d 1308, 1320–21 (S.D. Cal. 2020) 
(expert opinions on “intent, motives or states of mind . . . have no basis in any relevant 
body of knowledge or expertise”) (internal quotation omitted), aff’d, 9 F.4th 1102 
(9th Cir. 2021). Yet Minnucci repeatedly opines that BANA “deliberately” 
understaffed the Claims Call Center. E.g., HX 11 ¶¶ 15, 51, 59–61, 63, 66, 69, 70, 
74, 78, 81, 82, 101, 113. These are clearly improper expert opinions that must be 
excluded. E.g., Kawasaki Jukogyo Kabushiki Kaisha v. Rorze Corp., 2025 WL 
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GOODWIN PROCTER LLP 
100 Northern Avenue 
Boston, MA 02210 
Tel.: +1 617 570 1000 
Fax: + 1 617 523 1231 
LAURA G. BRYS (SBN 242100) 
LBrys@goodwinlaw.com 
GOODWIN PROCTER LLP 
601 S Figueroa St., Suite 4100 
Los Angeles, CA 90017 
Tel.: +1 213 426 2500 
Fax: +1 617 346 4444 
VALERIE A. HAGGANS (pro hac vice) 
VHaggans@goodwinlaw.com 
LINDSAY E. HOYLE (pro hac vice) 
LHoyle@goodwinlaw.com 
GOODWIN PROCTER LLP 
620 Eighth Avenue 
New York, NY 10018 
Tel: +1 212 813-8800 
Fax: +1 212 355-3333 
YVONNE W. CHAN (pro hac vice) 
YChan@jonesday.com 
JONES DAY 
100 High Street 
Boston, MA 02110 
Tel.: +1 617 960 3939 
Fax: +1 617 449 6999 
JANICE P. BROWN (SBN 114433) 
jbrown@myersnave.com 
MATTHEW B. NAZARETH (SBN 278405) 
mnazareth@myersnave.com 
MEYERS NAVE 
600 B Street, Suite 1650 
San Diego, CA 92101 
Attorneys for Defendant 
BANK OF AMERICA, N.A. 
 
 
 
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CERTIFICATE OF SERVICE 
I hereby certify that I electronically filed the foregoing with the clerk of the 
court for the United States District Court for the Southern District of California by 
using the CM/ECF system on October 17, 2025.  I further certify that all participants 
in the case are registered CM/ECF users and that service will be accomplished by the 
CM/ECF system. I certify under penalty of perjury that the foregoing is true and 
correct. 
 
 
Executed: 
October 17, 2025 
 
s/ Matthew L. Riffee 
 
 
 
 
 
 
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