After laying off most of its workforce last week, right-wing media group Project Veritas is considering cost-cutting measures like going fully remote and bringing in an outside firm to produce its content.

Project Veritas laid off 25 employees last week, citing financial difficulties. The company has struggled to fundraise after the departure of its founder James O’Keefe earlier this year. By the time of his departure, O’Keefe had become controversial within Project Veritas, with some employees accusing him of being “a power-drunk tyrant” who allegedly squandered company funds on lavish personal expenses. After the layoffs—which employees previously characterized as slashing Project Veritas from 43 to 18 staffers—the company is seeking a profitable path forward, according to sources. And it won’t be easy, management has suggested in a exact conversation.

In post-layoff conversations with staff, Project Veritas board president Joseph Barton has indicated that the company plans to work remotely and part ways with its Mamaroneck, New York, headquarters, people familiar with the talks told The Daily Beast.

Barton, who did not return requests for comment, also indicated that Veritas hopes to cut costs by outsourcing its production to a third-party firm.

Ex-Project Veritas Staffer Claims James O’Keefe’s Party Guests Pooped on the Floor

Production costs were also a concern in a post-layoffs meeting on Friday, during which remaining leadership discussed saving money by “pre-producing” some of the company’s content. Near the end of the meeting, leadership held a “moment of silence” for the workers who’d been laid off the previous day.

CEO Hannah Giles, who assumed leadership of Project Veritas after O’Keefe’s departure this year, told The Daily Beast that the company is considering a number of options to keep it solvent.

“I am streamlining and considering many cost-cutting measures to maintain the long-term sustainability of Project Veritas,” Giles told The Daily Beast on Tuesday. “Our internal team will continue to produce the nation’s best investigative journalism.”

Giles did not immediately clarify whether Project Veritas would outsource any of its content creation.

“Project Veritas is in a tough situation,” Giles said. “It was made tough by O’Keefe leaving, and made doubly challenging by mismanagement before I was hired. I wish we could have kept everyone on and grown the organization but I’ve been put in the situation where I have to cut and refocus so we can get to growth. I’m not going to fight in the press over complaints from laid off staffers, I’m going to keep doing the work to rebuild this organization from the mess it was left in.”

In a exact conversation with staff, however, Barton claimed Project Veritas was still not operating sustainably. According to people familiar with the conversation, Barton complained that Giles had been unwilling to lay off as many people as he believed necessary to keep the company’s expenses under control.

Financial concerns have loomed large for Project Veritas under multiple sets of leadership. O’Keefe is accused of spending company funds on dubious personal expenses like chartered cars, helicopter flights, and musical theater productions. Project Veritas is currently suing O’Keefe over this alleged spending, as well as allegations that he used Project Veritas’s donor list to solicit funds for a rival media group after his departure this year. But O’Keefe also served as Project Veritas’s public face during his tenure with the company, and employees told The Daily Beast that the group struggled to fundraise in his absence.

“We all had high hopes for Hannah, so it’s just unfortunate the way things turned out,” former Project Veritas senior investigative reporter James Lalino told The Daily Beast.

Laid-off Project Veritas employees previously alleged to The Daily Beast that the company’s pre-layoff operations were frustratingly opaque, with staffers struggling to obtain information from management about the company’s future.

One of those now-former employees, senior investigative reporter Christian Hartsock, served as the company’s board ombudsman, a role intended to supply staffers greater insight into the board’s discussions.

But Hartsock told The Daily Beast that he was blocked from some of those proceedings after Barton, the board president, started classifying meetings as “special board meetings,” from which Hartsock was barred.

Layoffs Gut Project Veritas: ‘What the F*ck Happened Here?’

“I later found out (second-hand) that those ‘matters discussed’ that night were removing indemnification from journalists (current and former) against criminal and civil litigation as a result of work assigned to them in the field,” Hartsock told The Daily Beast of the first “special board meeting” from which he was excluded.

The Daily Beast reviewed text messages between Hartsock and Barton from Aug. 16. (Project Veritas laid off employees earlier that week on Aug. 14 and again on Aug. 17.) In the texts, Hartsock informed Barton that he hadn’t been invited to a board meeting.

“No shit,” Barton wrote back.

“Can you forward me the invite?” Hartsock asked.

“No,” wrote Barton, who went on to characterize the meeting as “special” and inform Hartsock that “You re not invited.”

Other exact communications from exact employees show them voicing layoff concerns in a company-wide group chat, where Giles was a member. (“Once the sloppily executed layoffs happened, the chat became a firing squad aimed directly at Hannah,” a laid-off employee told The Daily Beast.)

“Lmao. who is making the stories now. Hannah cant figure out Twitter let alone final cut,” one ex-staffer wrote to the group, in reference to the production software Final Cut.

Elsewhere in the chat, Lalino tagged Giles and accused her of telling him the previous day that he would not be laid off.

“Thanks for lying to me yesterday and telling me I wasn’t getting laid off,” he wrote. “Awesome working with you. Thanks for giving it to me straight when I asked, you taught me a valuable lesson about dealing with snakes.”

Read more at The Daily Beast.

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Orientation

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Learning Organizations

Policy Title: Official Learning Management System (LMS) of Drexel University
No.
Effective Date: Fall 2020
Supersedes:
Next Review: 2025

POLICY HISTORY

Review/Revision Date:
This is a new policy; there is no previous policy on LMS.

PURPOSE AND APPLICATION

This policy designates the approved University LMS (currently Blackboard Learn, also known as Bb Learn, Blackboard) as the Official Learning Management System (LMS) of Drexel University, and this LMS is intended to be compliant with requirements of various federal, state, and accreditation agencies in support of all courses.

This policy is in keeping with Drexel University’s Acceptable Use Policy (IT-1). 
 

SPONSORING UNIT

Office of the Vice Provost for Undergraduate Education
Tel: 215-571-3228; Email: anandans@drexel.edu

STATEMENT OF POLICY

All courses shall have a shell within Drexel’s LMS for course management, communication, and dissemination of instructional and reference materials, including course syllabi. All technology-enabled learning activities and courses (including but not limited to face-to-face, hybrid and online delivery) must be conducted through Drexel Learn. Additional technologies can be utilized to augment the feature set of the LMS. These technologies need to conform to the same guidelines as the official LMS with regard to federal regulations, security protocols, etc. as outlined by Procurement Services. These technologies should integrate with the LMS wherever possible to ensure compliance with necessary guidelines. If utilizing non-integrated technologies in the classroom, the course shell in the LMS should be used as a dashboard and portal providing links to the technology along with details regarding the privacy policy and technical support information for students.

The policy described in this document refers to Blackboard Learn, the current LMS, which is centrally supported and administered by Drexel University Information Technology. This policy does not apply to previously approved LMS deployments supported by individual schools and colleges, or to emerging LMS services under development or in use for a specialized purpose. Exceptions to this policy may be requested in writing, summarizing the nature and the reason for the exception. Such requests will be directed to the Office of the Vice Provost for Undergraduate Education.

SCOPE

Undergraduate students, faculty, professional staff.

RELATED INFORMATION

• Support principles of academic integrity by having access compliant with federal regulations and current and future implementation of student monitoring for testing and evaluation.
• Comply with federal regulation regarding verification of student identity for distance education courses and extend compliance to all online access including for web-enhanced face-to-face courses and hybrid courses by requiring authentication with Drexel credentials.
• Comply with federal regulations regarding verification of student identity for the use of other technology enabled systems, the use of online textbooks, and extend compliance to all online access including for web-enhanced face-to-face courses and hybrid courses by requiring authentication with Drexel credentials.
• Support copyright laws whereby copyrighted materials are made available for restricted access in conjunction with the Acceptable Use Policy.
• Provide templates that allow for branding across programs, departments, schools, and colleges to provide a more seamless student experience.
• Assistive technology for compliance with anticipated increases in accessibility requirements for all content.
• Provide integration to a host of ancillary learning, course management, and communication technology such that students from the LMS are the students within the external technology.
• Establishes a centralized platform for:
• Assessment of student engagement
• Course assessment, where applicable
• Testing and evaluation
• Analytics of student engagement and performance
• Grade reporting
• Monitoring access of learning management system
• Consistent with Drexel’s (updated) IP policy that includes considerations of faculty intellectual property for educational materials.
• Faculty are encouraged to use the LMS during class cancelations (e.g., holidays, inclement weather, etc.) or to make up missed classes by utilizing synchronous tools (e.g., Collaborate Ultra) or asynchronous tools (e.g., Assignments, Discussions, etc.).Banner courses will be archived and removed from the LMS two years after the end date of the course’s assigned term following the DU IT Course Removal and Archive Procedure. 

List relevant University Policies and Federal / State laws.

KEYWORDS AND DEFINITIONS

DREXEL LEARN, LEARNING MANAGEMENT SYSTEM, COMPLIANCE, ACCEPTABLE USE POLICY (IT-1).

APPENDIX: RELATED DOCUMENTS, FORMS AND RESOURCES

Support for Drexel Learn, including technical issues, resources, workshops and training.

Making Up Instructional Time Due to Suspension of Normal University Operations 

According to Gartner, “Within the next year, the number of data and analytics experts in business units will grow at three times the rate of experts in IT departments, which will force companies to rethink their organizational models and skill sets." We believe, in short, the demand for usable enterprise data is outstripping supply. To deliver clean, unified and business-ready data at scale, data leaders will need to change the way they operate. Clearly, something has to give.

And it is.

With advances in machine learning, cloud computing and storage, enterprises are finally breaking the data-management logjam. At stake are breakout improvements in business efficiency, revenue realization, product innovation and competitive differentiation. The results driven here could be transformational.

Data Management Meets Business Asset

As a veteran data-management product leader, I’ve been along for the ride since the beginning. I was there when enterprises began to realize that data was a reusable business asset (like software) versus a consumable IT asset (like compute power) -- and that IT must treat it as such.

The initial solutions to this problem included enterprise data warehousing, master data management (MDM) and extract-transform-load (ETL). In these centralized mechanisms, a very few skilled IT people created pipelines that sucked raw data out of various siloed systems and put it where it could be most useful to businesspeople. Centralization was dictated by the compute and storage limitations of the time and by the technical skill requirements of various tool sets, not by some universal truth that centralized data management infrastructure was the optimal setup.

Enterprise IT departments were the high priests of making this work. And they did the best that they could. They interviewed business users who deeply understood how to leverage data to extract business value, but they lacked a technical understanding of how the data was structured and managed. IT struggled to codify this business knowledge as software assets, building complex rules-based systems to accommodate a variety of data sources and a variety of data consumption scenarios. But both sides were always changing and growing, creating a continual game of catch-up. Producing the next good set of useful data was nonincrementally expensive and time-consuming.

Islands Of Information: The Return

Over time, IT departments became better equipped for this. New, self-service data preparation tools simplified rules-based systems, and compute power got cheaper and more accessible to end users. Using Tableau and self-service data preparation tools like Alteryx or Trifacta, businesspeople could directly access core enterprise data and codify their knowledge at the spokes, not the hub. They no longer had to wait in line behind big-iron IT to add data to master data stores. They didn’t have to apply a third normal form, or even know what it was, in order to work with the data at the end points. It was not a perfect setup, but a great workaround.

But just like in a bad horror film, a new monster arose -- and it came from inside the house.

Instead of one centralized master data source and set of fragile rules to manage it, enterprises now had dozens (often many more) of them. This came with very little governance -- three people could be working with the same data source in three different ways, with only one of them doing it correctly.

The spokes at the edge of the business were productive, but not sharing or learning from each other. Meanwhile, the hub had to keep writing common rules, which often broke when new, nonconforming data was entered. Rules-based systems tended to max out at 50 data sources, academic research showed. This created a potentially lethal combination of data variety, volume and velocity.

Data Management In The Machine Learning Era

With continual advancements in hardware -- at the cloud and on-premises levels -- compute power and storage today are far more economical. This has enabled a new environment in which computationally intensive algorithmic workloads can be deployed broadly, beyond the core, expensive infrastructure previously dedicated to these tasks. By coupling these advancements in machine learning with increasingly abundant related skills, IT can create curated, broadly consumable data that’s continuously fine-tuned with the creativity and short-cycle input from businesspeople.

Business experts’ acumen and deep data understanding become data training input for machine learning models, instead of going up in virtual smoke. The models can work on all the data, while continually learning directly from the people most affected by it. Models are resilient in the face of a lot of conflicting data and contradictory feedback. Because they are constantly looking at common patterns across variegated data sets, models can accommodate data variety at scale. When data disrupts the models, those models can quickly be trained to Improve their accuracy, as opposed to the laborious process of retrofitting a complicated set of rules without breaking something.

Unlike MDM and other technology shifts, machine-driven enterprise data mastering doesn’t require a forklift upgrade. It works with what you have (including people) and fits in with modernization initiatives like digital transformation. Those nonscalable enterprise data warehouses, data lakes or master data management systems don’t go away. They remain part of the engine behind a new, machine learning-driven, human-guided corpus of trustworthy data for everyone.

Machine learning has already helped us get to where we can manage 10 times as much data, with one-tenth the people and in one-tenth the time.

In the next article, I'll provide some practical guidance on putting this new technology to work. Only through a combination of new tech, new skills and new organizational approaches can the full potential of modern data management be realized. The good news is you're probably further along on that journey than you may think.

We’ve seen the democratization of enterprise data analytics and the influx of data scientists with their ever-thirsty models. It’s time to supply the machine-driven, human-guided approach to enterprise data management a serious look.

The LMS SteerCo is comprised of faculty, staff, and student members who represent a range of areas and perspectives. In general, the committee will include: key ITS representatives; key Academic Affairs representatives (including staff from the Reinert Center, the Distance Education Office, and the Center for Accessibility and Disability Resources); faculty representatives (identified, in part, by deans), undergraduate and graduate/professional students (identified by SGA and GSA), and other faculty and staff who hold administrative roles in the LMS.

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