Analyze this: How data is reshaping the in-house role

By Jennifer Lewington December 18, 201618 December 2016

Analyze this: How data is reshaping the in-house role


In 2014, Charles McCarragher and his legal team at TD Bank Group faced a problem familiar to in-house counsel: too much work and not enough people to do it. 

More staff, in his view, was not the answer. “Adding lanes to the highway is not the way you solve rush-hour traffic,” says Mr. McCarragher, Assistant Vice-President Legal (Technology), especially without a quantitative explanation for “we’re busy.” Instead, he turned to data analytics—the business of mining internal and external company information to drive decisions—a strategy gaining ground with in-house counsel as they look to manage growing demand for legal services and add value to an organization’s bottom line. 

“There is a high level of acknowledgement that data analytics is central to the discharge of a general counsel’s mandate,” says Deloitte Partner David Stewart, co-author of the consulting company’s annual General Counsel Report. “The question is, ‘Are they happy with where they are today and do they feel they are optimizing the data and tools to their full advantage?’ A lot of people would say there is a lot of room for improvement.”

At TD, the need to rethink contract review procedures came to a head in 2014. 

With the quantity of work “increasing year over year,” McCarragher’s five-person team spent about 75% of their time on high-risk legal matters—the equivalent of 10-20% of work volume on an annual basis. Only 20% of the time was left for low-to-medium risk issues that accounted for 80-90% of the volume and still required scrutiny. 

Rather than hire more in-house lawyers, he used data to approximate the annual workload of one lawyer on staff, including the quantity, type and risk levels associated with the portfolio. That information fueled a discussion with external law firms on alternate resource models for some of the legal work.

In 2015, a hybrid model took shape. 

Working with McCarthy Tétrault LLP, a long-time strategic partner of the bank, and Exigent Group Ltd., a global provider of legal process outsourcing services, the Canadian TD legal commercial contracts team gathered internal data to analyze and conduct a triage of incoming work. Assisted by its two external partners, TD developed precedents, playbooks and resources guides to ensure that commercial contracts serviced through the model met internal bank procedures and legal department standards, according to McCarragher. 

McCarthy lawyers, aided by Exigent where appropriate, now handle the bank’s medium-risk contracts, becoming a proxy for TD’s in-house lawyers for the fundamental file work. As well, McCarthy and Exigent apply technology, processes and reporting to track certain commercial contract provisions identified by the bank. 

McCarragher describes the new model as a cost-effective, efficient and scalable resource that generates a rich source of data on contracts and gives TD an “effective and prudent way” to service lower-risk work and keep high-priority assignments in-house.

“Enabling the model was fundamentally based on the data that TD had been collecting for the past three years,” he says. “Without the data, it would have been very difficult to understand the opportunity and to ultimately devise a resourcing model to allow members on the legal team to focus on what really mattered for the bank.” 

Beyond workflow, patterns of information provide in-house counsel with material for evidence-based discussions about corporate strategy. 

“They [general counsel] can go in a quantitative way and talk about risk in the organization,” says Matthew Peters, Partner and National Innovation Leader at McCarthy, which provides data analytics support and services. Previously, he adds, “they would talk about it more anecdotally; now they can do so with much more authority because of the data behind it.”

As organizations explore the “untapped treasure trove” of information at hand, Peters urges close attention to protection of privacy. “Confidentiality, privilege and privacy are incredibly important and they have to be thought through before you do anything,” he cautions.

Also important, say industry experts, is the skill to ask the right questions about data and communicate with management about the findings. 

“For in-house counsel, it is incumbent on them if they want to be part of the business process and be seen as successfully contributing to the business that they talk the same language as the rest of the business,” says Exigent CEO David Holme. 

Data analytics, he adds, is not “the end in itself” but one part of an overall strategy by in-house counsel and other company experts equipped to capitalize on the use of algorithms. “The truth lies in this ensemble of expertise that uses the tools available,” he says. “That is where the magic lies.”

For some companies, data analytics assists in compliance. Isabelle Pierre, Deputy General Counsel and Director of Legal at General Dynamics Lands Systems Canada in London, Ont., says her department examines data to test existing compliance controls.

“Early detection is the biggest benefit,” she says. “If you can catch a problem or a weakness in your system before it becomes a real problem, it allows you stay on top of your compliance program and be on top of your game.” With any change in business activities and risk levels, she adds, “it allows you to see if your processes are still adequate.”

Getting a grip on data can also generate efficiencies with bottom-line impact. That’s the experience of Paula Pepin, Global Head of Legal at Hootsuite, a Vancouver-based technology company that has shot to global prominence for its widely-used platform to manage social media. 

Her department supports Hootsuite’s enterprise sales team, managing hundreds of legal negotiations with major customers every quarter. Hootsuite recently implemented a new tool allowing legal reviews to be submitted through, a customer relationship management platform. Requests for contract reviews are now submitted through the platform to Hootsuite lawyers who perform a triage based on the complexity of a deal, relevant deadlines and the time required for a response. 

“It really helps them prioritize their workflow,” she says. Data on the volume and risk level of contracts, and lawyer response time feeds into her department’s quarterly performance reports. That information, in turn, becomes the basis for an evidence-driven discussion on staffing.

“My discussion with the chief financial officer is not ‘we are busy, I need somebody else.’ It is that if you want us to reach that revenue number, I need an extra resource. If not, we will be a bottleneck.”

Earlier this year, with an eye to boosting productivity, Pepin wanted to identify potential distractions for her eight-member legal team. A quarterly report on departmental activities revealed that a high volume of queries took less than an hour of a lawyer’s time. “It’s what I call the ‘noise’—the small stuff—that interrupts you from your priorities,” she says.

In response, her department introduced “office hours” for small-scale requests, leading to a 50% drop in the volume by the third quarter of this year. “Instead of sending 15 emails a week, they come and see us between 8 a.m. and 10 a.m. on Tuesday morning and we hash through all of their requests,” she says.

Last year, Pepin introduced time-tracking to identify issues handled by her team, with a view to better allocate client assignments. The analysis showed that several lawyers spent at least 15% of their time on HR matters—the equivalent of more than 150% of a full-time headcount. That information created a business case to add a dedicated employment lawyer, freeing other lawyers to focus on the top legal priorities.

A member of Hootsuite’s executive leadership, Pepin says data analytics is transforming the role of the general counsel. “The traditional key performance indicator of the legal department has always been satisfaction and service levels. It doesn’t cut it these days,” she says.

Elsewhere, data analytics can frame an organization’s strategy in labour negotiations. 

As Chief Negotiator, HR Services at McMaster University, Geoff Tierney oversees bargaining with faculty, support staff and other unionized employees at the Hamilton, Ont., post-secondary institution. 

“Before we even get to the [bargaining] table, we use data analytics to create a compensation mandate using a whole set of factors internally and externally,” he says, such as salary ranges for comparable unionized workers in the region or at other universities. McMaster has customized a Microsoft Excel spreadsheet to track an array of line-item costs, from vacation pay and taxes to salaries and workers’ compensation payments. 

“Everything is data-based driven now; we cost everything,” he says. “If I don’t know what it costs, I don’t propose it.” 

For now, some in-house counsel are feeling their way on data analytics. 

“We are trying to integrate more into some aspects of our internal practice,” says Matthew Hawkins, Vice-President, Legal Counsel and Corporate Secretary at Colliers International Group Inc., but describes the effort as still “in its infancy.” Still, he sees potential to harness data to improve his department’s ability to communicate about risk management and apply the knowledge to “right-size” resources (such as differentiating between low- and high-priority legal tasks). 

TD’s McCarragher praises the unheralded contribution of analytics to a positive work environment, ensuring the most important, professionally challenging assignments remain in-house. With a deeper understanding of workflow and the life cycle of a typical transaction, McCarragher and his team can identify inefficiencies in the contracting process and de-bunk the stereotype of the legal department as a the bottleneck. 

“I have a general motto with the team: for them, I want this to be the best place to work on Bay Street,” he says. “One way to get to that goal is to make sure you have the right balance of working on the right things.”

Jennifer Lewington is a writer based in Stratford, Ontario. This article was initially published in the Winter 2016 issue of CCCA Magazine

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