TD bank case study - Business Finance
Please Answer the Following Questions regarding the Case Study. :1. Identify the main Data and Business Intelligence issues that plagued TD Bank Groups new Chief Data Officer.2. Prioritize the issues you identified, and suggest how the CDO should address them. Please be certain follow APA citation guidelines. Your response should be 750-1000 words, not including references.
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TD BANK GROUP: BUILDING AN EFFECTIVE ENTERPRISE DATA
MANAGEMENT POLICY
Murat Kristal, Glenda Crisp, Connie Bonello, and Katherine Heighington wrote this case solely to provide material for class discussion.
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Version: 2018-03-14
In October 2015, Glenda Crisp stepped into her new office on the 17th floor of TD Bank Group’s
headquarters. Crisp was the new chief data officer (CDO). She had moved from the 5th floor, where she
had been the corporate technology chief intelligence officer at the bank for the past four years. In her new
role, Crisp knew she needed to assess, validate, and deliver on promises made by her predecessor. Her main
focus was to move the theoretical ideas into tangible results.
Crisp saw issues in a variety of areas, such as organizational structure, the processes used to manage data
governance practices, and technology—all of which needed to be identified, prioritized, and then acted
upon. In order to be efficient in her implementation, Crisp made it her mission to set deliverable results for
each month, but she needed to determine what to prioritize and address first.
BACKGROUND
The Toronto-Dominion Bank and its subsidiaries, collectively known as TD Bank Group (TD), was one of
the top five big banks in Canada and was often ranked as number one or two in terms of total assets,
deposits, and market capitalization. The bank was created in 1955 when the Bank of Toronto and the
Dominion Bank merged, subsequently declaring its arrival with a new, high-profile head office that marked
Toronto’s skyline with what was then the tallest building in Canada.1
In 2002, TD started to expand into the United States, leading to significant and continual growth. The
market cap increased from CA$18.2 billion2 in 2002 to $103.5 billion by 2016. The bank more than doubled
its business locations, initially 1,328 branches in 2016, by adding many new locations along the east coast
of the United States, primarily in the northeast and in Florida. TD focused its expansion into the United
States on the retail banking industry, growing through acquisitions of smaller American banks. As a result
of the expansion, TD would also more than double its number of employees, growing from 42,817
employees in 2002 to over 85,000 in 2016.
1
“From the Beginning,” Toronto-Dominion Bank, accessed December 4, 2017, www.td.com/about-tdbfg/corporateinformation/tds-history/from-the-beginning.jsp.
2
All dollar amounts are in CA$ unless otherwise indicated.
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9B18E007
In 2015, TD Bank Group announced a seventh consecutive year of record adjusted earnings ($8.8 billion),
which was driven by TD’s strong performance in retail businesses and good results in the wholesale
segment. TD also had positive shareholder returns in fiscal 2015, which made it one of two Canadian banks
to achieve this result. TD had strong growth in operations, financial positions, share value, and financial
ratios (see Exhibit 1).3
IDENTIFYING THE NEED FOR A DATA TRANSFORMATION PROGRAM
Prior to embarking on its data transformation program in 2013, TD, like many large organizations, faced
some key data challenges. It had well-established policies, processes, and controls covering privacy and the
security of data, but the emerging hypothesis within the bank was that more could be done to meet growing
customer expectations that the bank use the data available to enhance and add value to the customer’s
experience and relationship with the bank.
In order to gain a deeper understanding of its data challenges, TD conducted interviews with over 200 of
its key business and technology leaders. Several key themes emerged from these interviews. While data
was managed primarily at the business level, the data quality processes, goals, and governance needed to
be formalized at an enterprise level. Also at an enterprise level, TD could enhance its ability to identify data
sources and trace the flow of data. This was particularly relevant because data usually needed to be extracted
from multiple systems to gain insight that was valuable. Finally, keeping analytics within each business
line and dispersing reporting among several teams and systems resulted in inefficiencies and ineffective
data management.
These challenges created operational inefficiencies and resulted in underutilized employee capabilities. The
business implications and the ever-growing amount of data warranted the need for TD to embark on a data
transformation program. TD needed to examine the way it managed and governed its data to realize its full
business benefit. The data transformation journey required TD to develop an enterprise data strategy, build a
team of people to govern and oversee the data, design and implement data standards and policies, and implement
processes and tools to monitor and enforce the data management policies and overall governance of its data.
TD was the first of the five major banks in Canada to establish a CDO role, created at TD in 2013. The
CDO was responsible for enterprise-wide data governance and the use of information as an asset. The CDO
was also responsible for driving enterprise innovation, transformation, and market-facing competitive
advantage through the combination of data and analytics. As a member of the senior management team at
TD, the CDO was able to monitor and to contribute to the strategic priorities of the organization. This
helped to align the enterprise data strategy with business priorities, and ensure that the data implications of
these priorities were understood and considered when prioritizing the key business initiatives.
Upon joining TD in 2013, the previous CDO established the Office of the Chief Data Officer (OCDO) with
a presence both in Canada—in Toronto, Ontario— and in the United States—in Mount Laurel, New Jersey.
The OCDO worked with multiple lines of business across the bank to establish data governance policies
and ensure that the departments adhered to these policies and regulations.
The first task was to develop the enterprise data strategy; establish data stewardship roles within the lines
of business; and pilot the data issue, change, and quality management processes. These activities were
critical to establishing the foundation for the management and governance of enterprise data. TD enlisted
3
TD Bank Group, Building the Even Better Bank: 2015 Annual Report, 3, accessed August 27, 2017,
www.td.com/document/PDF/ar2015/ar2015-Complete-Report.pdf.
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external analytical and technical expertise from a variety of consulting firms. Throughout the data
transformation journey, IBM had been a key partner in implementing the applications and doing the related
process work (see Exhibit 2).
Executive sponsorship and commitment to the data transformation program were important to ensure
resources were committed and expectations managed. In addition to appointing a CDO, TD also engaged
senior executives from each line of business as an “executive data sponsor” to ensure that the lines of business
data strategies were aligned with the enterprise data strategy and policy. The executive data sponsor role was
to provide funding, drive data governance and quality, escalate issues, and appoint data stewards.
COMPETITORS
Many organizations were drowning in a sea of data but were unable to leverage this data for business
insight. Banks, in particular, were dealing with increasing amounts of available data as mobile and online
services increased the amount of personalized data collected from customers. The question was how to
capitalize on the potential value in the data. Data underpinned every transaction, operation, and interaction
in an organization, but the ability to extract the power and value of the data and convert it into real actionable
business insight remained elusive to many organizations. TD was determined to be an industry leader with
its analytical capabilities and technological developments.
Deloitte Touche Tohmatsu Limited (Deloitte) evaluated the banks across Canada and the United States,
looking at their data management and analytical capabilities by breaking them down into six areas: (1) data
governance evaluated how the bank owned and managed data across the organization, including how it
controlled access to the data; (2) data management evaluated how effectively the bank managed master
data, the quality of the data, and metadata; (3) data acquisition measured the bank’s ability to acquire data
from multiple sources and how efficiently it did this; (4) data preparation assessed how the bank prepared
data from multiple sources and what formats it used for consolidation; (5) data consumption looked at the
bank’s ability to use the data to reveal insights; and (6) data analytics evaluated the business value the bank
gained from its data analytics.
According to Deloitte, TD was developing its ability to govern, manage, and acquire data, but it was in the
infancy stage of its ability to prepare, consume, and measure the data. TD had yet to develop mature
capabilities in any of the six functions. While TD was ahead or on par with the majority of Canadian banks,
the assessment concluded that it fell behind its American competitors.
REGULATION REQUIREMENTS
Other challenges that TD faced were the risk management regulations involving data management, such as
the Basel Committee on Banking Supervision’s regulation number 239 (BCBS-239).4 The Basel Committee
was an international risk management committee that issued international regulations and guidelines for
financial institutions. BCBS-239 was issued in 2013 to address risk involving data aggregation and
reporting. The regulation consisted of 14 principles that spanned four main topics: overarching governance
and infrastructure, risk data aggregation capabilities, supervisory review, and tools and co-operation (see
4
Basel Committee on Banking Supervision, “Principles for Effective Risk Data Aggregation and Risk Reporting,” Regulation
239 (2013), accessed December 4, 2017, www.bis.org/publ/bcbs239.pdf.
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Exhibit 3).5 The Canadian Office of the Superintendent of Financial Institution required that all Canadian
banks adhere to the regulation and its principles by 2017.
More urgently, because TD had such a large presence in the United States, Crisp was anticipating that U.S.
regulators would review TD’s plans to meet the new regulations imposed in the United States by the DoddFrank reforms.6 The Dodd-Frank Wall Street Reform and Consumer Protection Act was signed into
American federal law in August 2010 as a response to the 2008 financial crisis. One component of the
reform imposed regulations on data record keeping and reporting requirements.7
REDEFINING EMPLOYEE ROLES AND RESPONSIBILITIES
Before Crisp accepted the role as CDO, the position had been vacant for nine months. The extended period
without a leader had left the department fragmented and without direction. Many of the team members were
focused on other goals and priorities, which affected the cohesiveness of the department. Being a seasoned
executive, Crisp recognized that successful data transformation was going to require input from all
stakeholders. She needed to bring her team members together, and bring them together with other
stakeholders across the different lines of business to modify and implement an effective data strategy.
One method that TD used to ensure that data management was consistent across the large organization was
to designate data stewards. TD had over 300 data stewards among the lines of business. They “lived the
issues” and played a critical role in executing TD’s data governance and management standards and in
realizing project delivery outcomes. They were responsible for identifying critical data elements, managing
data issues and data changes across their line of business, and executing the data quality standards.
To ensure success, the data stewards needed to be accountable for and committed to resolving data issues, willing
to drive measurable results, have the appropriate level of involvement, and understand that data was a valuable
corporate asset. To progress with data transformation, the data stewards needed to have clearly defined
responsibilities and accountabilities, an essential set of capabilities, and a data-driven culture that allowed them
to make the right impact. Success also depended on having the right processes and tools to enable these
professionals to manage, care, protect, and govern enterprise data successfully as an enterprise asset.
Initially, when the first CDO assumed the role, data stewards had other duties in their lines of business and
typically spent only 25 per cent of their time on data governance and data management. And because the
CDO position had been vacant for nine months, some departments had shifted what resources had been
committed to data governance and management to other tasks. Thus, when Crisp started implementing new
policies, the data stewards’ workload drastically increased.
To ensure a consistent approach across the lines of business, policy now required certain processes for data
management. Among the changes, data quality processes were required to be completed on an annual basis.
Data impact assessments were also required of all large projects across the bank to provide evidence that
the projects aligned with the enterprise data strategy. The new policy implementations and the increasing
number of data-related projects placed more demands on the data stewards, who were providing expertise
5
Bank for International Settlements, “Summary of the Principles,” Annex 2 in Basel Committee on Banking Supervision:
Principles for Effective Risk Data Aggregation and Risk Reporting (report, 2013), accessed December 4, 2017,
www.bis.org/publ/bcbs239.pdf.
6
Dodd-Frank Wall Street Reform and Consumer Protection Act, Pub. L. No. 111-203, H.R. 4173, 111th Congress, accessed
December 5, 2017, www.sec.gov/about/laws/wallstreetreform-cpa.pdf.
7
“Final Rules, Guidance, Exemptive Orders, and Other Actions,” U.S. Commodity Futures Trading Commission, May 31,
2016, accessed March 12, 2017, www.cftc.gov/LawRegulation/DoddFrankAct/Dodd-FrankFinalRules/2016-12612.
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and assistance. As their roles and responsibilities expanded, Crisp knew she needed to find a way to address
their increasing workload. The challenge, however, was that none of the data stewards reported directly to
the CDO; rather, they reported to the manager in their specific line of business.
RESTRUCTURING OF TD’S DATA CAPABILITIES
In 2015, TD launched wide-scale restructuring, which included the enterprise data capabilities and resulted
in Crisp having to establish new types of relationships with changed departments. She also had difficulties
collecting the data necessary for the key performance indicators. For example, the prior CDO’s mandate
had included an advanced analytics department; however, with restructuring, the advanced analytics
department had been realigned under marketing (see Exhibit 4). Also, the enterprise analytics department
changed the metrics for reporting data. The consequence was the OCDO did not have access to the proper
data and metadata, which meant it could not properly measure the key performance indicators.
Because the role of CDO was fairly new in all organizations, the position lacked consistently defined
responsibilities. Crisp therefore needed to work continuously with other executives to differentiate what fell
under her domain from what fell under theirs. For example, data life cycle management, which included
current records retention, could fall under the domains of the chief risk officer, chief information officer, chief
operating officer, general counsel, or the CDO. Crisp recognized that TD’s data life cycle management policy
needed updating to reduce costs and risks associated with keeping files and data longer than necessary. And
although Deloitte had recommended that the responsibility fall under the domain of the CDO, Crisp was
unsure if she should take on the task or, for that matter, how her fellow executives would react if she did.
SIMPLIFYING PROCESSES
Before Crisp stepped into the CDO position, she made a point of meeting with the executive data sponsors
across the lines of business to see what needed to be addressed. The primary piece of advice she received
was to be more direct and concise with policy and how it was documented to ensure the lines of business
would adopt the processes.
The OCDO was responsible for producing the enterprise data governance policies, standards, and processes.
These policies provided a common approach across the organization for effective data management. TD
had implemented a number of common processes, programs, and tools to enable a consistent approach to
data governance and management. These included a data issue and change governance process, data quality
management process, and a data impact assessment for projects. The data issue and change governance
process ensured a single, consistent approach to manage and govern data issues and changes across all
business lines. The data quality and management process assessed the quality of critical data elements
across the enterprise, and the data impact assessment for projects ensured the projects aligned with the
enterprise data strategy. It also assisted the data stewards in assessing typical areas of challenge in projects.
When Crisp evaluated the original data quality process document, she noted that it was 141 pages long,
including 46 steps. She saw what the executive data sponsors were referring to and noted areas where the
document could be more concise and streamlined.
Crisp could engage IBM for a full-day “Design Thinking” workshop, which would lead some experienced
data stewards through exercises to help them simplify the data quality management process. Crisp needed
to determine if that was the best approach to streamlining the documentation, or if she should use only
internal expertise.
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TECHNOLOGY
Another of the CDO’s important responsibilities was to determine the correct and effective technology to
use. Technology and tools were important enablers for driving data quality, traceability, lineage,
monitoring, and accountability. TD took both a “build your own” approach and a licensed solution approach
for tools to manage its data. For example, TD chose to build its own data issue and change governance tool,
which was an enterprise repository of all data issues and proposed data changes. ...
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