Main Issues plaguing TD Bank Group’s New Chief Data Officer
The studied case study describes some of the issues and realities that TD Bank Group had to analyze and address if it was to maximize its competitive advantage from the use of data. In 2013, the position and role of a chief data officer (CDO) was established with the aim of transforming the process of enterprise-wide use and governance of data and make it a notable asset. The professional was also expected to drive innovation, foster competitive advantage, and transform the company using both analytics and data.
These attributes would also deliver strategic priorities that matched with the organization’s goals. Nonetheless, the bank’s chief data officer (CDO) had to consider and address a number of issues that plagued TD. For instance, the completed interviews indicated that the company’s “data quality processes, goals, and governance need to be formalized at the business level” (Kristal et al., 2018, p. 2). TD was yet to enhance its strategy for identifying sources and flow of data at its enterprise level.
The data team was also finding it hard to extract information from different systems with an effort of acquiring valuable insights. Each business segment was also required to keep data analytics and disperse reports. These scenarios contributed to ineffective management processes for data and inefficiencies. These issues led inefficiencies in operations and underutilization of workers’ capabilities (Kristal et al., 2018). A new wave of data transformation was needed to ensure that the company was able to achieve it business aims. A skilled team was essential to oversee and monitor the collected data. Additional designs and policies or standards for data were also essential.
With the increasing quantities of data from online services and mobile devices, many organizations were finding it hard “to extract the power and value of the data and convert it into real actionable business insight” (Kristal et al., 2018, p. 3). At TD, the move to develop a new model for data management was commendable. However, the organization was yet to develop effective capabilities in each of its business functions. Additionally, the Dodd-Frank led to a new law that imposed additional data regulations in the United States. Some of the key issues included the company’s ability to adhere to reporting and recordkeeping requirements.
The prolonged vacancy in the CDO office also left the IT department without a sense of direction. The stakeholders in the company were not providing their inputs to support this sense of transformation.
Prioritizing Issues and Solutions
The banking industry remains extremely competitive while new trends are recorded every single day. The collection and analysis of data are critical strategies needed to meet the demands of all key stakeholders and address the challenge of rivalry. The above section has identified some of the issues that the CDO needs to prioritize and address accordingly if the bank is to remain competitive. The first issue to consider was the acquisition of the right tools and frameworks to support and improve the organization’s enterprise data strategy. The second aspect to prioritize was the consideration of the emerging policies (Krahe et al., 2019). The third issue is to maximize the quantity of collected data and the desire to transform according to the changes recorded in the industry.
The CDO should consider several steps to simplify the complex process at the company to ensure that all workers adopt and follow it. The first step would be to identify the right person for the Office of the Chief Data Officer (OCDO) and recruit professionals to implement the best data strategy. The leader will also appoint new individuals to head departments and ensure that they align their data procedures with that of the company. The entire team will work collaboratively, engage stakeholders, and scan for changes in the business environment to ensure that timely results are realized.
Additionally, the CDO should consider the importance of collaborating with IBM for a “Design Thinking” workshop (Kristal et al., 2018). The approach is necessary since it will make it easier for the data leader to simplify the company’s data management approach. The procedure for analysis will be streamlined while at the same time supporting documentation. This model will make it possible for the company to reduce its data expenses while getting maximum benefits from the system.
Expanding Role of Data Stewards
The proposed changes have resulted in additional roles for data stewards. This new occurrence means that chances of resistance might be quite high while affecting the company’s performance. To handle this issue, the company’s CDO needs to redefine such roles and allow different stewards to focus on specific areas. For instance, some could be allowed to monitor the adoption and implementation of data polices while others would have to consider the effectiveness of the data collection procedures. To increase efficiency, the provision of relevance right tools and resources to such stewards would be necessary. The CDO should also be supportive, offer appropriate leadership, and help solve emerging problems. These initiatives are evidence-based and capable of guiding such stewards to manage and govern the company’s data efficiently (Kristal et al., 2018). On top of such considerations, the CDO should guide followers to complete data quality processes in a timely manner.
Data Lifecycle Management
The insights and facts gained from this case can dictate whether the CDO should take on responsibility for the data lifecycle management or not. Being a competent professional, this individual will identify some of the recorded strengths and weaknesses after every period. The CDO will also outline the best ways to minimize operational risks and keep expenses as low as possible. The lifecycle management should be in the hands of the CDO to ensure that the company gets the best from the implemented enterprise data strategy. With this kind of responsibility, the CDO will allow and guide the other executives to focus on their respective departments. The CDO will act as the mediator while providing a sense of direction (Alhassan et al., 2016). The CDO will ensure that they have the right resources and incentives to make the data lifecycle management process successful.
The studied case study has revealed that TD has made significant changes in an effort to transform its enterprise data strategy and meet the demands of all its key stakeholders. The collaboration and adoption of IBM’s tools means that the organization will achieve its goals much faster. Focusing on the presented insights, it is evident that the CDO should consider the need to implement the outlined changes in the selected countries (Brous & Janssen, 2020). The presented facts indicate that there is a need for the leader to start by implementing the proposed data strategy changes in the United States. The reason behind such a choice is that the US has implemented new policies that are intended to force companies to meet the outlined standards.
This approach will allow the company to continue performing optimally while at the same time meeting the demands of the customers. The new implementation approach would be successful since IBM is an American company that is associated with many stakeholders. The US also has many possible customers in comparison with Canada. The move to start implementing the proposed changes will address the external and internal pressures experienced in the US market (Krahe et al., 2019). The simplification of the data enterprise and the consideration of government policies can also make it possible for the organization to support its key business lines. The lessons and issues emerging from the US implementation process will guide Crisp to achieve better results in Canada.
Conclusion and Recommendations
From 2013, TD has been considering sweeping transformations that have the potential to improve organizational performance. The company has decided to appoint new professionals to fill the CDO and OCDO positions. These individuals have been on the frontline to complete various roles, introduce new tools and technologies, and appoint stewards who have the potential to align the new enterprise data strategy with the recorded market trends and customer expectations. Some of proposed initiatives are capable of taking the company to the next level and address the recorded challenges. For instance, IBM’s data resources would help the company transform its data strategy. Nonetheless, a number of issues existed that had the potential to affect the organization’s overall performance, including new policies, increasing use of mobile devices and online systems, and undefined roles. The designed action plan should, therefore, be informed by the nature of these challenges.
The CDO can design the best strategy for enterprise data and try it in the United States. This decision would be appropriate because the company is new in this country.
Alhassan, I., Sammon, D., & Daly, M. (2016). Data governance activities: An analysis of the literature. Journal of Decision Systems, 25(1), 64-75. Web.
Brous, P., & Janssen, M. (2020). Trusted decision-making: Data governance for creating in data science decision outcomes. Administrative Sciences, 10(4), 81-99. Web.
Krahe, M. A., Toohey, J., Wolski, M., Scuffham, P. A., & Reilly, S. (2019). Research data management in practice: Results from a cross-sectional survey of health and medical researchers from an academic institution in Australia. Health Information Management Journal, 49(2-3), 108-116. Web.
Kristal, M., Crisp, G., Bonello, C., Heighington, K. (2018). TD Bank Group: Building an effective enterprise data management policy. Ivey Business School Foundation.