It is interesting to note that, of the majority of executives (54.2%) who felt their organizations were “out of balance,” the responses were about evenly divided between those who believed they were placing too much emphasis on value protection and those who believed they were overemphasizing value creation.
Data-driven insight – and foresight
As banks work to strike the right balance between value protection and value creation, analytics and advanced data science technology are proving to be crucial tools. Banking, by its very nature, has always been dependent on information that is both accurate and timely. But today’s data-driven enterprises rely on data systems to go beyond accurate recordkeeping to provide management with both insight into past events and foresight into future outcomes.
Historically, traditional business intelligence and data reporting systems provided managers with information that was inherently reactive in nature. That is, these systems reported what happened – to an account, a transaction, or a line of business – so that management could react and respond to an event.
As systems evolved, they began to incorporate diagnostic capabilities as well. Diagnostic systems used analytics and visualization tools to help management understand the contributing factors that had influenced past events. Most banks today have come to rely on such diagnostic tools to help guide strategic decision-making.
Today’s more advanced data systems have progressed further, offering predictive capabilities as well. Using artificial intelligence and machine learning, these systems can identify what is likely to happen in the future regarding an account, a customer relationship, a branch, or an entire institution.
Ultimately, such capabilities can lead to even more sophisticated systems that can be characterized as prescriptive or deterministic. Such systems employ advanced analytics to prescribe and initiate actions that will influence outcomes. Thus, as banks’ data analytic capabilities mature, they advance from traditional reporting and visualization of data toward more predictive and prescriptive functions, which add further value to the organization.
These data capabilities also relate directly to the value protection and value creation model. Reliable, timely, and accessible data obviously is a necessity for the remediation and maintenance activities associated with value protection. And, at the other end of the spectrum, advanced data analytic capabilities can open new opportunities for creating value through the optimization of existing functions and the development of innovative new products, services, and work processes.
The underlying foundation for all these capabilities is quality data. Data that is timely, reliable, accessible, and consistent across all platforms and applications requires a system of effective data governance, with appropriate policies, procedures, frameworks, and enabling tools. Such a data governance system will encompass all phases of the data management life cycle, including the collection, integration, management, protection, and application of data across the entire range of value protection and value creation functions.
Enabling change in an empowering culture
One common strategic error many organizations make is applying the same business management and governance practices across all functions, without regard to their value creation or value protection orientation. Operating procedures, risk assessment processes, decision-making protocols, and management structures that are designed for remediation and maintenance functions might not be appropriate for a business unit that is charged with optimization and innovation.
Obviously, some risk management and compliance standards must be applied universally, but there are other instances where practices that were developed for maintenance or remediation-focused functions can inhibit the nimbleness and flexibility that are needed in order to foster innovation. The banking organizations that survive – and ultimately prosper – in this new environment will be those that succeed in establishing a culture that embraces innovation opportunities without diminishing necessary risk management practices and priorities.
To create such a change enablement culture, banks need to cultivate several crucial attributes or characteristics. These include:
- A mandate for change. Banks that adapt well to change inevitably have a top-down commitment to taking bold steps, applying new metrics, recognizing and rewarding successful change projects, and being open to new project methodologies such as design thinking or agile project management. This commitment is not just embedded within a project management office but is manifested throughout the organization. It also is supported by training, education, and a willingness to make the significant investments that are needed.
- A multidisciplinary commitment. In addition to top-down leadership, wholesale organization change also requires an organizationwide involvement. Success requires broad participation, often through the formation of multidisciplinary teams composed of the bank’s strongest performers in such core competencies as finance, operations, risk management, and compliance. This is particularly helpful in new product development teams, where legal, risk, compliance, technology, and customer relationship management specialists work together. In many cases, the most effective change organizations are those that are willing to break down conventional organizational lines or implement rotational programs that broaden the horizons of employees and managers alike.
- Flexible governance structures. Speed and agility in decision-making are critical, but often these capabilities are hampered by complex, redundant, or unnecessarily rigid governance processes. The effectiveness of a governance structure’s oversight and value is not necessarily related to its size and complexity. In recent years, industry leaders have begun to challenge and decompose some of these processes in an effort to streamline and simplify decision-making without increasing risk beyond acceptable levels. Here again, data science and technology are proving to be valuable tools in this effort.
- Preparation for new business structures. Beyond internal flexibility, there also is a need for flexibility in the overall organizational structure. In recent years, several conventional banking organizations have launched partnering or consortium-based relationships with software or financial technology companies. The ability to pool resources and investments to address common needs or problems can be highly effective, but to do so banks must be ready to assess and able to address the legal, regulatory compliance, and risk management questions that can arise.
Ideally, the cultivation of these cultural attributes would lead to the establishment of a center of change excellence within the organization. In addition to boosting visibility and offering public evidence of the bank’s commitment to change enablement, such a center also functions as a repository for ideas, tools, and methodologies that streamline the development of designs, prototypes, and refinements.
The ultimate objectives are to help drive the change management process and accelerate the implementation of new tools, techniques, products, and services. As technological advances and changing market demands continue to transform the industry, banks will find such capabilities are essential.
Although no one can predict precisely what lies ahead for the industry, banks that develop and embrace more effective data systems will benefit from both better insight into current trends and more accurate foresight into likely future developments. These enhanced data capabilities, when applied within an organizational culture that enables change and empowers innovation, can help banks adapt more nimbly to new environments and respond more effectively to the challenges and opportunities they encounter across the entire spectrum of the value creation and value protection model.
