In brief
- Most financial institutions (FIs) manage profitability using an obsolete paradigm running outdated technology.
- Robust profitability and performance management delivers actionable, bottom-line insights for day-to-day decisions and strategic planning.
- By making a change now, FIs can increase the return of investments in big data to support the broader profitability management agenda.
Prior to COVID-19, many financial institutions (FIs) were not able to invest in modernizing their finance capabilities as much as desired, due to investment spend being predominantly channeled toward more pressing needs, such as keeping up with stringent regulatory reporting requirements and investing in digital, anti-money laundering and cybersecurity capabilities.
As a result, today’s profitability insights miss out on the transformative technology advances of the last decade, including cloud computing, artificial intelligence and the benefits that can be derived from big data. In fact, many FIs depend upon an amalgamation of spreadsheet-based approaches and overly patched legacy systems that often cannot be adequately leveraged for timely business analytics.
The pandemic has provided a much-needed reality check. Today, success requires pivoting quickly between different performance scenario analyses and the agility to generate profitability insights that easily identify management actions. Delaying distribution of profitability insights to be accurate to the nth decimal place, on top of a very complex process, is a cost that most FIs should avoid.
Beyond the old profitability management paradigm
Financial institutions are accustomed to analyzing profitability through complementary lenses: a backward-facing lens to analyze past performance, and a forward-facing lens to model likely business scenarios.
For most institutions, integrating these two perspectives was already a steep challenge given legacy technology, siloed processes and taxonomies, and patchwork data-management practices. COVID-19 and the overall pace change, however, have rendered even that integration obsolete.
The backward-facing lens is especially insufficient, as it offers a lagging perspective of data sets that are typically available around mid- to late month and reflect the situation of the previous month, or quarter. In addition, forecasting future performance is now more challenging than usual, and COVID-19 proved that outlier-class macroeconomic events can outrun and outlast most profitability models. How might the timing and efficacy of a cure or a vaccine affect business conditions throughout 2021 and beyond?
Agility to react instantaneously is the new competitive advantage
Leadership at FIs must react more quickly and decisively than ever. It’s not unusual for strategic decisions to be made weekly in the current environment. However, with outdated profitability management as a foundation, actuals that are lagging and forecasts that are murky at best, finance teams find it difficult to glean profitability insights and identify actions for business leadership.
FIs that were ahead of the curve in modernizing their finance data and technology were typically able to analyze and respond more quickly to business impacts caused by the pandemic.
Today’s finance teams need a more agile platform that can run instant what-if scenarios based on the latest actuals and model large bottom-line impacts, such as the loss of a key institutional client or a significant change in anticipated business volumes. Moreover, establishing routines that are more self-service in nature enables finance users to quickly construct these scenarios without opening an IT service ticket. These capabilities redirect efforts toward analyses and insights generation utilizing near real-time and curated data, rather than draining resources for offline data retrieval and preparation for reporting. This better positions FIs to capture market opportunities, such as gain market share through more aggressive pricing or acquisition of new customers.
Quicker, better, more actionable: the benefits of strong profitability management
A robust but nimble profitability management framework provides transparency into bottom-line performance, as well as insights into the business levers that can be adjusted to impact future profitability results. Analytic outputs from the profitability framework support diverse end-user needs across pricing, margin analysis, customer segmentation, and more. The framework also delivers information to meet both enterprise reporting use cases and the needs of the business lines, including performance drill-downs into business segments, regions, products and clients.
Finance and business leaders are seeking better, faster and more actionable profitability insights to:
- Better understand product pricing and offset current margin pressures
- Balance the trade-off between acquiring market share and defending profitability
- Drive product optimization by understanding cost dynamics, cost behaviors and other factors to capture the true cost of a product
- Generate product campaigns and calculate the impact on enterprise profitability (e.g., better optimize existing infrastructure capacity)
- Create opportunities to cross-sell clients into more profitable product offerings
- Create additional transparency for costs incurred at a corporate level and, based upon an agreed taxonomy, generate a cost narrative to foster better engagement and dialogue within the enterprise
- With strong profitability management capabilities, FIs can quickly move among the agendas of growth, cost containment and crisis management according to market demands.
Pathways to better cost and profitability management
Technology and data quality are often ascribed as the culprits in underperforming profitability mechanisms. However, successful profitability management requires more than just technology. FIs should focus on:
- Strategic outcomes — ground the modernization of profitability capabilities with a clear understanding of what decisions need to be enabled. The entire transformation must focus scope and priority on where it adds value.
- The right tools — adopt transformative technologies, such as cloud-based tools and data virtualization, and create the right technology architecture rather than forcing a one-size-fits-all tool to execute the end-to-end process.
- Simplified methodologies — utilize the “strategic outcome” test to drive significant simplification of the end-to-end process. Often, unnecessary granularity are generated for the sake of creating data or to support outdated/discontinued requests. Establishing a clear link between data/insights produced and the strategic outcome they drive is critical.
- Traceable and trusted data — build trust in reporting profitability analytics based on the ability to trace cost and revenue data from profit and loss statements back to the general ledger, as well as through a structured master data management program.
- Self-service insights on demand — focus on creating standing profitability performance packs for leadership that are consistent across the enterprise, available early in the month, and based on standing, business-as-usual use cases. In addition, enable finance and business users to access curated and certified data sets to allow for analysis on demand and generate customized self-service insights.
- Training and adoption — embed profitability insights within key finance processes and workflows so they are used to support day-to-day management, rather than consulted only sporadically.
Profitability management is most valuable when it applies a consistent lens across the enterprise, while also integrating data from various functions and lines of business. This avoids redundancies in reporting, supports informed decision-making and better tracking of the outcomes.
Why the time is right
Most FIs are positioned to leverage previous large investments in big data to support profitability management. This increases overall return on investments that have largely been regulatory-focused and remain not fully paid off at many institutions. Furthermore, new data management techniques are available to improve the data supply chain, leading to better insights. Coupled with the latest advancements in technology, FIs can use social media-like constructs to surface and discuss those insights, while maintaining data integrity, fostering a more collaborative identification of management actions.
It might seem counterintuitive to secure investment capital during a cycle when most change initiatives are delayed and transformation budgets are being slashed. However, FIs are called to manage the trade-off between growing market share and defending profitability. FIs that deploy a profitability generation apparatus that is fast, agile and insightful will likely be able to better weather the economic storm and drive profitable growth.
Summary
The speed to generate insights and the agility to pivot quickly between alternate profitability scenarios can help financial institutions (FIs) better navigate the current economic and business environment, where balancing the trade-off between increasing market share and defending profitability is a key driver of competitive advantage. However, when it comes to generating profitability insights, most FIs are missing out on the latest transformative technologies and have built an ecosystem that is more focused on being accurate to the penny rather than enabling strategic outcomes with speed, simplicity and on-point insights.
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