Using Predictive Analytics to Achieve Optimal Cost Efficiency
In the current slow-growth economy, aggressive cost reduction initiatives continue to be a key board-level imperative for credit unions. New regulations, competitive threats and re-architecture requirements of aging IT systems continue to perpetuate a “leaner is better” mindset throughout the industry.
After undertaking numerous rounds of cost efficiencies over the past five years, today many within the industry have reached the laws of diminishing returns with their current cost reduction programs — or worse, are beginning to see adverse effects on growth and profitability as a result of short-term cost cutting actions.
Given this reality, it is becoming clear to many executives that future efficiency gains require a shift from tactical cost reduction actions to more strategic cost management. This means a greater focus on increasing the efficacy of cost reduction efforts while simultaneously investing in capabilities that will enable long-term growth and profitability. However, making this shift can be difficult.
How Complexity Threatens Cost Efficiency Goals
Cost management is undoubtedly one of the most complex activities in corporate planning. Unfortunately, the complexity of the exercise is accelerating at an increasing rate due to the fast paced nature of business—which is fueled by competition, 24/7 communications and rapid technology advances. For many reasons the objective of cost efficiency is clear, but the execution is burdened with many obstacles that hijack the exercise and give rise to a much lower outcome than originally was ambitioned.
Human and political factors are causes not to be neglected. But, commonly the blame for cost reduction project shortcomings is owed to increasing dynamic complexity, which results from hidden, unknown factors—or more precisely, interactions between factors—that can become significant and unexpectedly predominant in the cost equation. Over time, cost management programs become destabilized as the impacts of dynamic complexity cause unanticipated losses in quality, changes to volumes, and/or increased costs.
Making the necessary shift from tactical cost reduction actions to more strategic cost management is a challenge because the interdependencies between in-house and outsourced business processes, services and infrastructure have become overly complex and exist in a constant state of change.
Under these conditions it becomes increasingly difficult to accurately assess the potential impact of critically important decisions. Without forward-looking visibility, executives are often surprised when the results of their cost reduction decisions produce unacceptable levels of risk or unintended consequences.
Gaining Visibility into Hidden Factors that Drive Cost Efficiency
Most credit unions use some form of business analytics to help guide cost reduction decisions—whether in the form of spreadsheets or performance management software. However, business systems have become too complex and dynamic to be understood using methods of statistical analysis. The result is a tunnel-vision view, which provides decision makers with only partial knowledge of any situation.
Dynamic complexity results from new, never seen before patterns that cannot be understood, measured and controlled using a historical review of what has happened in the past. The effects of dynamic complexity indirectly appear in a balance sheet over time—growing undetected until they become obvious, at which point it is often too late for effective remedial actions.
Finding the Answer to “What is Optimal?”
Modern approaches to predictive analytics are able to reveal current system inefficiencies and provide a future-oriented view into how changes across services, architecture and infrastructure will impact performance.
In much the same way CAD/CAM is used in engineering and design, this process allows institutions to test ideas, validate plans and build operational models to perfect cost management strategies before any changes or investments are made.
With visibility into the factors that influence cost base across the entire business, it becomes easier for executives to identify opportunities to improve efficiency.
4 Steps to Improve Cost Management Programs in 10 Weeks or Less
- Model current system behavior – While there are many opportunities to set and achieve strategic cost management goals, it is most advisable to start by identifying a single, high-priority business problem to solve—with the goal being to quickly demonstrate success and prove that gains can be realized through the applied use of predictive analytics. Credit unions can use pre-built models and templates to accelerate time to value and fill in data gaps.
- Interpret current system behavior – Once the model have been proved, users can start identifying root causes of an increasing cost base and/or decreases in quality of service. Then prediction capabilities can be used to identify which systems and infrastructure will cause potential bottlenecks and constraints as services adapt and scale to meet increasing demands in the future.
- Identify improvements to business and IT systems – “What if” analysis can be performed to determine the effect of aging on current systems while prescriptive capabilities can be used to identify which remedial actions are required to improve the environment. Additionally, benchmarking can be used to expose new opportunities for improvement. Clear graphical displays help users prioritize which changes will yield the most significant improvements in terms of efficiency, cost and quality.
- Model future system behavior – Once the optimal future state has been identified, credit unions can validate if planned changes will yield the desired results before changes and investments are made. The overall effectiveness of any service process or project can be measured in terms of throughput, quality, cost and risk, while corporate dashboards can be used to assess performance against key business metrics.
Today, costs are undoubtedly a major concern for credit unions that need to adapt to a tougher regulatory landscape and improve competitive position amid uncertain economic conditions.
A great opportunity exists for those credit unions that are able to significantly raise the cost efficiency bar—by gaining visibility into strategic cost management opportunities that have the potential to boost the institution’s long-term health—in a way that ultimately helps the credit union ‘do more for less’.
Stripping out cost is undoubtedly hard work, fraught with many challenges, but predictive analytics can help ease the burden.
Modern approaches to predictive analytics allows credit unions to gain a unified view of the dynamic factors that drive cost base, compare themselves through robust competitive benchmarks to highlight alternative ways of working, and create the right action plan to improve the institution’s flexibility, responsiveness and efficiency as needed to meet evolving member demands.
While those that lack transparency into the root causes of cost inefficiencies may well still achieve growth, it may be unprofitable growth. Credit unions that approach cost as a board-level strategic concern will—with the right decision support tools—deliver superior member value, demonstrate the economic strength regulators are requiring and secure a real competitive advantage.