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Optimizing strategic financial planning through big data and analytics

Financial Services Writer

The financial services industry has reached maturity, according to the definition of industry life cycle set by Inc. Through the lens of Porter's Five Forces, explained in Harvard Business Review, the industry is characterized by:

  • Intense competitive rivalry
  • Falling prices and reduced profitability
  • Supply exceeding demand, leading to slow revenue growth
  • Increasing threats from substitute suppliers
  • Competitive costs

It is a daunting undertaking to compete in the modern financial services marketplace, and businesses must find opportunities for increased automation and efficiency to be successful.

Efficiency is king

Players in the industry know that effective strategic financial planning and efficiency are king. While finding new sources of revenue is always important, minimizing the cost base is the most direct route to maintaining or improving profitability in the current stage of the industry's life cycle. One tactic commonly employed to reduce costs is engaging in mergers and acquisitions (M&A), amalgamating market share and thereby achieving economies of scale. Alternatively, some organizations choose to innovate in continual process automation to drive down delivery costs.

M&A opportunities are not always available, but every financial services provider can benefit from continual improvement. How can businesses identify opportunities for improvement? Big data and analytics can be very helpful in this regard.

Big data provides financial services providers with a volume, velocity and variety of data that was not possible before. Data-driven organizations are five percent more productive and six percent more profitable than their competitors, Harvard Business Review notes. For this reason, effective strategic financial planning often includes using analytics to identify areas that could benefit from enhanced automation.

Examples of metrics, derived from advanced analytics processes, that indicate a need for enhanced automation include:

  • Unacceptable error rates: Internal error-tracking systems provide part of the picture, and customer surveys can present even more relevant data. These two sources can also be enriched with insights from unstructured social media data. Customers are talking to their social connections about service experiences, and analyzing data from these discussions can lead to valuable insights.
     
  • Reduced employee productivity: It is easy enough to identify key performance indicators (KPIs) to measure employee productivity. Organizations can compare that data to competitors' achievements in the same areas to give the results appropriate context.
     
  • Regulatory and compliance concerns: Compliance burdens will continue to increase in the financial services industry. KPIs geared toward identifying the efficiency of compliance activities are a critical dimension in strategic financial planning and delivery efficiency assessments.

Making it happen

The Project Management Institute notes that there is a very large chasm in project success rates between high- and low-performing organizations. A key differentiator between these two groups is the degree to which their projects and programs are aligned to the organization's strategy. Using best practices, appropriate project management methods and the right big data and analytics tools will help achieve that alignment and ensure the financial services organization is a high-performer when it comes to optimizing strategic financial planning processes.

https://kapost-files-prod.s3.amazonaws.com/uploads/direct/1448461216-25-9766/StrategicFinancialPlanning_Blog.jpgThe following considerations will help focus big data and analytics initiatives on strategic outcomes:

  • Use roadmaps: Experienced, strategic IT partners can be helpful in mapping out which technologies will deliver the best returns.
     
  • Be disciplined: Companies should not look to build Rome in a day. Rather, they should aim to execute appropriate projects based on the roadmap or big data strategy.
     
  • Build with the future in mind: Scalability and flexibility are key considerations, as the volume of data in play will grow quickly and significantly.
     
  • Manage change and risk: This is another area where a seasoned service provider can add significant value. Effective change management processes are required to optimize alignment of people and processes in the new data environment. Utilization of experienced professionals will assist in enhancing project quality, minimizing risks and reducing time to market.

In short, the financial services industry is a highly competitive environment, one characterized by decreasing profit margins, increasing customer demands and the ever increasing threat of disruption by innovative financial technology startups. However, productivity gains and competitive profitability differentials are achievable through effective use of big data and analytics. Learn about the advanced analytics that can help you drive more effective strategic financial planning across your organization.