Organizations collect overwhelming quantities of data – from internal functions and operations to external customer interactions. With business analytics holding a strong promise to analyze data for competitive advantage, real-time insights across the value chain has become critically important for Chief Financial Officers (CFOs).

Traditionally, CFOs have owned data-driven analytics for strategic aspects of managing the business. However, big data and data analytical capabilities have given CFOs an opportunity to bridge the gap between strategic and operational decision-making. Leveraging analytics for operational decisions enable CFOs to extend their influence outside core finance functions.

Value Chain Beyond Finance

Once the CFO is convinced about leveraging analytics in operational decision-making, he or she can, through finance-supported analytics, drive value outside finance’s core functions throughout the business. Areas in which finance-supported analytics can drive value include:

  • Procurement — spend analysis and vendor management

  • Business units — margin-erosion analysis, pricing analytics, customer profitability

  • Sales and marketing — price-points, revenue drivers and leakage, demand-price elasticity, customer churn and retention

  • Supply chain — sales- and finance-linked forecasting, product profitability

  • Information technology — technology investment and planning

Regardless of the department or function, a CFO needs reliable data and insights to make informed decisions. Be it the study of a company's marketing success, or an evaluation of their customer support efforts, data-driven analysis serves to tease out the right information to make cognitive and evidence-based decisions. The CFO is often found wanting in correctly appreciating the power of data collection efforts. The high risks of taking a myopic view of individual departments divorced from the company's bigger picture needs to be factored in as well. One cannot impress enough the critical importance of collecting relevant data across all business units to enable centralized control. This ensures that all the company's decision-makers are on the same page when drawing conclusions from the same book.

The consistency of data collection across different sites and data collectors is a critical aspect of data quality. Effective training and processes ensure that such consistency is maintained across all company functions. As such, a solid acceptance of a singular version of the truth must dominate discussion plans and decision-making.

While it is not a complex process, an improved understanding of the business requires meaningful collection of data for thoughtful analysis. It is also vital to analyzing better ways to boost revenues and profitability.

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