Unlocking Opportunities in Big Data




The Chartered Institute of Management Accountants (CIMA) in joint collaboration with the American Institute of Certified Public Accountants (AICPA) released a report on how organizations can unlock the value of big data and drive business performance. In addition to comprehensive desk research, over 2000 CFOs and finance professionals working in a broad range of sectors across more than 80 countries were surveyed for the report.

Data has become a key focus for business leaders today and is changing the way business is done. The volume, variety and velocity of data available for analysis is expanding exponentially and this wider shift towards a data-driven business model can be attributed to recent advancements in IT. Widespread adoption of enterprise resource planning (ERP) systems, electronic point of sale (EPOS), ecommerce and other internet-based systems has allowed more and more data organizational data to be captured digitally.

There is now an unlimited array of data sources for the organization. Examples of these data sources include mobile devices, call centre recordings, external data feeds, machine-generated data, customers’ social media posts etc. Data generated from all these sources includes a mixture of structured internal data and typically unstructured external data that may be used to strengthen analysis and forecasting and yield new insights into business performance, risks and opportunities.

This data explosion requires organizations to focus on developing new skills, invest in new tools and adapt new ways of thinking. The more data becomes a core business asset, the more the organization must learn to adapt to this data-driven business era and determine how it will use data to improve business performance. This means having the ability to find and extract insights from its data.

In this era of data-driven decision-making, finance professionals are well placed to transform data into commercial insights and value through planning, budgeting, forecasting and performance management. In other words, finance must know how to aggregate outcomes so that they can be converted into insightful reports.

To truly unlock the opportunities in big data, finance and accounting professionals need to partner closely with IT, data scientists and business leaders who in turn will turn their insights into action. Furthermore, finance professionals must have the ability to clearly communicate, lead and influence as well as possess a strategic understanding of the business.

The report also identifies five traits of the data-enabled CFO and these include the following:

  • Able to identify which data points are more useful in understanding what drives the business.
  • Have a clear sense of what customers care about most, why they choose the organisations’ products and services, how those customers are acquired and what helps retain them.
  • Able to embrace new forms of data and creative ways to incorporate this into business decision-making.
  • Comfortable with uncertainty, including the reality that big data may not provide definite answers.
  • Explore new ways to interpret data to better inform management decision-making.

Instead of relying on accounting data that is typically historical in nature, finance is now increasingly required to provide a real time forward-looking perspective of corporate finance. Investing in new analytics techniques and tools which are capable of managing and analyzing large amounts of data can help management draw new insights from data.

Organizations that choose to ignore the value of data in decision-making run the risk of losing out to others who are improving performance and gaining new insights from their data. Opportunities arising from big data include:

  • Ability to identify new opportunities for cutting costs or increasing efficiency.
  • Improved development and monitoring of KPIs that are aligned to corporate strategy.
  • Ability to prepare driver-based forecasts i.e. basing financial forecasts on operational drivers.
  • Ability to identify, assess and monitor external risks.
  • Increased revenues through better customer segmentation etc.
  • Ability to improve the responsiveness of decision-making and strategic planning.

Although new analytics tools play an important role in analyzing data and extracting insights from it, before delving into the world of unstructured data analysis, organizations should first identify the key business questions they actually want answered. In other words, the organization needs to fully understand its business model and its intangible assets, its data structures, data quality and data sources.

Once the problem to be solved is defined, the organization must then identify the data needed to answer its questions. In order to successfully inform decision-making or performance management, the data to be used must be reliable and accurate. Finance need to take the lead role of extracting insights from the data available within the organization. At the beginning of a data analytics project, Finance must ask the right questions and also ensure that any insights generated are actually used to aid decision-making and drive business performance. The ability to manipulate data and present it in many ways that are insightful and relevant to the audience is important for driving performance.

The following five steps are essential for creating a data-centric business:

  • Understand what new data would be relevant to your business model and competitive position.
  • Assess what data initiatives are already in place within your business.
  • Identify potential quick wins or small-scale proof of concept projects.
  • Conduct a formal data project to develop a related strategy.
  • Build on this initiative to start developing a data culture and ensure that data is regarded as an asset of the business as a whole.

In conclusion, finance needs to look beyond historical reporting and recognize the commercial potential of embracing a wider set of data. Furthermore, finance will need to review other non-traditional sources of data in order to gain more thorough understanding of business performance.

 

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