Nell'Armonia, digitalisation de la fonction finance

The big data challenge for finance departments

Big data financial analysis

The diversification and exploding volume of information are changing business analysis and forecasting methods. The CFO is at the heart of this transformation.

The current decade has seen a true information revolution.

Mobility, social networks and a refocus on customers are leading enterprises to take an increasing interest in their customers’ behaviours, their own e-reputation and the outward communication that seals their place in the competitive landscape.

The corporate value chain inevitably means that this information impacts the enterprise’s projected financial results and the cross-functional management of performance, driven by the CFO.

Our answer: big data reporting and prediction


  • Information is diversifying and its volume exploding
  • New data to be integrated into forecasts and reporting
  • A new approach to information analysis
  • Nell’Armonia helps you navigate your way around
Big data reporting and prediction Nell'Armonia

Quantitative and qualitative data increasing exponentially


Mobile investments and the growing reliance on social networks to communicate with and survey customers have brought with them a real explosion in the volume and sources of information which enterprises have to deal with. More data will be created in the next two years than has been created over the last ten years.


The finance department therefore has to adapt to this information revolution – which comes on top of the accounting information it habitually handles – and has to integrate it into its business analyses and the financial results.

Analyse financière de masse Big Data

The challenges for finance departments posed by the big data revolution

Reporting and forecasting have to evolve

The CFO stands at the end of the value chain of all digital investments, every one of which has an impact on the corporate financial results:

  • Impact of the e-reputation of a service/product line on turnover variations or forecasts
  • Impact of the effectiveness of a marketing campaign on turnover seasonality
  • Impact of customer satisfaction on settlement periods and therefore on cash flows
  • Impact on profitability of prices and positioning in relation to competitors etc.

All this information has a direct influence on reporting, analysis and forecasting processes, and obliges finance departments to broaden the range of information sources which they can tap into in order to fine-tune their processes and ensure the alignment of performance measurements.

New analytics and reporting methods and technologies

This data revolution has ushered in an explosion of information in terms of volume and format (quantitative, qualitative, structured or unstructured data), resulting in the relegation of classic BI solutions to the rank of outmoded tools:

  • Costly and unresponsive (“project” mode for each development)
  • Delivering obsolete information before reaching the consumer
  • Information taking more time to produce than to consume
  • With search and storage tools that are unsuited to real time exploitation, to purely qualitative information processing, to destructured searches (mining/correlations) or to predictive analytics(complex algorithms).

New approaches to information analysis therefore have to be implemented in order to ride the big data revolution to maximum effect: new technologies, new methods of forecasting (predictive analytics) and information analysis (correlations).

Nell’Armonia helps you navigate your way around!

Nell’Armonia has developed real expertise in the field of big data financial analysis (big data predictive analytics) and supports and guides you in handling feedback and in opening up your financial processes to new sources of information, with a staged approach:

  • Working with you to identify the business themes that will constitute pilot themes for trialling and validating this new approach
  • Working with you to define the architecture most suited to your needs, and the data flows to be implemented
  • Working with you to select the most appropriate technologies: software, “in-memory” technologies capable of meeting analysis and performance requirements
  • Implementing the selected technologies
  • Steering change management among your decision-makers and users, championing the added value of these innovative solutions.
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