Advanced financial analysis to improve decision support

The digitalization of companies impacts the finance function. The CFO is certainly the person best placed to understand the value of advanced analysis, which makes it possible to combine a multitude of micro and macroeconomic data. The advanced financial analyses are among today’s leading decision-support tools.

Perform a top down scenario analysis

The “top down” approach aims to take into account the various factors of the global environment in which the company operates. This is a macroeconomic approach.

Taking into account the general economic context as well as major indicators that are particularly important for the sector of activity concerned, such as the variation in exchange rates, will make it possible to generate forecasts. These will then be compared with the actual results.

On this basis, and depending on the discrepancies observed, the CFO may propose the implementation of any necessary adjustments. Predictive analysis thus opens the way to the prescriptive dimension.

Decisions will be based on the most appropriate choices in terms of value creation, in line with the forecasts established by advanced predictive analyses.

The purpose of a “top down” scenario is to determine how major macro trends are likely to provide investment opportunities. The idea is to progressively go down to the level of each department of the company, then to each service and project. In this way, the expected returns and the level of risk exposure will be very finely assessed. This study will enable the company’s managers to define priorities and allocate resources to the various subdivisions in an optimal way.

If necessary, the “top-down” logic can be combined with a “bottom-up” approach that aims to identify sectors with a strong innovative capacity that are little affected by the macro-environment.

Advanced financial analysis to develop self-optimizing sales forecasting algorithms

Leveraging algorithmic capabilities and artificial intelligence is essential to deliver sales forecasts.

Advanced predictive analytics enable us to observe, with great precision, the evolution of customer buying behavior, and thus gain visibility on the main opportunities to be seized.

Algorithmic segmentation makes it easy to rank customers and highlight sales prospects. The company is then in a position to anticipate the needs of its customers and thus to benefit from a favorable position in a very competitive market. It may also, if necessary, define a pricing policy. Advanced financial analysis also provides an effective means of simulating the impact of decisions to be taken.

Using a single platform greatly enhances the integration of data from multiple sources. Thus, the integration of forecasting, budgeting and results data is automated. The agility of the system makes it possible to forecast over a selected period of time. Performance monitoring is done in near-real time and allows for quick adjustments to be made.

Develop demand models to improve working capital and inventory management with advanced financial analysis

Forecasting working capital requirements is an essential issue for any company. It helps to determine the needs that must be financed by equity or by borrowing.

The identification and dynamic cross-referencing of a number of data points provides visibility into potential failures. These can be caused by an inefficient invoicing system, too many payment terms granted to customers, poor optimization of supplier invoices, or a too approximate inventory management.

Once the difficulties have been identified thanks to advanced financial analyses, it is advisable to implement useful measures: just-in-time inventory management, negotiation of payment terms with the main suppliers, etc.

Advanced financial analytics help create value in companies that are at the forefront of the digitalization of the finance function. Indeed, the exploitation and sharing of numerous data informs decision-making by providing precise predictive analyses that can simulate the results to be expected for each of the possible options.

P.S.

SQORUS supports its key account customers in digitizing their finance functions. With a functional and technical expertise of the main solutions of the market dedicated to the finance business, we implement and accompany our customers in all phases of their projects. Thanks to consultants certified on solutions such as Oracle, Netsuite, PeopleSoft, Kyriba or Axway, Sqorus is the preferred integrator of financial solutions on the market.

Also read about the digital transformation of finance functions

• What is the role of the finance department today?

• 5 obstacles to the digital transformation of finance functions

• The finance function, an actor of change in the digital transformation of the company
• Predictive analytics to unlock value and detect growth opportunities
• Better managing talent to overcome the obstacles to digital transformation in the finance function
• Improve financial processes with automation and RPA
• Provide users with real-time data with data visualization
• Advanced financial analysis to improve decision support
• Identify the business processes in the finance function that would benefit most from digitization
• Security at the heart of the company's financial transformation
• From a Finance IS to a Finance Data System