From a Finance IS to a Finance Data System

The digitalization of companies impacts the finance function. The purpose of digitization is to convert physical information into digital format. It promotes data storage and exchange. With digitalization, the finance function is moving to the next level. The aim is now to homogenize the finance IS in order to improve processes and increase the level of analysis. In order to take this crucial step, it is necessary to have quality data.

Strategy FINANCE

The Finance blog

Documenting data flows

A lot of data is flowing into the finance department. Also, this data must be supported by servers and networks powerful enough to guarantee its storage and make it available in a reduced time.

It is also necessary to homogenize, classify and document the data, so that each interested party is able to retrieve and analyze the information. In a fully operational system, the data can even be directed to the users without them having to perform tedious search operations.

Identify sensitive and relevant data flows

It is essential to classify data flows according to their sensitivity (personal data, medical information, etc.). In a digitalized financial system, it is necessary to establish a risk map. The personnel concerned will be the object of awareness actions since the quality and security of the data also depend on the human factor.

Indeed, data entry errors, for example, can affect the reliability of the basic data and thus distort any analysis. Finally, the traceability of the most sensitive data must be guaranteed.

For business strategy, it is critical to determine what customer information is most useful, who is capturing it, and to whom is this customer data accessible.

Make data reliable to use it well

Some of the so-called referential data are quite stable over time. This includes the inventory of material resources and the number of clients.

Operational data, on the other hand, is likely to change rapidly. For example, the level of sales of a given product or the churn rate of a service may vary significantly over a relatively short period of time. Also, the reliability of the data will depend on its updating. The operational departments need to have very recent data. It is then important to specify who is responsible for updating the data and how often. When you know that 25 to 30% of prospect files are obsolete after one year, the sales team must remain vigilant about updating them, at the risk of launching marketing campaigns unread.

In addition, to be fully reliable, some data will need to be linked to other information. It is therefore necessary to achieve a higher level of organizational integration and decompartmentalization of the business lines.

    Financial data governance in place

    In too many companies, there is still no real governance of data flows. The latter are exchanged between various sources, without any real overall architecture having been put in place. Some information may be sent several times to the same recipient, others will never reach the interested parties.

    This governance requires efforts in the organization and in the definition of new processes. A dedicated team within the IT department can be mobilized to define the processes to be implemented, to control them and to deliver the authorizations and other access rights.

    At the same time, each of the departments concerned will feed the database set up and ensure that the data is up to date and consistent, as part of their day-to-day operations. The role of the operational actors is fundamental since they are the ones who have the expert knowledge of the business and who can therefore give the best opinion on the quality of the data. Effective governance is based both on the architecture of the system developed by the IT department and on listening to and mobilizing the business.

    The Data Owner plays a key role here since he is responsible, among other things, for the data and its updating. It must manage data collection, storage and protection.

    In particular, it must:

    • Mapping the data it handles
    • Control access to this data
    • Coordinate their protection
    • Set up a repository to contextualize the data

    Enhancing the value of financial data

    Having high quality basic data is the prerequisite for advanced analyses that will help in decision-making.

    Based on accurate predictive analytics, executives will be able to identify business opportunities. The more integrated the financial data system, the more efficient the reporting. It is therefore crucial that this system be understood by all.

    By automating and simplifying processes and increasing their operational experience, finance managers will be able to leverage their level of business expertise and become strategic partners to senior management. Investing in data exploitation is now a priority. Meeting this essential challenge is, in fact, part of the contemporary means of creating value.

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