Data compatibility: how financial departments can (…) – TOOLinux

The world around us is changing faster and faster and financial departments cannot always adequately respond. This leads to fluctuations in indicators in financial systems, which should determine the impact on business performance.

This requires real-time analysis, consisting of collecting all the information regarding the company’s turnover, which can reveal indicators of business opportunities or pitfalls. But how detailed should this analysis be? What information has commercial value? I tell you in this blog!

Leverage the digital financial processes of tomorrow

To address this challenge, a new set of tools and technologies, such as artificial intelligence (AI) and predictive analytics, are being developed that automate the collection of data at a scale and speed never before possible.

It also helps financial professionals get rid of manual data entry and spreadsheets. In this way, they can turn into someone who, through financial analysis, shows how to influence the company’s operations. By applying artificial intelligence and intelligent automation, finance can manage the business based on hard numbers and translate them into language that business decision makers can understand.

Manage your business based on financial data

To do this, organizations must go through three steps: record all financial data, create value, and retain it. The underlying financial systems must be designed so that the finance department can draw up budgets and forecasts and compare them to current numbers and business priorities. In this way, the finance department can provide explanations for discrepancies and correct erroneous assumptions in forecasts. Finance professionals can then map out actions and assign them to various business units and teams. This approach also enables Finance to respond to ad hoc status updates, identify real-time trends, and more accurately predict the impact on business performance.

Data compatibility issues

But to achieve this, a solid foundation is needed, especially data compatibility. Financial data is currently hidden in all sorts of systems and is not always reliable, as it is often done manually. This is why the approach to data integration must be carefully considered. The quality of customer and supplier master data in all financial management systems must be verified and guaranteed. And that’s the job of the finance department.

Technologies that can help in this regard: REST APIs which, when combined with low code, can offer new flexibility in financial systems. In addition, Intelligent Invoice Processing (SIP) helps automate the processing of accounts payable and perform predictive general ledger analytics. This results in significant savings and faster payment of creditors’ bills, leaving more time for employees to complete tasks that may matter. Similarly, Intelligent Invoice Recognition (SIR) services allow the recording of creditor invoice data scanned using artificial intelligence.

Finance departments that bring order to data collaboration can enable the business to do more with financial reporting and act as a strategic partner. Business decision makers can expect the following from the finance department:

Permanent forecast for the current year: modern financial planning and analysis (FP&A) systems should always be available for viewing, and not used only for traditional quarterly reporting. The business should be able to add new data at any time, while the finance department decides when to report.

Regular status checks: It is important to keep track of who has access to the FP&A system and to check who has not yet added updated information. This way you can clearly see who made the decisions and get a comprehensive view of business performance.

Reports that tell a story. Financial reports should be more like reading a newspaper, and members of the executive team should have access to ready-made summaries at any time. To do this, the finance department must convert all financial reports and business data into a standardized report.

Working on data interoperability can be a big, long journey. Therefore, it may be appropriate to focus on smaller projects first. For example, first solve problems for a specific financial process or a specific business unit using automation and data mining. From there, you can develop and help run the business with correct and appropriate financial documents.

- Lode Maris, Regional President Unit4 Western Europe

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