How finance can use data to create value across the enterprise

Advanced data analytics is regarded as the new gold. In the past, it was difficult to identify and quantify the specific added value and actual results of effective data management. However, as the costs and accessibility of artificial intelligence (AI), cloud services and other analytical instruments are steadily declining, and there is greater clarity about key analytical areas, the targeted use of data analytics is increasingly becoming a focal point for many companies. Today, no company can afford to ignore the potential advantages of data analytics for business decision-making processes, for example regarding an improved profit margin or stronger customer loyalty. This would be a considerable competitive handicap. The prime objective of data analytics is to obtain more detailed information and draw conclusions to flow into ongoing operations in a timely and targeted manner. Clear responsibilities and governance structures in the various functions and business segments are key to successfully unlocking the value potential of data.

While converting data into insights is a technical task, the translation of insights into added value requires a sound understanding of the business and financial impact. The finance function has always been responsible for translating financials into business activity, and already works in a cross-functional manner by monetizing each of the company’s actions, options and activities. Ultimately, it is in the unique position of being able to collect data from every area of the company as well as to process and present this data for management decisions. CFOs today are expected, from an internal management perspective, to provide real-time insights from data of all types, also increasing beyond the scope of purely financial insights. To this end, the finance function requires access to structured financial data as well as other structured company data and unstructured market data. Only by doing this can the finance function use analytics to map complex value relationships, influence their impact on financial ratios, simulate potential scenarios and reliably predict relevant market developments.

On the other hand, CFOs are under immense pressure to prepare information for a host of different external stakeholders, ranging from customers through to social influencers. As a rule, more transparency has a measurable effect on a company’s market position, image and value. Strengthening the finance function so that it can prepare a factual basis for decision-making, namely through the optimal use of data analytics, is therefore vital. Multiple factors determine the extent to which companies proactively explore the possibilities of data analytics or adopt a wait-and-see approach. These include the willingness to change or the pressure felt by companies from external stakeholders and their analyses. 

For example, the Norwegian sovereign fund sold several large investments in international companies due to breaches of maximum environmental emissions and other metrics. Its active investment management policy provides explicit limits for measurement ratios in the area of sustainability.

Moreover, ESG scorecards and ratings are gaining increasing weight in the context of available capital. This is already affecting access to and the cost of capital to a large extent.

3. Management of reputation risks

Classic reputation risks often arise as a result of global-scale scandals, which prompt customers to reassess a company. But advanced data analytics increase the possibility that even smaller scandals can be aggregated to a larger overall picture. Or analytics can allow external parties to question or refute assertions in companies’ sustainability reports. This may not necessarily stir up scandals with significant public impact, but a reputation risk may creep in nonetheless.

A key objective of the finance function will therefore be to align quality assertions in the financial statements with the data available on the market. In contrast to external analyses, the CFO must always be in a position to gain deeper insight, access better information and make more accurate forecasts than external parties. The establishment of a management and analytics model is necessary to allow for prompt reporting on key value drivers.

4. Market access

In addition to customers, investment companies and activists, companies are also facing another stakeholder group that intends to increase its use of data analytics: governments, authorities and other institutions. An increasing reporting burden is being placed on the finance function, especially in the regulatory environment, which cannot be managed adequately without analytics and flexible reporting solutions. Another lever will be the rating and assessment of company information by authorities, as is the case already with taxes.

The Chinese Corporate Social Credit System (CSCS), scheduled for implementation in 2021, will force the trend significantly further by recording and analyzing publicly accessible corporate information across various parameters. To achieve this, China plans to use data analytics and AI to collect the digital data footprint of companies and analyze the data in real time. The company rating from the analysis will likely have a direct impact on the company and could include sanctions such as higher tax rates, exclusion from project tender procedures or blacklisting. The positive effects are fewer customs inspections, swifter processing of applications and much more.

Even if the finance function does not necessarily bear the responsibility of monitoring the data analyses planned in the CSCS, its integration within the finance function should be endorsed. On the one hand the finance function is also responsible for other ratings, while on the other, embedding the main driver of CSCS in the internal control model alone already leads to operationalization and use of all relevant data in day-to-day decision-making processes.

Now more than ever, CFOs have the means of contributing to the success of their companies in a sustainable manner thanks to solid data analysis. In this way, the finance function’s key focus will shift from a unit primarily providing internal transparency and transactional services to that of a business partner providing added value.

Business partnering will be decisive for companies using advanced data analytics, allowing them to increasingly strengthen their market position, by making advanced data analytics an integral part of their DNA. Largely basing their decisions, forecasts and communication on data analytics means they can become the kind of company that stakeholders expect them to be. Not only does the company benefit internally from better and fact-based decisions, but it is regarded as a reliable partner on the market by consumers, investors, employees and other stakeholders.

Reliable information, accurate forecasts and transparency vis-à-vis various stakeholder groups allow for informed purchasing decisions, investments and regulatory clarity. The companies consequently benefit from the trust placed in them over other companies.

In a world shaped by constant change, it is critical that CFOs collaborate on the corporate strategy and help communicate it to stakeholders on the basis of well-balanced information. Data analytics can make a decisive contribution toward achieving this objective and will be a, if not the key, cornerstone for valuable contribution by CFOs.