Harnessing the power of Big Data in financial operations

While the COVID-19 pandemic has thrown unexpected challenges at businesses, it has also made them realize the potential of data and analytics

The pace of digital innovation across all industries has exponentially increased in recent years, with companies trying hard to keep up with the rapid changes. The last two years have been especially challenging for many sectors. With the global supply chains being disrupted due to the COVID-19 pandemic, consumer sentiment continuing to remain low and volatile markets, companies are keeping a hawkish eye on rising operational costs, securing existing revenue streams, and finding newer ways for revenue increases.

But challenges also provide an opportunity for innovation. Digital transformation promises immense opportunities for companies that are willing to harness the power of data and analytics. The role of a chief financial officer (CFO) as someone who makes the company resilient and future-ready against unexpected disruptions has become particularly important in this context.

Data Analytics and the Role of a CFO

The role of a CFO has also undergone massive transformation − from a person who is simply in charge of financial reporting and keeping the accounting books to an architect of value who drives intelligent, data-driven decisions to support governance and systems for the company on the behalf of all its stakeholders. Today, CFOs are using the power of big data not only in planning, budgeting, and forecasting but also for rigorous business performance reviews using the best industry practices.

[box type=”shadow” align=”” class=”” width=””]The value of insightful data is crucial to all areas of business operations – whether it is predicting consumer behaviour, streamlining operations, optimizing procurement costs, efficient inventory management, managing cash flows, or measuring the return on investment (ROI) of a company’s initiatives and improvement programs. [/box]

For example, recently the CFO of a manufacturing company complained of the rising costs of logistics. During monthly performance reviews, it was found that there was labour unrest at two of the company’s factory sites that was not only delaying loading and unloading processes but also adding to rising operational costs. While this had been going on for almost three weeks, the lack of this information flowing up to the leadership prevented the team from taking proactive steps to solve the crisis much earlier.

This is just one of the innumerable ways in which data and analytics can help businesses in taking pre-emptive decisions to avert crisis and make them future-ready for potential roadblocks. Gathering reliable data and relevant insights and making those available to the leadership team is crucial in making time-sensitive, important business decisions. How do organizations enable a strong nervous system in their operations, so that the right insights on performance, and the factors impacting it, flow naturally to the decision-makers? The CFOs have a big responsibility towards ensuring such early warning mechanisms get established, and business managers can act on these alerts proactively.

Driving Value through Data

Big data can not only help businesses in overcoming crises but can also assist them in streamlining their operations. For instance, a large manufacturing company that works with multiple third-party vendors might procure raw materials at different rates and payment terms from different suppliers for its various factories. Data can help such an enterprise find out the best rate and payment terms at which raw materials need to be procured so that the company in question can have efficient working capital.

Another way in which data can be used is to ensure a superior experience for your stakeholders. Suppliers of business-to-business (B2B) companies often complain of inordinate delays and errors in invoice processing. Data-driven technology can easily solve this issue through a tracking mechanism that can provide information to all stakeholders regarding the status of payments.

Post-pandemic Trends in Big Data

While a once-in-a-lifetime disruption like the COVID-19 pandemic is rare, businesses regularly complain of operational disruptions that can be taken care of by making enterprises more agile. The pandemic has once again reiterated the importance of making organizations resilient against potential disruptions related to supply chain, procurement of raw materials and day-to-day operations.

At the same time, more and more companies are also looking at scalability when it comes to managing finances. Companies are now trying to cut back on their fixed costs while trying to increase the proportion of variable costs within the total operational budget. This has prompted many companies to outsource their non-core activities. Ecosystem partner organizations can not only bring about cost efficiency but also help in technology upgrades.

Data can not only help companies in streamlining their operations but also in providing a superior customer experience. Companies that transform digitally are likely to retain their customers much more than those that do not. While on one hand, organizations are using data and analytics to ensure compliance to regulatory mechanisms, they are using the same data to provide greater value to customers.

The Human Factor

Despite the rise of data in the digital economy ecosystem, one cannot overlook the importance of human intervention in identifying data biases that may result in skewed outcomes, low accuracy, and errors. Organizations must work with skilled professionals in interpreting data for making more meaningful decisions that can help bring more value for the company and all its stakeholders.

Tarun Satiya

[author title=”Written by” image=”http://”]Tarun Satiya, Managing Director, Accenture India[/author]

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of ET Edge Insights, its management, or its members

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