The finance function is undergoing a significant transformation as we approach 2030, with leading organizations focusing on four key imperatives to drive efficiency and effectiveness.
First, finance departments are looking beyond traditional transactional activities to unlock efficiency in more strategic areas. By leveraging advanced technologies like machine learning and AI, companies are automating complex tasks in financial planning, capital allocation, and auditing. The need for data accuracy will be greater than ever to ensure key data points used for decision making are timely and verified.
Second, in a break from the past finance leaders are taking charge of data management across their organizations. With the exponential growth of data, finance departments are uniquely positioned to define master data strategies, prioritize data quality, and invest in agile, tech-enabled data infrastructures. This cannot be achieved through legacy systems, but requires finance departments to embrace the latest and greatest technology available on the market. It is important to note that changing systems is now safer, making it easier to transition away from decade old technology.
Third, improving decision-making is crucial. Finance teams are using advanced analytics to provide clearer, faster, and richer insights. This involves upskilling staff in analytical and data visualization techniques, as well as enhancing the quality of finance business-partnering roles.
Finally, reimagining the finance operating model is essential. This includes breaking traditional hierarchies, creating flexible teams for deeper business insights, embedding digital skills across the organization, and developing business-savvy finance leaders.
By embracing these imperatives, finance departments are not only reducing costs but also shifting towards more value-added activities. As we move towards 2030, the finance function is poised to play an increasingly strategic role in guiding organizational decision-making and driving enterprise value creation.
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