Real-time intelligent data to fuel business insights should come to decision makers, rather than them having to approach finance personnel.
Finance is a crucial support function in any organisation. From achieving regulatory compliance to making potentially irreversible decisions that determine future business direction and priorities, financial data must first and foremost be accurate and insightful to shine the light on new growth opportunities and increase customer and client success.
However, an extensive global survey with over 700 senior finance leaders in global cities including US, UK, and Singapore, has revealed that over a third of respondents spend more time collecting data than analysing it, with 59% of large organisations citing “difficulty extracting data from legacy platforms” as a major challenge to achieving their analytical goals.
This shows that finance leaders are increasingly finding it hard to keep up with the rapid pace of business and the demand for real-time financial information. As a result, there is a high chance that the accuracy of data may have been compromised over time.
One might say that this is because finance professionals have previously left the organisation’s decisions around improving its analytics capabilities to others. However, recent high-profile scandals of financial misreporting and pressure on support functions to take on a strategic role have instilled in them the urgency to start thinking about how technology enables greater control and visibility of data across the organisation.
Strategic opportunities waiting to be unlocked
From long-term projections to short-term reporting, finance teams must consistently provide an error-free assessment of investment risks and business operations, but few people go to work being excited about chasing after data. They simply want answers to their questions.
So how can financial professionals make data work harder and faster for them? There are a couple of factors. At the foundation of every modern finance team is its Enterprise Resource Planning (ERP) software that comes with analytical capabilities to automate mundane tasks and generate actionable insights.
This allows finance professionals to transit from a spreadsheet-dependent, collect-and-report business to one that can leverage data to make strategic decisions across functional areas—for example, shifting the marketing and sales strategies in a region based on projections of supply and demand. It is a complex process involving big changes to business processes across teams, as well as to data management and access, and the very culture of decision-making in an organisation.
Yet another important aspect is the new approach to analytics for finance professionals, giving them tools that make it easier to stay informed about key financial measures. For example, they should be able to set alerts on the most-relevant Key Performance Indicators (KPIs), review data through visualisations and narratives, and share findings with colleagues via social media platforms on their mobile phones or laptops.
Going one step further to optimise the experience of business users, analytics capabilities should also be tied into the everyday work experiences of employees and their workgroups. What this means is that data should come to the user, rather than having the user go to the data.
The most modern ERP software is built on a cloud Software-as-a-Service (SaaS) platform and embeds machine learning algorithms that are constantly learning how each user interacts with the system, so it can further personalise data and streamline processes. This allows for highly personalised KPI visualisations according to each user’s needs and determines thresholds for each measure, runs what-if scenarios, and tracks progress towards goals.
Chief Financial Officers (CFOs) and their finance teams play an increasingly strategic role driving investments in emerging technologies which increase insights and agility and enable new business models. For them to take charge of business processes and important decisions in an organisation, ERP software must be designed to deploy quickly with best-practice KPIs powered by machine learning that provides predictive insights and enables users to monitor business performance against the metrics they set, drill down into details, look at trends and other measures, and finally make decisions wisely and quickly.
Riding the ASEAN digital wave
In this region, where digital transformation is a top priority for businesses across all industries, many people, including CFOs and Chief Information Officers (CIOs), have been quick to catch on, with many moving ERP software to the cloud to better streamline workflows and improve outcomes across the board.
Asia Commercial Bank (ACB) is one of the largest private banks and most technologically advanced financial institutions in Vietnam. With 346 branches providing retail and commercial banking services, including term deposits, credit cards, loans, and other financial services to more than four million customers nationwide, ACB is the first bank in Vietnam to move to a cloud-based SaaS ERP system.
This enabled them to process daily closing up to four times faster, increase storage capacity by three times, and reduce overall hardware investment costs by 30% over the course of three years. Not only do they have a powerful core needed to develop, refine, and deliver faster services with increased transparency, the use of as SaaS ERP cloud solution enables them to access data and insights to improve speed, agility, and accuracy to deliver the future of modern banking in Vietnam.
The benefits of a SaaS ERP software do not stop at large financial institutions. Bukalapak, one of four unicorn start-up companies and the biggest e-commerce marketplace in Indonesia, needed a set of solutions to help its finance team crunch financial data quicker, more efficiently, and more accurately.
With SaaS ERP cloud software, they were able to operate with more agility and finesse, leveraging the software’s connected intelligence to make better-informed decisions with higher productivity and improved results. With less time being spent on managing accounts and closing books, more time can be devoted to strategic decision making to grow the business.
Driving organisational change
Looking ahead, with more and more aspects of the production and consumption of data insights augmented by automation and AI, we can expect a dramatic reduction in the human effort involved in insights generation and more access to data and analytics for the business end-user. When finance teams start to proactively take charge of their digital capabilities and use data to outpace change, the path is paved for them to drive their organisation forward.