Imagine you’re planning a trip to a new city. Financial reporting is like having a basic tourist map. It shows you the major landmarks and gives you a general sense of where things are, but it doesn’t tell you the best routes, potential detours, or hidden gems along the way. It only provides the perspective of how things were at the time of printing. Financial analytics however, is like having an interactive GPS with real-time data. You can zoom in on specific areas, see traffic patterns, and even discover hidden opportunities. You can plan your financial journey with more precision, adapting to unexpected changes along the way.
According to Gartner’s Top 5 Priorities for CFO’s in 2024, 54% of finance organisations still struggle to provide data and reports stakeholders can rely on, which is why improving finance metrics, insights and storytelling was also rated as a top priority this year by CFO’s. Relying on historical financial data with fixed perspectives, while crucial, is no longer enough. To achieve optimal financial health, companies need to make informed decisions by leveraging analytics, data visualisation and storytelling capabilities. This means progressive finance teams have a role to play in transforming data from a passive observer into a proactive driver of informed decision-making. This transformation journey has four stages, which we’ll explore here. The more mature the analysis along this journey, the bigger the impact will be.
Stage 1 – Traditional Financial Reporting
For generations, finance teams have focused on financial reporting. This involves gathering, summarising, and presenting past financial data, of what’s happened in the previous month, quarter, or year. It’s essential for understanding where a company has been and serves key audiences such as boards, management teams, financiers, and other investors. As it’s often used as part of formal and regulatory financial reporting purposes, the structure and format of reports is important, which is also good for consistency. The nature of accounting means that closing the books takes time and the financial reports present performance as it was at a point in time in the past, rather than what’s happening right now. Information is often high-level and presents data in isolation, so doesn’t assist in identifying underlying causes and taking targeted actions. Financial reporting also provides limited value to address emerging trends, anticipate challenges, or capitalise on unforeseen opportunities.
Stage 2 – Traditional Financial Analytics
Venturing beyond simple financial reporting, analytics or business intelligence tools provide more depth than a structured reporting format. With more up-to-date information, different perspectives provide insight on what is happening, for example what area of the business is driving the increase in COGS? Graphical visualisations offer visibility into trends and outliers in a way that tables of numbers can’t match. Interactive tools enable users to drill down and see detail that is often hidden in a formatted report.
Analytics tools also enable more than just visibility. Forecasts for example are a long-used benchmark for measuring actual performance, however how do you know if the forecasts themselves are good quality benchmarks? Analysing forecasting accuracy can refine forecasts to provide better benchmarks. However ultimately, this type of analysis is still centred on historical data, so while it offers some improvement over pure reporting, it still lacks the forward-thinking perspective needed for finance teams to provide proactive decision-making to influence future outcomes.
Stage 3 – Finance Led Operational Analytics
A crucial aspect of any finance analytics initiative to influence the future is identifying the right Key Performance Indicators (KPIs) to track. KPIs are measurable values that reflect the health and performance of your business, and also provide clear focus on areas to target for increasing that performance. Selecting the most relevant KPIs depends on your specific industry, business goals, and strategic initiatives. If the bottom line of the business is financial, then however operational the KPIs are, some need to tie back to financial drivers. Some common KPIs for active financial analytics include:
- Revenue growth rate: Measures the increases in revenue over a specified period.
- Profitability ratios: Metrics such as gross and net margin assess your ability to generate profit from sales.
- Spend ratios: Percent of sales highlight the spend on selected business areas as a proportion of revenue aligning investment in target areas.
- Inventory turnover ratio: Indicates how efficiently inventory levels are managed to reducing holding costs.
- Accounts receivable turnover ratio: Shows how effectively a company collects payments from customers to improve cash flow.
- Liquidity ratios: Current ratio indicates your ability to meet short-term financial obligations.
- Environmental, social and governance (ESG) ratios: ESG initiatives are top of mind for finance teams in 2024 with an increase in mandatory ESG disclosures. Top ESG concerns like health and safety, employee diversity, transparency and disclosure are all measurable.
By actively monitoring these and other relevant KPIs specific to your business, you can gain real-time insights into your financial performance and make data-driven decisions that drive sustainable growth and success.
Reducing the time from data entry to availability for analysis can also be critical. Using technology to access and analyse up-to-date financial information can enable immediate course correction and strategic adjustments as market conditions or business dynamics evolve.
Stage 4 – Advanced Financial Analytics
Further to operational KPIs, a proactive approach to predictive financial analytics can elevate any outcome. Here, data becomes a strategic weapon, empowering finance and other teams to focus on driving the business. This is done with:
- AI/Predictive insights: Leveraging advanced analytics tools and modelling techniques allows you to anticipate future financial performance and make data-driven decisions that position your business for success, for example consider an AI-based forecast. Methods such as statistical analysis or machine learning can also help develop contingency plans or seize emerging opportunities.
- Actionable intelligence: Active analytics doesn’t just present data; it translates it into actionable insights that empower informed decision-making across the organisation, including resource allocation, investments, and overall business strategy. In a retail context this may be optimising pricing strategies to increase sell-through.
So How Do We Embrace More Advanced Finance Driven Analytics?
The good news is, transitioning to a more advanced and finance led analytical approach is achievable. Here’s how to get started on your journey.
- Invest in the right tools: Modern cloud data platforms can streamline data collection, automate manual accounting and reporting tasks and provide a single, consolidated version of the truth for operational and financial data. While self-service data analytics tools like Power BI can provide intuitive, easy-to-use dashboards with drill-down analysis of data to easily uncover opportunities and trends.
- Design & present your finance dashboards effectively: We’ve found it’s important to ensure that data and analytics dashboards or reports are designed to tell a story. For example, placement of graphics should represent the nature, prominence, and sequence of data. If you’re showing cash management, graphics could highlight the current ratio, cash balance and outstanding debts. Visualisations could be tailored to different stakeholder groups based on their information needs and details that aren’t critical should be removed if they don’t aid data interpretation.
- Ensure secure, effective and efficient use of data with the right oversight by developing an effective data governance program: Establish clear guidelines and processes for data collection, storage, and access to avoid sprawl and ensure data quality, security and a consistent version of the truth. Document data lineage from multiple disconnected systems and provide reusability of data assets.
- Embrace New Technologies: Explore the potential of artificial intelligence (AI) and machine learning (ML) to automate tasks, identify hidden patterns, and generate predictive insights, especially in FP&A processes to generate more accurate forecasting, efficient resource allocation and proactive risk management.
- Build a data-driven culture: Empower your finance team with data analysis skills and encourage a culture where data is valued and readily used to inform decision-making across all levels of the organisation.
- Supplement your team with the right data and analytics skills to help you determine and implement the analytics capabilities you’re going to need.
By changing company data from being a limited set of numbers to an insightful, operational decision-making tool, you can better leverage your financial information to make clear business choices. With near real-time insights and predictive capabilities, companies led by progressive finance teams can transform from a passive observer into a powerful driver of strategic advantage, gaining a competitive edge, optimising financial performance, and achieving long-term success.
