We have heard repeatedly in the past 12 months, the statement “cash is king”. Yes, that’s true, but in order to sustain such statement (chicken and egg scenario type) we should also adopt the following statement: “data is king as well”.
In today's fast-paced and competitive business environment, data is no longer just an asset—it’s a necessity. For SMEs in New Zealand, the ability to harness data for financial forecasting can make the difference between thriving and merely surviving. As local and global market conditions become more unpredictable, relying solely on historical financial records or gut instincts is no longer enough and 2024 has been a great testament for this within SMEs we work with.
To stay ahead, businesses need to leverage data analytics tools that provide accurate insights and enable informed decision-making.
Forecasting with data analysis is not only a technical skill, but also a strategic and create skill. To become a successful forecaster, you need to develop a range of skills, such as critical thinking, problem solving, research, data literacy, statistical reasoning, scenario planning (especially in the current market environment), storytelling and persuasion.
At Bellingham Wallace, we’ve seen how powerful data analytics can be in helping businesses enhance their financial forecasting, gain a clearer view of their future, and make smarter, faster decisions. In this article, we’ll explore the benefits of using data analytics for financial forecasting and how businesses can harness this transformative tool to improve their performance and growth potential.
1. The Shift from Historical Data to Predictive Analytics
Traditionally, NZ SMEs used to take last years’ financial historical data, apply a % uplift, and that’s it, the financial forecasting exercise for the year was done. While relying on historical information approach has value, it often falls short in rapidly changing markets where future conditions may bear little resemblance to the past. This is where predictive analytics comes into play.
What is predictive analytics?
Predictive analytics uses a combination of historical data, statistical algorithms, and machine learning techniques to identify patterns and predict future outcomes. By analysing data in real time and applying advanced modelling techniques, businesses can gain insights into potential trends and forecast future financial performance with greater accuracy.
Once you have collected your data, you need to analyse it to identify patterns, trends, correlations, and outliers that can affect your forecasts
At Bellingham Wallace, we help businesses move from basic financial projections to predictive forecasting. This shift enables SMEs to not only understand what is happening now but also anticipate what is likely to happen next. Depending on your industry, goals, and resources, you may need to use different types of data, such as historical, market, customer, competitor, or environmental data. The assessment of such data will generate more accurate predictions.
Benefits of Predictive Analytics for Financial Forecasting:
Increased accuracy: Predictive analytics minimises guesswork by using complex algorithms that consider multiple variables and patterns.
Faster decision-making: With real-time insights, businesses can make decisions quickly, allowing them to adapt to market changes as they happen.
Proactive risk management: By anticipating potential challenges or downturns, businesses can put strategies in place to mitigate risks before they impact the bottom line.
2. Improved Cash Flow Management Through Data Analytics
Cash flow is often cited as one of the most significant challenges for SMEs (“cash is king”). Without effective cash flow forecasting, businesses may struggle to manage short-term obligations, plan for future investments, or even stay afloat during periods of reduced revenue. Data analytics tools can radically improve the accuracy of cash flow forecasts, helping businesses predict their liquidity position more effectively.
How does data analytics enhance cash flow management?
With data analytics, businesses can integrate data from multiple sources, such as sales, accounts receivable, payroll, and expenses, and even exchange rates, to get a comprehensive view of their cash flow. These tools allow businesses to track patterns in payment behaviour, identify seasonal fluctuations, and project cash inflows and outflows with greater precision.
For instance, if a business experiences cyclical changes in revenue, data analytics can help predict these cycles more accurately and ensure that cash reserves are optimised to cover leaner periods. Likewise, data-driven insights can help identify late payments or areas where cash is being tied up unnecessarily, allowing businesses to improve collection practices and streamline expenses.
At Bellingham Wallace, we work with businesses to implement advanced cash flow forecasting tools that provide real-time insights, giving them the clarity they need to manage liquidity effectively and confidently plan for the future.
3. Strategic Decision-Making with Advanced Data Analytics
Data analytics does more than just improve forecasting accuracy—it empowers businesses to make strategic, evidence-based decisions. In a competitive market, the ability to make swift and informed decisions is essential. By harnessing the power of data analytics, SMEs can identify trends, evaluate risks, and uncover opportunities that may not be immediately apparent from traditional financial reporting.
How can SMEs use data analytics for better decision-making?
Identifying key drivers of financial performance: Data analytics can help businesses pinpoint the variables that have the greatest impact on their financial performance. This might include understanding the correlation between marketing spend and revenue growth, or identifying which products or services contribute most to profitability. By focusing on these key drivers, businesses can allocate resources more effectively.
Scenario analysis and planning: Data analytics allows businesses to model different scenarios and assess the potential impact of various decisions or market conditions. For example, an SME could use scenario analysis to explore how a price change or exchange rate might affect customer demand or how a supply chain disruption could impact revenue. These insights enable businesses to plan for multiple outcomes and make more resilient strategic decisions.
Customer segmentation and behaviour analysis: One of the most powerful applications of data analytics is in understanding customer behaviour. By segmenting customers based on purchasing patterns, demographics, or preferences, businesses can tailor their marketing efforts, optimise pricing strategies, and improve customer retention. This level of granularity allows SMEs to better anticipate customer needs and adjust their offerings accordingly.
At Bellingham Wallace, we assist businesses in the process of asking the right questions in terms of identifying what information and drivers could impact and alter the strategic direction of your business. We will you implementing data analytics tools that not only improve forecasting but also enhance overall decision-making capabilities. Whether it’s refining product offerings, adjusting pricing models, or developing new revenue streams, data-driven decision-making can transform how businesses operate and compete.
4. Implementing Data Analytics Tools for SMEs
The benefits of data analytics for financial forecasting and decision-making are clear, but for many SMEs, the challenge lies in design and implementation. With the abundance of data analytics tools available, it’s important to choose the right solutions that align with the specific needs of your business.
At Bellingham Wallace, we work with SMEs to identify the best data analytics platforms and tools that can deliver tangible results. We currently work with different tools available in the market. Whether you’re looking to improve cash flow forecasting, enhance strategic planning, or gain deeper insights into your customers, the right tools will empower your business to make smarter, data-driven decisions.
Steps to Implement Data Analytics for Financial Forecasting:
Data collection and integration: Start by identifying the key data sources within your business. This might include accounting systems, customer relationship management (CRM) platforms, and sales data. Ensuring that these systems are integrated is crucial for gaining a holistic view of your business’s financial health.
Choosing the right tools: There are a wide range of data analytics tools available. It’s important to choose a solution that matches your business’s size and complexity.
Training and support: Implementing data analytics tools requires buy-in from key stakeholders within your organisation. Ensuring that your team is trained to use these tools effectively will maximise the value they deliver.
Continuous monitoring and improvement: Data analytics is not a one-time activity. To fully harness its potential, businesses should continuously monitor their performance, update their forecasting models on a rolling basis, and refine their decision-making processes as new data becomes available.
Driving Success with Data Analytics
Data analytics is no longer a luxury reserved for large enterprises—it’s a critical tool for SMEs looking to improve financial forecasting and make smarter, faster decisions. By leveraging predictive analytics, improving cash flow management, and enhancing strategic decision-making, businesses can gain a competitive edge and drive sustainable growth in an ever-changing market.
At Bellingham Wallace, we’re passionate about helping New Zealand businesses unlock the power of data analytics and forecasting. With our expertise, we can guide you through the process of thinking, defining, implementing the right tools, interpreting the data, and turning insights into action. Get in touch with us today to learn how data analytics can transform your business’s financial forecasting and decision-making capabilities.
Author - Jonathan Kogan
