Management Performance Reporting:
Many Finance teams depend entirely on Financial ERPs for data, and spreadsheets for modeling. The combination of spreadsheets with legacy systems, containing siloed and large volumes of transactional data, leads to a risk of repetitive manual work, and a shift away from value-adding activities. This can be both time consuming and demotivating, preventing Finance professionals from moving the needle in their roles.
As the need for robust financial and management performance reporting increases, the existing processes can end up extremely complex with different functional heads, business leadership and teams end up unable to extract insights from large spreadsheet reports. This results in back and forth clarifications and questions to the team, which exacerbates work demands. Further, with limitations of spreadsheets in terms of data volume, reports are to be aggregated at a high-level, resulting in missed opportunities for deeper insights.
For instance, a mid-sized business typically has multiple separate softwares in place for budgeting, financial statements and monthly departmental reporting making it extremely difficult to consolidate planning data without tons of manual effort. A single source of truth of all financial information is needed as cutting and pasting data from multiple systems is unproductive. This could be done by automating manual aggregation, unifying business planning with one source of truth for financial data and giving other function's budget owners more ownership over their numbers with workflows, scenario modeling and ondemand reporting capabilities.
2. Budget and Variance Analysis:
Automation of financial statements and reports offers many advantages to the finance team and the business as a whole, not the least of which is increased accuracy and decreased time spent on the creation and review of the reports. When data flows directly from a source system, it becomes a lot more seamless to prepare reports such as a bespoke management report or variance report, without too much intervention from the finance team and the time saved can be dedicated for analysis. More time spent on analysis, means deeper and more meaningful insights. The sooner the business leadership gets timely insights the more agile and adaptive the business can be.
The monthly or quarterly variance report is far more than a simple financial statement. It is a critical tool in understanding how close your company is to the path laid out during the annual budget process. These nuggets of information can only come from an analysis of the report, and a thorough analysis only comes from a timely and accurate report. Automating the creation and updation of the variance data gives time back to the office of finance so that the important work of variance analysis can be done well.
For instance, in mid-sized businesses variance reporting is cumbersome, budget consolidation is tedious and cross-functional collaboration is hard to facilitate. Usually, the important financial assumptions that the businesses rely on for operational planning— such as resource utilization, revenue and payroll expenses—are based on outdated actuals. This results in the finance and accounting teams spending wasted efforts in monthly meetings with department heads in deciphering variances.
A business can standardize and automate the monthly reporting process so that cross-functional teams could start planning from the same page. Solutions to create one source of truth for budgets, forecasts and actuals should be used, which would then reduce the time spent on variance analysis significantly and provide on-demand scenario modeling that enables strategic, data-driven decisions. This would also provide firms with the ability to plan as a team and drive agile decision making based on what-if analysis. And, instead of using out-of-date numbers for reporting, firms could test budget and actuals against any number of future assumptions to always deliver a reliable snapshot of long-term revenue trajectory. This level of insight is crucial for business-wide processes to lower costs effectively.
3. Planning and Forecasting:
Predictive analytics helps predict future trends for accurate planning, forecasting and decision making. It can play a key role here by forecasting the financial health of the business and providing red-flags and early warning systems. Predictive analytics also can be used in a variety of finance processes like predicting revenue, demand planning, analyzing loss drivers and detecting frauds. For example, a commonly used technique in Predictive analytics is Regression analysis which helps determine the relationship between two or more variables (linear and multiple regression). In addition, logistic regression is a commonly used machine learning technique that is used to create predictive models where the outcome of the prediction is a binary yes or no.
For instance, Marketplace businesses work on huge amounts of data. They track everything from engagement to clicks, and databases or websites store customer contact information and interaction history. With data stored in different places, marketing teams often cannot form a coherent, comprehensive marketing strategy and track its effectiveness. The firms could use predictive modeling that uses a customer's purchasing history to inform the firm of the most effective times to market a particular product to that customer. Demand forecasting could also be done using predictive analytics where a specific region of the customer base is analyzed by knowing their preferences and predicting how they will respond when a future demand is created. Predictive analytics could also help reduce customer churn by monitoring affinity for the brand and informing the firm when to take action to stay in good standing.
4.Month-end Close and Reconciliation:
Financial closing is a crucial aspect for any business's success. During the month-end close process, the finance department has the ownership of ensuring that discrepancies are reconciled to provide more accurate financial statements that reflect a company's actual financial state.
Reconciliation is a key part of the account closure process and integral to ensuring tight financial control and compliance. Majority of accounting and finance teams rely on spreadsheet-based templates and macros to support reconciliation. The process is both manual and cumbersome. Summarizing information also becomes difficult as there is a lack of standardization especially when teams have to search through different spreadsheet files that are disparate. They also face pressures from internal and external auditors to get control of the reconciliation process. Businesses need to automate the entire process by developing workflows using automation solutions and rule-based modeling that would lead to seamless processing of high volumes of reconciliations every month. Overall, financial reporting sanctity improves with consistency in reconciliations and standardization.
Three types of reconciliation that could be automated are:
- Bank reconciliation: Automated bank reconciliation enables businesses to quickly and efficiently perform bank reconciliation, especially when multiple bank accounts are in operation. By reading data from source documents such as pdfs and other formats, transforming such data into structured datasets, bank reconciliations can be executed in a fraction of time taken.
- Intercompany reconciliation: The automated process identifies possible mismatches between subsidiaries due to errors in invoicing and other transactions such as loans, deposits and interest received or paid. Automation helps in defining rules to process such data and generating reconciled and unreconciled data in order to minimize bank transaction fees, optimize liquidity, and reduce financial and currency costs as well as risks.
- Asset balance reconciliation: Adjusting the asset additions and depreciation and amortization expenses and tying to the closing balances based on data from General ledger can be implemented and aberrations flagged.
5.Automation in Accounts Payables and Receivables
Accounts payable automation software has revolutionized the way businesses handle their financial processes. This technology streamlines the accounts payable invoice processing, making it more efficient and accurate. With accounts payable automation, the entire accounts payable workflow is optimized, from invoice reception to approval and payment. This not only reduces the chances of errors but also accelerates the accounts payable process, improving overall productivity. Small businesses can benefit from dedicated accounts payable software designed to meet their specific needs, while larger enterprises might opt for comprehensive solutions like NetSuite accounts payable and receivable.
In the realm of accounts payable management, the importance of automation cannot be overstated. The best accounts payable automation software integrates seamlessly into the existing systems, offering end-to-end process automation. One such solution is Yooz AP Automation, which stands out for its ability to facilitate vendor payments and enhance the accounts payable workflow. This software efficiently tackles tasks ranging from invoice automation to approval. Notably, the paperless accounts payable process is a hallmark of these systems, minimizing paperwork and optimizing resource utilization.
Accounts receivable is another crucial aspect of financial operations that benefits from automation. Accounts receivable automation software provides businesses with the means to streamline their invoicing and payment collection processes. This technology, often referred to as AR automation software, ensures that invoicing is accurate, timely, and consistent. Just like accounts payable automation, accounts receivable management software caters to businesses of varying sizes. It offers features such as automated reminders, which significantly reduce the instances of late payments and improve cash flow.
The integration of automation software in both accounts payable and accounts receivable processes has transformed the way businesses manage their finances. From efficient invoice processing to seamless approval workflows, these tools enhance accuracy and productivity.
6.Internal Accounting Audit:
Internal accounting Audit has always been resource heavy, labor-intensive, expensive, and time consuming. Most accounting audit processes involve having to investigate extensive volumes of data. Additionally, the proceedings have to go through various accounting principles, compliance and checklists. Automating allows accounting systems to crunch numbers, identify discrepancies, and flag transactions that require deeper review. Those requiring deeper review can then be taken up by teams where judgmental calls are needed. It has become all the more important now with less time available to detect anomalies in audit reports and errors costing businesses dearly.
In any traditional organization, the internal audit process starts with risk monitoring activities on the macro level and then drilling in to understand how these risks are affecting processes within the company. The first step is to understand the processes. and thereafter equipping the auditors with necessary tools and systems so that they can assess the risks inherent in the business. Automation could be incorporated to remove inefficiencies and reduce the amount of time and effort required to conduct an audit. In summary, firms could realize tangible benefits by implementing automation solutions into the auditing process.
For instance, in a mid-sized business, internal audits are typically carried out by testing only a subset of data (sampling method). This poses a challenge with the chance of missing out on anomalies and outliers very high. Even methods and techniques to investigate cash processing, foreign transactions and adherence to corporate actions are usually non existent. A process-driven automation solution that addresses the reconciliation issues and identifies financial control gaps can optimize the audit completeness, timeliness, quality and accuracy of the tests could be developed. This would let auditors better understand the trends and patterns of the business making it easier to identify anomalies or outliers, among others.
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