Financial reconciliation processes are a staple at every company. Whether it’s monthly close reports or expense projections, companies need friction-free ways to gain insight into what’s happening with their finances. Unfortunately, financial data processing is a bottleneck at most enterprises.
Despite the rise of sophisticated BI and financial solutions, Excel remains the software of choice for most companies. Through its Office 365 service, Microsoft still sees over 258 million users worldwide. Some 15% of enterprises still use Excel to process financial data despite their size.
Consolidating vast reserves of data through manual processes is a close to impossible task. Excel’s ease of use is undeniable. Many financial reporting teams don’t even realize that they can experience the best of all worlds by automating data consolidation and integrating these processes with their Excel spreadsheets.
Here are six benefits of automating financial data consolidation.
Financial data speaks to the beating heart of a business. It has the potential to tell stories of consumer trends and hidden value drivers. The problem is these insights can be buried within mountains of irrelevant data, and uncovering them might take a long time.
Organizations source their financial data from multiple departments, and aligning them is time-consuming. There are also likely to be data formatting issues that make sharing a single spreadsheet between departments troublesome.
An electronic solution that automates financial data consolidation in Excel will remove these bottlenecks and allow finance teams to start working on data instantly without chasing it. Thanks to preformatted data, running analytics is a simple task, and businesses can gain deep insights into every aspect of their activities.
One of the main roadblocks to data-driven financial optimization in growing businesses is a lack of communication. Thanks to the difficulty of sharing financial data across departments, important data tends to get siloed. Instead of building correlated economic models that can drive insight, they sit separated from the rest of the company.
When this happens, it’s tough for higher-level executives to gain a complete picture of the business. Collaboration opportunities also shrink since it’s impossible to know what another part of the company is working with. As a result, the organization resembles a loosely connected series of features rather than a cohesive unit.
By automating data collection and consolidation, companies can deploy resources to uncover insights. For instance, a trend present in one department might point to a dependency or vulnerability in another. Declining sales in a product might have knock-on effects on an enhancement or an accessory service.
Greater financial integration drives such insights, and automating data consolidation to create a single source of truth is the first step to achieving these results.
Data integrity is at the heart of useful reports. If analysts cannot trust the data they’re slicing and dicing, their words are unlikely to produce much insight. In most organizations, cleaning information is often the most time-consuming task.
Automating data collection removes this hurdle, and a company’s reports can be generated not just faster but in ways that present insights with greater accuracy. Thanks to the shorter time cycles involved in preparing, verifying, and consolidating reports, organizations can act faster.
An automated process also alerts employees of missing and less than perfect data, depending on thresholds specified by departments. For instance, some data might not be available before the month’s end. Reports can take this situation into account and dynamically update once the data becomes available.
From an employee’s standpoint, all they’ll need to do is update their spreadsheet, and the algorithm takes care of the rest.
Large shared spreadsheets are a nightmare for internal auditors since it can be impossible to track cell-level data changes. In the modern regulatory environment, an organization cannot claim ignorance of the cause of changes to their financial data. The reputation loss can be terminal.
Automated processes generate cell-level audit trails and force users to document changes to all values. The result is a digital track record that is verifiable and trustworthy. Thanks to such granular controls, teams can rely on their reports and won’t have to second-guess their data’s validity.
Greater audit control also improves an organization’s insight into their processes and helps them spot weaknesses in the reporting workflow.
One of the advantages that line-of-business data solutions bring to the table is the power to access insights in real-time. Aside from dynamic data feeds, reports can change to reflect real-time business conditions and be modified as available data.
Thus, higher-level executives can run ad-hoc reports in presentations or meetings to gather business information that can impact quickly. In turn, employees with access to the solution don’t need technical expertise since running reports is as simple as clicking data variables on screen.
With easier access to customized reports, companies can make better-informed decisions on the fly and won’t have to rely on rigid, parameterized reports to access insights. Ad-hoc reporting also democratizes data analysis since anyone in the organization can run an account and provide insights that benefit the business.
An organization’s employees are its greatest resource. Deploying their considerable skills on clerical tasks that involve formatting data for unnecessary spaces and commas is wasteful. These activities also damage employee morale.
By automating these tasks, employees can work on analyzing data and adding more value to the organization. They can dedicate time to develop custom metrics and find hidden trends in data instead of worrying about chasing some departments to post their numbers.
These benefits flow upwards as CFOs can dig deeper into financial data and react faster to changes in business trends.
While Excel is a great tool for financial professionals, its lack of automation poses a challenge to organizations. The solution is to automate data consolidation and integrate analytics capabilities into the spreadsheet itself. The result is better insights and faster data analysis, not to mention employee morale.
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