Democratising financial projections for the age of SaaS

Stacks of money.

Democratising financial projections for the age of SaaS An incurable evangelist of cloud security, data protection and cyber risk awareness, Asim Rahal is a Detroit-based independent IT service provider.

More than 650,000 companies in the United States use Excel to create financial projections. While Excel is surely a versatile tool, it forces manual processes onto finance departments and essentially hinders collaboration.

Companies were locked into Excel in the past because cloud-based budget management and financial reporting software were only targeted at enterprises. These days, however, advanced SaaS solutions that automate financial processes are available for companies of all sizes. These products allow companies to increase collaboration between their departments to create better projections while maintaining data integrity.

Here are five functions that benefit from increased democratisation, no matter the size of your business.

Modeling assumptions

Given the importance of financial data, the legacy practice of giving only finance employees access to it doesn’t make sense. True business insights are unlocked by democratising access, since finance employees cannot know all business assumptions when creating pricing models and market projections.

Higher-level executives can play around with various calculations such as unit economics, operating costs, inflation, and interest rate changes, improving their precision when projecting profitability and revenue. By creating models that incorporate different assumptions, companies can rely on the ones that make the most sense.

More importantly, everyone in the organisation can contribute to these models by providing their inputs. For instance, manufacturing departments can provide much better estimates of upcoming capital expenditures than the finance department can. The result is accurate financial models that have real-world relevance.

What-if scenario creation

Most businesses look at financial projection and analysis (FP&A) solutions as tools to project costs and create budgets. This view explains why so many of them continue to stick with Excel.

However, modern solutions do much more than just tally costs. They allow companies to model the effects of costs and business assumptions on empirical bottom-line figures. For instance, companies can create different financial models and project their impact on revenues and cash flow. Analytics of this kind helps companies identify key business drivers.

For instance, a company may need to determine whether to allocate capital towards an improved manufacturing process or marketing. By entering the respective costs and assumptions of both choices, companies can create models that reveal bottom-line impact in an easily understood format.

Best of all, they can do this from within Excel if they wish to minimise workflow disruption. Software these days can integrate with Excel with cloud databases and other business intelligence tools to provide deep analysis abilities without requiring users to change their workflows.

Incorporate data from various sources

One of the reasons monthly closes and budget forecasting is tough is because companies have to incorporate data from a wide variety of departments and sources. Each department has its own data formats and structures – or lack thereof – and the typical solution is to create a shared file that everyone can access.

The issue with this approach is that data integrity is compromised. An electronically synced solution makes all of these challenges redundant since integration takes place in the background. Once these integrations are set up, employees can view data on a single screen, within Excel, or on a SaaS dashboard.

Since integration is electronic, version control and establishing a single source of truth is simple. Most software automatically record data changes and provide users with version histories. Thus, no matter how complex or varied a company’s financial data sources are, they can slice and dice them as if everything was on a single platform.

Easy visualisation and exporting

One of the challenges of data analysis was that users needed technical knowledge. Without the ability to query databases, business users had to rely on IT or technical teams to mine their data. Needless to say, the chances of goals getting lost in translation were high.

Thanks to the development of software UI, non-technical users can quickly query data and retrieve results instantly. Smaller companies can use these platforms as well, thanks to the ease with which they can be set up.

Best of all, users can create dynamic dashboards that use live data. As a result, comparing metrics, projecting trends, and creating better projections is simple. In addition, teams can even unearth relationships between metrics if they exist.

Exporting these live dashboards is simple thanks to the integration with standard reporting tools such as Excel or Powerpoint. Organisations can create reports and embed live dashboards that always present accurate data.

Automated scheduling and ad-hoc analysis

Ad-hoc reporting is arguably the biggest advantage of democratising financial data. All employees in the company can instantly run reports using data points of their choice. Users in business units can retrieve insights on the fly when in meetings or presentations.

One of the challenges of ad-hoc analysis is enforcing proper data analysis frameworks. Non-technical users might end up creating reports that are biased and drive their organisations down the wrong path. Parameterised reports are a solution to this problem.

Companies can schedule these reports for preset times and populate them automatically using business data. Thanks to the dynamic data element, these reports will update themselves automatically, and no one will have to manually prepare and send them to recipients.

Greater access, better analysis

Data analysis doesn’t have to be siloed these days. Businesses of all sizes and users of all abilities can query data and derive insight from them. Democratising data analysis will, therefore, result in better financial projections and more accurate company cash flow analysis. Given their importance to bottom lines, these are desirable outcomes for all businesses.

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