Business analytics and scenario modeling are staples at companies that use data to inform their growth strategies. Given how quickly business conditions change, thanks to technology reducing competitive barriers, finance, HR and other executive leaders must spend time modeling the impact of their decisions before pulling the trigger.
Payroll data is an underrated source of insights when modeling scenarios. Typically, companies value their MIS, CRM, web traffic and product pipeline data, and payroll as an afterthought. However, payroll data is a fundamental input to every model.
Here’s how good payroll management ensures high levels of data integrity and results in more accurate company data analyses.
Better right-sizing analysis
A company’s workforce is its most valuable asset. Unfortunately, optimal headcounts are tricky to model, leading to situations where companies have to resize.
Getting your workforce size right is critical, though – hire too few people, and you’ll find it hard to scale. Hire too many, and you’ll risk having to let people go when times get rough, creating attrition and damaging employee morale. The costs of furloughing staff are considerable, especially when one considers hiring and training costs.
Workforce capacity planning is therefore a core responsibility when projecting growth, and these models feed into decisions at key junctures. If a company is facing challenging times, its workforce model informs it whether a hiring freeze is more appropriate than reducing workforce counts. When a company scales, it’s all about projecting the number of hires and accounting for their contribution to revenue.
Payroll data plugs directly into these analyses, since it is the investment a company has to make to realize a return.Processes such as metadata management, defining data collection guidelines upon hiring new employees, and storing data in easily accessible infrastructure assist workforce scenario modeling.
Companies that centralize and integrate their payroll data with broader financial modeling platforms can access insights quickly and create the right growth paths.
Accurate expansion scenario modeling
Every successful company eventually contends with expanding into new territories and markets. Unfortunately, expanding the wrong way can make a company a victim of its own success, and expansion plans can go wrong in several ways. A company might underestimate hiring costs, regulatory filing needs, and market size.
While no company can predict business outcomes with full certainty, scenario modeling goes a long way toward understanding the impact of known variables. Hiring costs are the biggest variable in this case. Should your company invest in opening a new physical office, or should it adopt a virtual workspace?
Should the company engage an EOR and use it to hire employees? Or hire them as contractors? These questions have several financial implications. An expansion scenario plan takes them all into account by plugging in different numbers and giving financial analysts an outcome they can quantify.
These figures play an important role in board meetings, where executives must justify their decisions before executing them. Payroll data is a central input to these plans, because modeling the potential investments in salaries and compensation models needs to be complete before deciding to expand into a new market.
For example, the company might find that changing its compensation structure might better address new employee needs, translating to savings on hiring costs. Expansion models have several variables to account for, and integrating payroll data for further analysis is pivotal.
A company that manages its payroll data per best practices will always have a step on the competition, thanks to the insights these datasets offer when integrated with broader financial data.
Structured business data integration
To know where a company is going, its executive leaders have to understand where it’s been. Traditional financial data, including payroll, is backward-looking and cannot predict the future. However, it plays an important role in informing management about trends and pitfalls to watch out for.
For instance, increasing payroll costs might point to inefficiencies in department budgets. This trend also points to potentially flawed assumptions.
A company might have hired more salespeople in anticipation of increased revenue. However, due to delayed product releases, sales might have stagnated, leaving salespeople with unachievable quotas. The issue in this scenario might be a lack of developer and testing resources that create product delivery delays.
Payroll data is a critical cog in a company’s business analysis process. The trends it reveals tell companies how well their plans are going and help them project profits in the near future. Good payroll management is thus critical to ensuring companies receive all the insights they need to future-proof their businesses.
Savvy payroll data management also gives the board and potential investors a picture of company growth. Increasing workforce sizes and subsequent payroll increases let investors know if a company is managed well. Metrics like revenue per employee and average compensation per employee give investors a quick way to measure management efficiency.
Well-organized data can therefore lead to further opportunities for the company, especially when times are tough.
Payroll management for strategic analysis success
Payroll information is not the most exciting dataset companies can draw from. However, these signals are crucial for planning company growth. From workforce and expansion planning to business efficiency analysis, payroll plays a key role in informing executives of their positions, helping them plan for the future.
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