Companies, like humans, can be healthy or unhealthy. In some ways, performing data analysis is an organization’s way of getting a physical exam—by tracking its vital signs, decision-makers can tangibly observe how well their efforts are paying off (or failing to do so). They do this by measuring key performance indicators (KPI) that tell the story of their company’s financial health.
Businesses base their KPIs on their objectives. Obviously, different industries call for a different approach to assigning meaningful KPIs. But in general, there are two kinds of KPIs to consider:
- Lagging: Lagging indicators, like financial metrics, show past results and performance.
- Leading: Leading indicators, like employee engagement, tend to forecast future results because they may lead to a cause/effect phenomenon.
These metrics derived from company data are the signposts on the way to effective decision making. But taking stock of finances requires knowing what to even ask of the data. Here are just four data metrics for measuring a company’s financial health.
1. Inventory Levels
Does your business sell a physical product? If so, you likely have to stock some inventory to ensure order fulfillment goes smoothly (unless you rely completely on drop-shipping). Keeping track of inventory-related metrics over time helps you achieve sales goals, grow revenue and even predict future trends. For example, preparing for an upcoming holiday season often involves looking back on previous seasons as a jumping-off point, then using forecasting to estimate how the economy and trends could affect the next one.
2. Sales Productivity
Looking at inventory and sales levels are both short-term metrics, but they are the building blocks of any long-term plan because they’re bound so tightly with immediate revenue. There are a number of different ways to track sales productivity, depending on your business model and industry. McKinsey suggests a few starters: market share, pricing compared to competitors’, rate of location openings and sales boosts by location.
Using search-driven analytics and ad hoc analysis, companies can engage with company data at every level. This means the sales and finance teams can track sales productivity, while the supply chain specialists can look at inventory specifically. Leaders tend to work with big-picture financial KPIs, while HR personnel look at financial health in terms of metrics measuring turnover and cost of hiring.
3. Overhead Expenditures
Overhead costs are the regular, fixed costs it takes to run a business, from the cost of renting a commercial space to keeping the lights on, the water running and the specialty equipment in working order. It’s easy to forget about this metric in the grand scheme, especially because so many organizations pay bills automatically nowadays. But overhead costs end up having a huge effect on profit margins. Why? Because companies measure overhead costs against adjusted gross income (AGI) as a way to determine financial health. A good rule of thumb is to keep overhead expenses around 20 to 25 percent of AGI.
4. Net Profit
Net income is a bottom-line metric, used in part to determine margins and return on investment (ROI). After you’ve subtracted your total operating expenses from your total revenue, you’re left with net profit. Not only is it important to track this metric over time, but it also provides insight into where your company can tighten up operations.
If your net profit is coming in lower than expected, it’s either because the cost of operation is too high or revenue stream is too low. Taking a high-level look can help identify where you need to drill down into data for more specific answers.
Your Company’s Financial Health
These four data metrics for measuring a company’s financial health are just the tip of the iceberg when it comes to the mighty potential for data analysis. Companies must decide which metrics are useful to them and manipulate their data stores accordingly.
If you are interested in even more business-related stories and information from us here at Bit Rebels then we have a lot to choose from.