Earnings per share (EPS) calculates the amount of net profit a company has per outstanding share of its common stock. In calculating this number, organizations can understand their profitability. The higher the EPS, the more profitable it is.
EPS is one of the most prominent line items used to determine how much money a company brings in and their corporate value. The higher EPS is, the more likely investors will pay more for company shares.
How to Calculate Earnings Per Share
On the surface, the formula for EPS seems easy enough. Find the net profits of a company and divide that number by the number of shares. However, this figure can be adjusted.
In the numerator, net income can be adjusted by subtracting the continued operations. This adjustment makes the figure more relevant and realistic. This is important when using EPS to calculate other important company success metrics, such as price-to-earnings (P/E) ratios.
Types of Earnings Per Share
Because there are several ways to adjust EPS, investors look at various types of EPS numbers.
Basic EPS is the simplest way to calculate how much a company makes per their outstanding shares.
Diluted EPS is similar to basic EPS, but this calculation also takes into account the securities that can be converted into common shares, including employee stock options and bonds. Because of this, diluted EPS tends to be lower than basic.
Adjusted EPS is the diluted EPS score with specific line items removed. These line items are atypical costs that can skew the company’s EPS, such as tax credits from previous years.
Each type of EPS can be used for various reports or situations. When comparing two companies, it’s critical that you use the same type of EPS to make your analysis. However, when using EPS to compare year over year growth internally, using adjusted EPS is more accurate because it takes away one off discrepancies.
When to Use Earnings Per Share for Investment
There are many occasions when you’ll want to use EPS to better understand the organization or your competitors.
The first is the PE Ratio, which evaluates the price of a company based on its earnings. This tells investors how much the market is willing to pay for each dollar of earnings.
EPS growth shows you how quickly your company has grown in terms of earnings. This growth can also predict future trends, which gives a good overview of the health of the company.
Dividend payout ratios looks at the return on EPS, or profits, to shareholders. This lets you know the financial sustainability of a dividend. If the payout ratio is higher than EPS, it’s clear that the company is in trouble and cannot sustain that level of earnings.
Earnings Per Share
Earnings per share is much more than a line item on a sheet. It has a direct impact on the organization in several ways.
Take a Predictive Stance
Stock analysts use earnings per share to predict what a company’s revenue will look like ahead of time. This predictive stance can help organizations know where and how to invest so that they stay in the black and in growth mode.
Maintain Product-Market Fit
A lot can be gleaned from looking at how earnings per share fluctuates over time. By monitoring the patterns of growth or decline, organizations can spot how well aligned their offerings are with market demands, or if there’s a need to regain product-market fit.
Improve Employee Experience
Organizations who have teams vested in the company’s stocks know that their employees pay close attention to earnings per share. These earnings directly correlate to the company’s success, and teams can personally feel when their company does well and EPS increases.
Understand Market Alignment
When comparing earnings per share against a competitor’s EPS, companies can understand their position in the market. Monitoring this trend over time lets organizations keep a pulse on their competitive stance and how well their company aligns with market needs.
Customer Experience (CX) Terms
- 360° Degree View of the Customer
- Agentic AI
- AI Ops
- Annual Recurring Revenue
- Behavioral Economics
- Behavioral Insights Matrix
- Behavioral Triggers
- Bow Tie Funnel
- Brick-to-Click
- Business Impact Analysis (BIA)
- Cognitive Computing
- Cohort Analytics
- Content Mapping
- Convergence / Divergence Bands
- Conversational User Guidance
- Customer Data Profile
- Customer Experience (CX)
- Customer Friction
- Customer Insights Map
- Customer Journey
- Customer Journey Mapping
- Customer Satisfaction (CSAT)
- Customized Ratios
- CX Intelligence
- CX Led Growth
- CX Metrics
- Data as a Product (DaaP)
- Data as a Service (DaaS)
- Data Culture
- Data Driven
- Data Engineering
- Data Fabric
- Data Governance
- Data Humanization
- Data Hygiene
- Data Looping
- Data Mapping
- Data Mining
- Data Modeling
- Data Monetization
- Data Swamp
- Data Visualization
- Data Warehouse
- Data-Centric
- Descriptive Analytics
- Diagnostic Analytics
- Digital Asset Management (DAM)
- Digital Transformation
- Dirty Data In Dirty Data Out
- Domain Specific Models
- Embedded Intelligence
- Empathy Mapping
- Employee Data Profile
- Employee Experience (EX)
- EPS
- EX to CX Data Mapping
- EX to CX Mapping
- Experience Management (XM)
- Foundation Models
- Gap Analysis
- Generative Adversarial Network
- Generative AI
- GEO
- Hallucinations
- Human-Centered Design (HCD)
- IRR
- Journey Analytics
- Large Language Model
- Machine Learning (ML)
- Managed Agile Services on Demand
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- MRR
- Neural Network
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- RevOps
- ROAS vs. ROI
- S Curve of Growth
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- StoryVesting
- Table Stakes Testing
- The 3 P’s
- Transformers
- User Experience (UX)
- User Insights Map
- User Interface (UI)
- Vector Database
- Voice of the Customer (VoC)
- Voice of the Employee (VoE)
- Word Cloud Generator Sentiment Mining
- X Analytics