The 4 Stages of Business Observability

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6 min read
A transparent illustration of four hollow circles in sequential order, each with different designs, surrounded by a cylindrical line with arrow, to demonstrate the 4 stages of business observability

Outlining the business observability stages

Business observability focuses on the performance and key metrics of your entire company. It involves broad data sources such as marketing platforms, customer feedback, and sales data.  

With such a wide range of capabilities, breaking up the stages of business observability is the best way to understand its full potential.

These stages provide a comprehensive and actionable way to improve your organization's day-to-day health and performance. They include:

  1. Collect
  2. Detect
  3. Inspect
  4. Act


Gather and manage data from various sources throughout the organization to establish and improve KPIs.


Independently track KPIs in real-time and detect unusual activity. Using artificial intelligence and machine learning models, quickly identify patterns, problems, and opportunities across critical metrics.


Comprehend the data and insights produced to draw timely insights. Analyze the root causes of problems and inspect anomalies with contextual information about each phenomenon.


Notify appropriate stakeholders quickly to address the insights, issues, and anomalies identified. This is made possible through real-time monitoring, intelligent alerting features, and vital collaboration and communication integrations. 

Collect: the first stage of business observability

How you collect and connect data makes up the critical first stage of business observability.

Collecting data provides the information needed to monitor and measure the performance of a business. Connecting data is effectively squeezing the most juice from your data possible.

Collection capabilities

When assessing the software's collection capabilities, consider the following:

  1. Scalability: Collect and process large amounts of data efficiently
  2. Flexibility: Adapt to different types of data and changing business needs
  3. User-friendly interface: Easy to use, with or without technical expertise
  4. Real-time data: Access real-time information for fast decision-making
  5. Security: Maintain confidentiality and privacy by protecting data
  6. Integration: Reporting, analysis, and visualization tools (e.g., Looker, DBT)
  7. Support: Offer guidance when integrating different data sources

Connector Types

The more connectors a business observability software offers, the wider range of businesses it may support. The first stage of business observability involves having software connectors that support data integrations from:

  • Third-party tools
  • Internal databases and data warehouses

Some business observability software connectors may include:

  1. Cloud connectors: Cloud-based systems and services like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. The software can process this data to monitor and analyze business metrics.
  2. Database connectors: Both relational databases (e.g., MySQL, PostgreSQL, Snowflake, Big Query) and non-relational databases (e.g., MongoDB, Cassandra). 
  3. Application connectors: Like customer relationship management (CRM) systems, e-commerce platforms, and marketing automation tools. 
  4. Custom connectors: Monitor and analyze metrics specific to your operations, even if they are not supported by other connectors in the software. 

Detect: the second stage of business observability

Having all the data is great. But what you draw from it is the next stage of business observability.

The detection stage of business observability is like accessing the optic nerve of your organization. Detection is understanding how operations are performing, so you can manage your business smarter.

One of software’s smartest capabilities is automatically generating insights from your KPIs, eliminating countless hours manually poring over data. Machine learning algorithms and other tools spot data trends and patterns, so you can stay on top of potential issues and keep things running smoothly.

Insight attributes

Making important decisions is about having all the necessary information. That's where insights come in.  

An insight is a clear, concise piece of information that helps you understand what's going on in your business.  

Backed on solid data analysis, it should guide you on what to do next. Here's what you can expect from an insight:

  • A description of the issue or phenomenon
  • Data sources used to identify it
  • Key findings from the data
  • Implications of those findings
  • Suggestions for further investigation or action

Insights are the roadmap for your next steps, keeping your business moving in the right direction. 

Inspect: the third stage of business observability

The next stage in business observability is going further in depth to inspect key drivers and contributing factors of change.  

This pillar allows users and stakeholders to understand how insights are drawn, amplifying the validity, reliability, and relevance of their conclusion.

For example, the software might collect an e-commerce business’s performance metrics (orders, average order value, number of transactions, etc.). Through data analysis, the software identifies increased payment failures during peak traffic periods.  

This could be a potential issue affecting user experience, leading to lost sales.

Inspection capabilities in this stage of business observability give specific root causes on where these increased payment failures originate — through any device or browser — so the payment provider can take swift corrective action.  

Personalized insights

Since one size doesn't (usually) fit all, insights need to be molded specifically to your needs, interests, and preferences. Here's how this stage of business observability achieves that:

  • Behavior: Use data and analytics to understand past behavior and configurations, identifying trends and patterns relevant to each person
  • Display: Configure insight presentation and format, matching each person's learning preferences and visual needs
  • Follow-up: Provide options for further exploration and action, such as links to related data, resources, or suggestions for next steps

Personalized insights are more engaging and relevant to the user, building trust and confidence in the data analysis being presented. 

Act: the final stage in business observability

With insights generated and root causes identified, the final stage in business observability is taking action — amplifying and addressing revealed issues and anomalies.

This business observability stage’s last capability is to inform strategy and operational decision-making, which affect key areas such as product development, marketing, and customer service.

Delivering insights where they matter

The starting point for acting effectively is alerting the right stakeholders. Once the right people have been notified, it's important to analyze findings together, bring up recommendations, and discuss potential solutions or strategies.

Collaboration creates the best plan of action to address the issue and improve performance. Here are some examples of how the final stage of business observability helps you achieve this:

  • In-app feed: Share insights through an in-app feed or report, giving teams an overview of KPIs and trends
  • Email and messaging: Make access to insights seamless by pushing them directly to inboxes, or collaboration tools such as Slack or Teams
  • Ticketing systems: Integrate with existing ticketing systems to incorporate insights into workflows

Your teams will increase performance while reducing issues and anomalies, all by overhauling processes and implementing new strategies through this business observability stage.

Alerting without chaos  

Observable systems identify and surface alerts before end customers are impacted. Ensure insights are delivered without endless notifications — here are some best practices:

  1. Balance: Alert fatigue is real — too many of them make it hard to distinguish signals from noise
  2. Specificity: Alerts should be contextual, personalized, and grouped, giving a concise, yet complete picture
  3. Versatility: Alerts should be sent where people are — communication channels like Slack and Teams, or through ticketing systems 

Why traditional tools no longer work

You've learned about the stages of business observability and which critical capabilities you should look for.  

But why do traditional options like dashboards or standard software monitoring platforms fall short in our modern work environment? 

See why sticking to a business dashboard leaves you vulnerable

Dashboard outline cut off by bars graphic to represent business dashboards

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As your company looks to achieve the best possible results, you need a modern approach to run your business and change your business. The Modern Operating Model brings strategy, teams, and data together to help make decisions faster, optimize operations, and drive better business outcomes.

Whether you’re a large enterprise facing competitive disruption or a small business leading the innovative charge, Quantive helps get you where you want to go.

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