The past decade was defined by unprecedented growth and technological advancement, fueled by a never-ending “more, more, more” mentality. Yet, there is only one constant in business — it’s always changing.
What’s changed?
- Global sociopolitical and economic uncertainty?
- The “first adopter” competitive edge diminishing?
- Outdated methods not working as they should?
This is where the topic of business observability begins. When it comes to your business, and especially your data, “more” is no longer the answer. How we employ and utilize our data at scale seems to be the ultimate question across industries.
But what is business observability, and why are AI-supported solutions suddenly so important?
What is business observability?
You might have heard the term “observability” before. Usually applied in the context of monitoring IT performance or engineering environments, observability has slowly found cross-functional applications.
Business observability is the ability to properly collect and manage business data, then make informed decisions using insights from that data.
Business observability allows you to minimize failure or disruption through a business lifecycle that never stops evolving, granting you visibility into everything happening across your organization and/or teams.
Your company can leverage business observability to:
- Monitor and measure the performance of KPIs in real-time
- Quickly identify trends, issues, and opportunities
- Fuel decision making informed by data
Whether affected by internal or external factors, your day-to-day operations are becoming more complex. Data-informed decision making and business agility are no longer "nice things to have” — they are a necessity in any modern operating model.
Learn more about the modern operating model

So, why should you consider business observability for your business?
Why is business observability important?
Without proper business observability, silos worsen, decisions are made without context, and inconsistencies in your data go unaddressed. This makes detecting and diagnosing potential issues a serious vulnerability, impacting your business and customers alike.
So what is business observability really all about? Automation.
Yes, the buzzword that has infiltrated business rhetoric and every ambitious professional’s dictionary. Business observability and automation go hand-in-hand through three key capabilities:
- Data collection
- Data organization
- Trend identification
Data collection
Automate KPI dashboards and monitoring software by organizing all your data in one place. With one source of truth for all your business data, there’s no shifting between applications or guessing which data is most accurate.
Data organization
Handling the sheer volume of data by our (human) selves is no longer possible. Business observability solutions take your data a step further by improving how you sort and organize data.
Data becomes accessible and insightful with little-to-no manual input.
Trend identification
Business observability solutions go beyond one-way alerts offered by traditional solutions like dashboards — they leverage the power of machine learning and AI to enhance automation.
Data is first inspected without human intervention. Green, yellow, and red flags are identified to users, with key operational metrics providing insight into what’s happening.
As a result, decision-making loops are streamlined and automated, saving your business time and resources.
What's the difference between business dashboards and business observability?
After saying “more, more, more” is no longer the answer for modern businesses, it would be hypocritical for us to suggest having just one “more” solution in your business stack will make all the difference.
Rather, business observability solutions offer both “better” and “more” as a value. Better technical functions and more practical applications, versus more alarms and notifications.
Let’s explore how traditional solutions like business dashboards fall short of your business demands.
Lackluster reporting capabilities
Business intelligence tools and KPI dashboards have been the go-to choice for monitoring performance. We’ve used them to create reports, visualize data, and send alerts.
The problem? Much of this work relies on the assumption that:
- We know what to look for in our data
- We can predict changes before they occur
- We can dedicate all our time to manually monitoring them
Sure, there have been improvements to these tools as the business landscape has evolved. But frankly, one-way business dashboards can’t keep up anymore. Their limited value is no longer sufficient given our greater, more comprehensive needs in the modern world.
Alert fatigue
Over time, data volume has increased and processes have become more complex. The dashboards we currently use not only lack scalability in relation to the growing number of metrics, but can't provide full context into KPI relationships within the organization.
What once helped us distinguish the important now achieves the opposite.
The previous sense of urgency and impact of dashboards has been diluted — we’ve over-notified, over-pinged, and otherwise, dashboard-ified everything to the point that nothing feels important anymore.
This creates three obstacles for the modern business:
- There's a larger scope for things to go wrong
- It’s nearly impossible to identify individual deviations
- Minor overlooked faults can lead to significant repercussions
What’s missing is alignment and focus at the core. Without that, strategy execution falters because nobody knows what to pay attention to or why.
Flat data
Perhaps the greatest opportunity loss with traditional solutions is extracting the most of your data. There’s a wide range to look at and analyze, but the best a static KPI dashboard can do is show surface-level data.
Traditional dashboards and one-off monitoring tools can’t go the extra step when it comes to our data — adding context and depth.
Your modern business requires a solution that doesn’t just display your data, but intuitively processes how complex, intertwined, and nuanced it is. How does a business observability platform account for this? By:
- Going granular with key metrics and qualitative segments
- Uncovering the source of change with root cause analysis
- Sending comprehensive breakdowns of trends and anomalies
Evolving in operations isn’t possible until you can view, analyze, and act on your data in one place.
How you can achieve business observability
Let’s be clear — business observability doesn’t just replace monitoring. It enhances it using data and insights to provide a holistic, comprehensive understanding of your ecosystem.
Business observability provides an adaptive, autonomous, modern approach to data — identify changes, opportunities, and potential issues otherwise impossible with static business monitoring.
Using the power of your KPIs across the organization, business observability guides you toward better decision-making and corrective action when necessary.
Business observability can be achieved using the following framework:
- Collect: Unify data to reduce monitoring complexity
- Detect: Proactively identify changes in business KPIs
- Inspect: Understand the root cause of any unexpected behavior
- Act: Optimize where appropriate or remediate the disruption
Collect data
Business observability starts by capturing the right data.
After all, you can't control what you’re not measuring. As such, the first step is figuring out which business KPIs to monitor and where they’re sourced from, as each set of metrics is unique and configured to user priorities.
For example, in marketing, teams may track a KPI like Average Order Value (AOV) to assess customer segments and refine marketing strategies accordingly. Sales teams, on the other hand, may look at the number of Sales Qualified Leads (SQLs) as a broad metric.
Business observability platforms expand on data collection with the ability to deconstruct each KPI in terms of geography, demographics, device, source, etc.
Detect changes
Once you’ve set up your data collection processes, you'll need to keep an eye out for unusual behavior. Anomaly detection is a core competency inspired by business monitoring.
Examples of anomaly detection include: sudden spikes in check-out errors, shipments taking too long, conversions plummeting, customer churn, etc.
To detect events effectively, you'll need to understand what the typical behavior of each KPI looks like, and if there are any interdependencies between them.
A business observability platform will integrate these complex behavioral patterns into its detection framework, helping you account for their complexities.
Inspect issues
After identifying unexpected behavior, you’ll want to understand what caused it. The underlying reason might not be obvious, as important as other issues, or accurately reflect what’s happening in your operations.
For example, if you're an e-commerce company and you notice an unusual dip in orders, you might assume there's an issue in your online store's payment system. However, the problem could also be in your paid advertising funnel or a simple reporting error in your host’s functionality.
Business observability platforms go a step further in helping you identify and inspect the issue, not just send alerts.
Act on insights
Now you know what happened and why.
The top differentiator in business observability versus traditional business monitoring is taking corrective action — fixing bugs, supporting customers, and correcting issues before they become costly.
On the other hand, if an unexpected change was positive, your platform will help you understand what’s working in your favor and double down for optimal results.
Learn more about the capabilities of a business observability platform

Gain more insight into business observability
You've now know about business observability and what it can accomplish for your business.
Now it's time to deep dive into the business observability process.
Learn about the 4 stages of business observability

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