You can't manage what you can't measure. Businesses increasingly rely on business intelligence tools to extract insights and drive decision-making. But merely implementing BI platforms is not enough. Understanding how users engage with these platforms and the analytics adoption levels within the organization is critical for maximizing the value of BI investments. This is where tracking BI usage becomes essential.
By tracking analytics usage, businesses can gain valuable insights into how their BI tools are being utilized, identify usage patterns, measure user engagement, and make data-driven decisions to optimize their BI environment.
In this article, we will explore different approaches to tracking user engagement in and through BI platforms and discuss the benefits and considerations associated with each method.
Built-in BI usage analysis
One of the easiest and most direct ways to track user engagement and measure BI adoption is through the built-in usage analysis offered within many BI platforms like Power BI, Tableau, Qlik and others. These reports provide insight into how users interact with the platform, what content they consume, and the overall usage trends.
While many BI tools have this in-built functionality, the level of detail they provide varies significantly.
For instance, Tableau offers quite sophisticated usage tracking features through its built-in monitoring capabilities. Administrators can measure user engagement, content consumption, and system performance. Other popular BI platforms like Looker, QlikView, and MicroStrategy also provide their own built-in usage analysis capabilities. They allow pretty much the same scope of insights: user activity, content usage, and system performance.
Meanwhile, one of the most popular tools - Power BI - provides quite limited analytics with their Usage Metrics Report - it allows users to identify who has viewed their reports, when they were accessed, and which pages and platforms were used. However, they provide only 1 month (3 in the old version) of historical data, which is not enough to understand usage trends and build a strong data strategy.
At the same time, if the built-in analysis was as good as it seems from the outside, all our BI environments would be in perfect order and BI adoption reaching sky levels. Yet, it doesn't happen. And the limitations are to blame.
All inbuilt usage analysis functions have their own restrictions. Different dimensions for analysis, not aligned data structures, and different timeframes don't allow deep analysis, especially if a company has a multi-tool BI environment. This can be a challenge for organizations that require long-term historical data for trend analysis, user behaviour patterns, or security purposes.
Customization - or rather the lack of it - comes as another restriction. While the built-in usage analysis features provide fast insights, they may have predefined metrics, visualizations, or groupings. This can limit the depth of analysis or the ability to tailor the reports to specific organizational requirements. Businesses aiming for advanced analytics management or requiring specific metrics will be bound hand and foot.
25% of organizations use 10 or more BI platforms, 61% of organizations use 4 or more, and 86% of organizations use 2 or more.
Additionally, having analytics scattered all over those multiple BI tools adds to this complexity. As Forrester says, 25% of organizations use 10 or more BI platforms, 61% of organizations use 4 or more, and 86% of organizations use 2 or more.
Imagine each of those 10 tools has its own way of analysing user activities and reports usage. And some of them are out of view at all (like the omnipresent spreadsheets).
It's basically impossible to have a holistic view of user engagement and adoption across various departments, teams, or regions in such a complex multi-tool analytics ecosystem.
All of these limitations show a desperate need for an alternative - a centralized BI usage tracking system. So what now, every company has to dive deep into developing its own system for the purpose?
Doesn't sound perfect, but it's a viable solution. Let's explore how that can be done.
Building Custom BI Usage Solutions
While the built-in usage analysis provided by BI platforms offers fast and effortless insights, organizations with specific requirements, advanced analytics needs or complex BI ecosystems may choose to build their own custom tools extracting usage data and analysing log files with a set of APIs.Building a custom solution offers several advantages.
01
It provides flexibility in terms of data retention and analysis. Organizations can define their own data retention periods, allowing them to capture and store usage data for as long as needed. This is particularly beneficial for organizations that require long-term historical data for trend analysis, working with BI adoption, or compliance purposes.
02
Custom BI usage solutions allow companies to define and track their own metrics and KPIs. Unlike the predefined metrics offered by built-in usage analysis, custom solutions enable organizations to tailor usage tracking to their specific requirements. This empowers businesses to focus on the metrics that matter most to their BI adoption and engagement goals.
03
Building custom tracking solutions gives organizations the ability to integrate usage data from all present BI solutions and even combine it with other relevant data points, such as employee and other corporate data to gain a more comprehensive understanding of user engagement and BI adoption.
However, it's important to note that building and maintaining custom usage analysis comes with challenges. It requires technical expertise in working with APIs, developing data pipelines, and ensuring data accuracy and integrity. Business needs to allocate resources for development, testing, and ongoing maintenance to ensure the newly built system remains robust and effective.
It takes a lot of money, time and gives no guarantee of success.
Wouldn't it be easy to just buy a specialized tool? - you might ask. Well, we believe it is. Let's explore the possibilities out there.
Ready-Made Solutions and Third-Party Tools
Third-party tools have pre-built functionality designed specifically for tracking BI usage. These solutions seamlessly integrate with popular BI platforms and offer a wide range of user behaviour and report utilisation analytics features. They eliminate the need for organizations to develop custom tracking solutions from scratch, saving valuable time and resources.In comparison with other options, specialised tools provide several advantages for organizations seeking to track BI usage analytics.
First, they offer a quick and convenient implementation process.
These solutions are specifically built to integrate with popular BI platforms, making the setup process smooth and straightforward. Organizations can start tracking usage analytics without the need for extensive development or customization.
Second, ready-made solutions typically offer advanced analytics capabilities.
They provide comprehensive reporting and visualization features that go beyond the basic usage metrics provided by built-in tools. These tools enable organizations to delve deeper into user engagement, content consumption patterns, and platform performance.
Third, these solutions often come with user-friendly interfaces and intuitive dashboards.
They provide a centralized and user-friendly view of usage analytics, making it easier for administrators and business users to access and interpret the data. These solutions offer interactive visualizations, drill-down capabilities, and customizable reports, empowering the BI team to explore usage analytics and gain actionable insights.
There are some tools on the market that usually cover advanced usage analysis for a single BI platform and work as an extension - like Power BI or Tableau focused. And it brings great value already.At the same time, offering a comprehensive cross-platform analysis for all BI tools in your company in a single place would be a perfect match.And that is what we aim for with our own tool - Accton Auditor.
INTRODUCING ACCTON AUDITOR
Accton Auditor is a dedicated tool that provides continuous analysis of reports' stats data, user activities, and license utilization in your BI environment. It helps identify areas for improvement in your adoption strategy, control costs and report population while offering customization and scalability to meet specific analytics needs.
How to choose the right approach?
When selecting an approach for BI usage tracking, it's important to consider your organization's specific needs and goals. Here are some key factors to consider:
1. Historical Perspective:
Assess the required timeframe for data. Determine whether built-in usage analysis provides sufficient historical data or whether you need long-term trends for analysis, compliance, or regulatory purposes.
2. Customization:
Evaluate the need for tailored metrics and KPIs. Consider whether predefined metrics offered by built-in tools meet your specific requirements or if a custom solution is necessary to track the metrics that matter most to your BI adoption and engagement goals.
3. Integration and Scalability:
Consider the complexity of your BI ecosystem. If you have multiple BI tools in use, assess the capability of the tracking approach to integrate data from various platforms seamlessly. Additionally, consider the scalability of the solution to accommodate future growth and potential additions of new BI tools.
4. Technical Expertise and Resources:
Evaluate the availability of technical expertise within your organization. Building a custom solution requires API integration, data pipeline development, and ongoing maintenance. Ensure you have the necessary resources and expertise to handle the development and upkeep of a custom tracking system.
5. Time and Cost:
Consider the time and cost associated with each approach. Ready-made solutions offer quick implementation and reduce the need for extensive development, saving time and resources. On the other hand, custom solutions may require a larger upfront investment but offer greater flexibility and customization options.By carefully evaluating these factors, you can choose the approach that aligns best with your organization's requirements, maximizes BI usage insights, and drives data-driven decision-making.
