insightsoftware, the comprehensive provider of solutions for the Office of the CFO, released Embedded Analytics Insights for 2024, a research report in partnership with Hanover Research uncovering the embedded analytics priorities, trends, and challenges of modern developer teams. The data highlights why developers decide to build or buy analytics functionality and desired analytics features, including customizable dashboards, data preparation tools, and interactivity capabilities.
“In an increasingly digitized workplace, the race for application innovation is relentless in today’s fast-paced technology market. The result is increased pressure on developers, with more customers viewing dynamic, intuitive analytics as a make-or-break application capability,” said Jay Allardyce, General Manager, Data & Analytics, insightsoftware. “When deciding to build or buy analytics, development teams must carefully whether they have the skills and resources to build and maintain advanced analytics that meet rising customer expectations.”
The report found that organizations spend 30 hours or more per week addressing analytics challenges, including building customer-specific content (33%), mitigating performance issues (25%), and correcting data inconsistencies (25%). This can be incredibly costly, with organizations spending $115,856 per developer yearly to tackle these common concerns. In response, developers must consider the time, money, and other valuable resources saved by investing in tools that enable users to investigate data and customize it to address their specific business needs more efficiently. The report echoes this sentiment with 80% of buyers saying customizable dashboards influence their investment decisions.
When organizations save on the resources it takes to establish effective embedded analytics functions, they can turn their attention to advanced analytics features like predictive analytics and generative artificial intelligence (GenAI). Five years from now, 84% of developers believe GenAI will be the most important analytics capability. This is not surprising, considering AI has the power to bring detailed analytics to all business users, driving more intelligent decisions that keep organizations ahead of the competition.
Most respondents were happy with their decision to build or buy. But among those thinking the grass might be greener, ‘security and compliance’ was the number one reason they would hop the fence. In the current climate of AI exploration, it makes sense that buyers and builders are more focused on security, the most common hesitance for AI adoption. This data highlights security and compliance as a key priority for any organization investing in advanced analytics. Buyers should seek solutions with robust, tested security features and controls. Builders must carefully consider the cost and skills required for comprehensive, ongoing security maintenance and updates.
“All development teams are feeling the squeeze from leadership to drive more value from their existing technology investments,” said Jay Allardyce, General Manager, Data & Analytics, insightsoftware. “Our research shines a light on the impact an ineffective analytics strategy can have on an organization’s product roadmap and resources. With a customizable, secure, and compliant embedded data analytics solution, developers can remove many common analytics challenges, freeing them to focus on competitive differentiation to drive business value.”
Download the complete findings of the Embedded Analytics Insights for 2024 report here.
Research Methodology
insightsoftware’s Embedded Analytics Insights for 2024 report was developed in coordination with Hanover Research. This independent survey was conducted among 356 developers, IT, and analytics professionals across the United States who participate in the decision-making process for analytics solutions. The survey included a mix of ISVs and other IT teams. The technology decision-makers surveyed were evenly split between buyers and builders of analytics solutions to ensure strong comparison data.
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