With new technologies like AI, ML, and NLP paving their way into markets, much progress has been witnessed in the business intelligence and analytics maturity of businesses across industries. While most of these technologies are not new, advancements in computing power and algorithms have made technology adoption more attractive to middle-market firms looking to establish a competitive position. Though the reason for embracing these technologies may differ from business to business, a few common reasons include the ongoing need to improve operational efficiency, understand customer behaviors, and gain a competitive edge.
Today business intelligence and analytics are helping organizations in numerous ways. While some are applying analytical insights for fraud detection and prevention, risk analysis, and customer behavior analysis. A few other companies are building chatbots and BI based systems that provide intelligence using a natural language interface. Evidently, these technologies know no bounds, and their use cases are expected to grow across industries.
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Improving Business Intelligence and Analytics Maturity – Suggestions from Analytics Experts
Based on a survey, approximately 80% of businesses globally were classified as having low business intelligence and analytics maturity in 2020. Since this metric is directly linked to an organization’s technology adoption ability, it is one of the biggest impediments for organizations looking to drive value in the new normal.
Businesses with low business intelligence and analytics maturity levels are distinctly characterized by traditional data management methods and the lack of in-house analytics capabilities. Data quality issues, inconsistent processes, and poor coordination across the enterprise are rampant in the initial phases of data and analytics maturity since organizations often lack the ability to exploit advanced analytics. To tackle this challenge, organizations must implement the right tools, effectively train their employees, and ensure continued support to garner the benefits of BI and analytics.
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Apart from these aspects improving business intelligence and analytics maturity is a multi-factor problem and includes issues associated with technical infrastructure, organizational capabilities and skill levels, business culture, and ability to leverage existing data. In this article, our analytics experts shed light on few strategies to augment your organization’s business intelligence and analytics maturity.
This analytics maturity assessment was created to help our analytics experts understand your data and analytics maturity levels and gain insights into how your current investments drive organizational value.
Establish a robust, organization-wide data governance model
According to our analytics experts, organizations with low business intelligence and analytics maturity lack a unified data governance model, crucial for data management and insight generation. To succeed, these organizations must establish rules that align with their business goals and monitor them to prevent maverick spending. A robust data governance model can strengthen business objectives and empower businesses to capitalize on new opportunities while mitigating long- and short-term risks.
Leverage technology and deploy modern business intelligence and analytics platforms
Integrating data from multiple databases and storing it in a centralized repository is crucial for businesses looking to succeed in the digital era. Modern analytics platforms are built with these capabilities to enable businesses to analyze data from multiple perspectives and provide future enhancements when it leverages data decisioning.
“Business leaders should consider extending their current analytics platforms to accommodate modern analytics technologies and deploy an advanced analytics maturity model,” said an analytics expert at Quantzig
Create a powerful data strategy
Developing a robust BI-powered data strategy is essential for businesses looking to drive value through data and analytics implementation. Therefore, businesses should develop a holistic BI strategy with a roadmap that defines goals and KPIs for analyzing performance. Most importantly, businesses must develop a data strategy that aids the efficient allocation of resources to create value through BI and gradually extend the scope to enhance their BI and analytics maturity.
Foster improvement and develop capabilities
According to Quantzig, data and analytics leaders across organizations should focus on implementing a flexible working model that facilitates democratic access to technologies and platforms. This enables businesses to expand the scope of their strategies and share insights across teams, ensuring all business units work in tandem. To gain insights into the role of business intelligence and analytics in driving process improvements, request for more info right away!
Based on these insights, it is evident that early adopters of business intelligence and analytics will gain a competitive edge. Those in the initial phase of implementation will ultimately move up the analytics maturity ladder and witness an organization-wide change with time. However, all of this depends on your business’s ability to adapt and build the necessary capabilities and technology expertise in artificial intelligence, machine learning, and NLP, along with data-backed strategies focused on achieving business goals.