Top Five Business Users' Challenges with Analytics

3 min read
Jul 2, 2024 9:18:10 AM

What are the Top Five Business Users' Challenges with Analytics?

Business users face several significant challenges when it comes to effectively utilizing analytics, each impacting their ability to derive meaningful insights and make data-driven decisions. We explore each area and conclude with a short segment on how eyko helps users overcome many of these challenges.

1. Data Accessibility and Integration

One of the biggest challenges is data accessibility and integration. Business users often struggle to access the data they need due to data silos within the organization. These silos can be caused by disparate systems, inconsistent data formats, and lack of integration between different departments. This fragmentation makes it difficult for users to obtain a comprehensive view of the data, which is essential for accurate analysis. Moreover, even when data is accessible, it might not be in a usable format, requiring significant effort to clean and prepare it for analysis.

2. Data Literacy

Another major challenge is the lack of data literacy among business users. Many business professionals do not have the necessary skills to analyze and interpret complex data sets. This skills gap can lead to misinterpretation of data, incorrect conclusions, and ultimately poor decision-making. To address this issue, organizations need to invest in training programs to enhance data literacy across all levels. Providing user-friendly analytics tools that offer intuitive interfaces and guided analysis can also help bridge this gap, making it easier for business users to work with data.

3. Deriving Actionable Insights

The third challenge is the difficulty in deriving actionable insights from the data. Even when business users have access to data and the necessary skills to analyze it, they often struggle to translate analytical findings into actionable business strategies. This challenge is compounded by the sheer volume of data available, which can be overwhelming and lead to analysis paralysis. To overcome this, organizations need to focus on providing clear, concise, and contextually relevant insights. This involves leveraging advanced analytics techniques, such as machine learning and AI, to highlight key patterns and trends, as well as implementing effective data visualization tools that can simplify complex data and make it more digestible.

4. Data Quality and Accuracy

There are also issues related to data quality and accuracy. Inaccurate or incomplete data can lead to faulty analyses and misguided decisions. Ensuring high data quality involves implementing robust data governance practices, continuous monitoring, and regular audits to maintain data integrity. Business users need to have confidence in the data they are using; otherwise, the insights derived from analytics will be unreliable and potentially harmful to the organization.

5. Lack of Alignment Between Analytics Initiatives and Business Objectives

Finally, there is often a lack of alignment between analytics initiatives and business objectives. Analytics efforts must be closely tied to the strategic goals of the organization to be truly effective. Business users may struggle to see the relevance of analytics to their specific roles and objectives if there isn't a clear connection to business outcomes. To address this, organizations need to ensure that analytics projects are driven by business needs and that there is a clear line of sight between data insights and business impact. This requires strong leadership, clear communication, and a culture that values and promotes data-driven decision-making.

How eyko helps users overcome these challenges?

eyko empowers business users to quickly and easily combine data from multiple sources into reports, dashboards, and A.I. insights in one integrated solution – designed for business users.

1. Data Accessibility and Integration: eyko automatically understands data sources, transforms, and cleans the data without requiring deep IT skills, thereby enabling business users to overcome the challenges of data accessibility and integration.

2. Data Literacy: eyko makes it easy for business users to ask tough questions of their data. eyko's inbuilt smarts, and the A.I. Assistant makes it easy for users to surface trends, patterns, and correlations without being a data scientist.

3. Deriving Actionable Insights: eyko empowers users to enrich data with classifications, transformations, hierarchies and more so as to surface actionable insights. Combined with the A.I. Assistant, the enriched data enables users to surface actionable insights such as "what customers are at risk of churn?"; "what inventory is about to expire?"; or "what suppliers are at risk of being late?"

4. Data Quality and Accuracy: eyko's data merging, cleaning, and enriching steps ensure data quality is core to the analytics being built and used by business users. It also ensures a single version of the truth by eliminating data silos.

5. Lack of Alignment Between the Business Objectives and Analytics Objectives: Often organizations contain the analytics strategy within the I.T. teams only. With eyko, I.T. and Business Users can each leverage multiple data sources including data warehouses and data lakes to empower insights and analytic inquiries. Users are not constrained by I.T. when they use eyko, yet, I.T. can still focus on building data warehouses and lakes.

In summary, eyko was designed and optimized for users to overcome the current and future analytics challenges. Learn more today or book a demo now.

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