Balancing business stakeholders and data analysts in BI projects: Are you ready to bridge the gap?

As a BI Analyst at a financial organization, I've found that the trick is balancing compliance with useful insights, like creating reports that tick all the regulatory boxes while still showing stakeholders clear customer behavior trends.

Business Intelligence (BI) involves methods and tools for analyzing and presenting data to aid decision-making. Key elements include: Core Components: Data collection, integration, analysis, visualization, and reporting. Tools and Technologies: Data warehousing, data mining, analytics tools, and visualization tools. Key Concepts: KPI dashboards. Benefits: Accurate data, streamlined processing, and informed decisions. Challenges: Costs, user adoption, data quality, and integration issues. Future Trends: AI, real-time analytics, and self-service. Effectively using these elements transforms data into actionable insights for better decision-making.

The difference between a beginner analyst and a pro is the understanding of goals. Sometimes a stakeholder will give you a list of requirements, and a pro knows to ask 'why'. It's very possible to deliver perfectly on the list and the customer can't answer the questions they need or take the actions they expected. A pro asks questions such as 1. What decisions are you trying to make 2. What metrics are most important and why

In BI initiatives, stakeholder objectives include: In order to support organisational goals, there is strategic alignment. Data-Driven Insights: Giving decision-makers useful information. Metrics and KPIs are tracked for assessment purposes in performance measurement. Using data to streamline procedures is operational efficiency. Competitive advantage: Acquiring knowledge to maintain market leadership. User experience: Making sure things are accessible and simple to use. Cost-Effectiveness: Managing expenses and maximising ROI.

Analyst Perspectives in BI focus on: Data Accuracy: Ensuring reliable data. Insight Generation: Identifying trends and actionable insights. Tool Proficiency: Effectively using BI tools. Reporting Quality: Creating clear, useful reports and dashboards. Data Integration: Combining data from various sources. User Requirements: Addressing end-user needs. Problem Solving: Resolving data issues.

Realizar dinámicas de grupo con la participación activa de los involucrados el proyecto en las cuales se expongan y analicen las posibles soluciones en las diversas áreas del negocio. Para ello existen herramientas gerenciales muy útiles como el brainstorming.

Bridging Communication between stakeholders and data analysts involves: Simplified Language: Translating technical terms into accessible language for stakeholders. Frequent Updates: Providing regular progress reports and updates. Feedback Integration: Using stakeholder feedback to improve data outputs. Objective Alignment: Ensuring BI initiatives align with business goals. Collaborative Sessions: Hosting meetings to clarify needs and resolve issues. Training and Support: Offering guidance on BI tools and data usage.

Nowadays, many organizations are focusing on making informed decisions based on insights derived through BI. Although there is a good rate of success, there is also a notable incidence of failure. There are many reasons behind these failures, but I have observed that some BI projects fail due to a lack of clear communication, proper understanding, and alignment with key stakeholders. Without a clear purpose or defined desired outcome, a BI project has a significant chance of failure, even if all criteria are properly followed. With a clear objective, the insights from BI must be communicated to stakeholders in an understandable language by simplifying technical terms, trends, and analysis. Storytelling is one approach to bridging this gap.

Realizar dinámicas de grupo con la participación activa de los involucrados el proyecto en las cuales se expongan y analicen las posibles soluciones en las diversas áreas del negocio. Para ello existen herramientas gerenciales muy útiles como el brainstorming.

Realizar dinámicas de grupo con la participación activa de los involucrados el proyecto en las cuales se expongan y analicen las posibles soluciones en las diversas áreas del negocio. Para ello existen herramientas gerenciales muy útiles como el brainstorming.

Process Integration in BI involves: Data Consolidation: Combining data from various sources into a unified system. Workflow Coordination: Aligning BI processes with existing business workflows. System Compatibility: Ensuring BI tools work seamlessly with other software and systems. Automation: Implementing automated processes for data collection, analysis, and reporting. Consistency: Standardizing data formats and procedures across the organization. Continuous Improvement: Regularly updating and refining processes based on feedback and performance.