AkzoNobel Centralizes Data with Genie to Enhance Decision-Making
With Genie Agents enabling natural language queries, AkzoNobel has transformed how its leaders access critical insights, moving from a chaotic dashboard environment to streamlined, instant responses that drive smarter decision-making.
Key Facts
- AkzoNobel reduced ERP systems from 50 to 4, streamlining operations and enhancing data accuracy.
- Genie Agents improved decision-making speed, turning complex queries into instant insights for leaders.
- Centralizing finance data on Databricks cut response times from months to seconds, boosting agility.
- Early skepticism about Genie shifted as it revealed critical insights, enhancing user adoption and trust.
- Trust in Genie was established through clear standards, ensuring reliability and reducing data discrepancies.
Summary
Summary
AkzoNobel, a global paints and coatings company, faced significant challenges with data accessibility and dashboard overload due to its fragmented ERP systems. By centralizing its finance data and implementing Genie Agents on the Azure Databricks platform, AkzoNobel transformed its data analytics capabilities, resulting in faster, more reliable insights for decision-making.
Background
AkzoNobel operates in over 150 countries and employs more than 30,000 people. The company, known for its coatings used in various high-profile projects, had a complex IT landscape built through numerous mergers and acquisitions. Prior to deploying Genie, AkzoNobel managed over 50 ERP systems, each with separate analytics, leading to inconsistent processes and KPI definitions. This fragmentation resulted in slow data retrieval, often taking months to answer enterprise-wide questions.
Challenge
The primary challenge was the inability to quickly access reliable data for decision-making. The existing dashboard overload failed to provide timely insights, leaving leaders to make guesses or rely on outdated information.
Solution
AkzoNobel centralized its IT infrastructure, reducing its ERP systems from over 50 to just four. The company consolidated its finance data into a single instance with a harmonized general ledger and migrated to a lakehouse architecture on the Azure Databricks Data + AI Platform. This foundation allowed the team to integrate SAP-based finance data and develop models for key financial metrics. Genie Agents were introduced to enable natural language queries, allowing users to ask questions and receive answers quickly.
To drive adoption, the team collaborated with business analysts to identify critical finance questions and demonstrated Genie’s capabilities. This approach successfully engaged key stakeholders, including the CIO, who became a daily user of Genie.
Results
The implementation of Genie Agents significantly improved data accessibility and decision-making speed. The CIO, initially skeptical, now uses Genie daily, even during his commute. The solution has enabled teams to ask both strategic and minor questions, enhancing overall data-driven insights across the organization.
Key Insights
- Centralizing data systems can streamline analytics and improve decision-making speed.
- Engaging stakeholders early in the deployment process helps drive adoption and trust in new tools.
- Establishing clear standards and ownership for data queries enhances reliability and user confidence.
Customer Testimonial
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Entities Mentioned
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Products
Technologies
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Key Concepts
Definitions
- Genie Agents
- Genie Agents are tools that allow users to ask questions in natural language and receive instant answers, enhancing data accessibility.
- lakehouse
- A lakehouse is a unified data platform that combines the benefits of data lakes and data warehouses, enabling efficient data management and analytics.
- SLA
- Service Level Agreement (SLA) is a commitment between a service provider and a client that outlines the expected level of service.
- ERP systems
- Enterprise Resource Planning (ERP) systems are integrated management systems that help organizations manage business processes across various departments.
- EBITDA
- Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA) is a financial metric used to evaluate a company's operating performance.
Use Cases
- →Natural language queries for finance data
- →Identifying churning customers
- →Answering strategic business questions
- →Providing instant insights for executives
- →Correcting discrepancies in financial data
- →Enhancing data accessibility for analysts
Frequently Asked Questions
What is Genie and how does it work?
Genie is a tool that allows users to ask questions in natural language and receive immediate answers. It leverages centralized finance data and advanced analytics to provide insights quickly.
How did AkzoNobel improve its data management?
AkzoNobel centralized its IT infrastructure, reducing over 50 ERP systems to four, and consolidated finance data into a single instance on the Azure Databricks platform.
What challenges did AkzoNobel face with dashboards?
The company had more dashboards than employees, leading to confusion and delays in obtaining answers to business questions. This prompted the need for a more efficient solution.
How does AkzoNobel ensure the reliability of Genie?
AkzoNobel sets clear standards for each Genie Agent, including ownership, SLAs, and certifications. This helps build trust in the tool among users.
What future developments are planned for Genie?
The team is exploring proactive, contextual, and agentic experiences to further enhance the capabilities of Genie and improve user engagement.