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Empowering General Mills With Stronger Data & Tableau Capabilities

A structured Tableau training and consulting program that helped General Mills’ Supply Chain and Finance teams build independent analytics skills and improve decision-making through effective data visualization.

Client Overview 

General Mills, a global leader in the food manufacturing industry, aimed to strengthen the analytical capabilities of its Supply Chain and Finance teams. To support data-driven decision-making, the organization sought structured training and expert guidance in Tableau.

Objective

To equip internal teams with the skills needed to independently analyze data, build dashboards, and drive operational decisions using Tableau.

Participants

  • Supply Chain Analysts

  • Finance & Reporting Teams

  • Business Intelligence Enthusiasts

  • Functional Managers who rely on data visualization for strategic planning

DGTL's Strategic Approach

DGTL Innovations delivered a focused, hands-on learning experience combining foundation, advanced skills, and expert consulting.

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Training Modules Delivered

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  • Base Training on Tableau
    Introduction to data visualization, dashboard creation, data prep, and reporting for Supply Chain & Finance teams.

  • Advanced Tableau Training
    Deep dive into calculated fields, advanced charts, data blending, complex dashboards, and real-time case scenarios.

  • Expert Consulting for Tableau
    Guidance on optimizing existing dashboards, improving performance, structuring data, and aligning Tableau workflows with General Mills’ business needs.

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DGTL Innovations designed a structured, immersive, and application-driven learning experience tailored to the operational workflows of General Mills.

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1. Instructor-Led Interactive Sessions

  • Each module was delivered live by certified Tableau practitioners.

  • Concepts were explained using examples relevant to supply chain, finance, and reporting.

  • Sessions encouraged active participation, questions, and open discussion.

 

2. Hands-On Practice With Real Business Data

  • Participants worked on datasets similar to General Mills’ internal environment.

  • Practical exercises included building dashboards, cleaning data, and modeling KPIs.

  • Real-world use cases helped teams understand how visualization supports operational decisions.

 

3. Step-by-Step Dashboard Development

  • Trainers guided the team through the complete lifecycle of dashboard creation—from data import to visualization and storytelling.

  • Focus areas included layout structuring, interactivity, filters, drill-downs, and performance optimization.

 

4. Collaborative Problem-Solving & Group Activities

  • Teams worked together on mini-projects to reinforce learning.

  • Group exercises encouraged cross-functional collaboration between supply chain and finance participants.

 

5. Real-Time Q&A and Troubleshooting

  • Trainers addressed queries as participants built dashboards, ensuring immediate clarification.

  • Specific challenges related to data formats, visualization logic, or KPI mapping were addressed live.

 

6. Post-Training Assistance & Expert Consulting

  • DGTL provided guidance for improving existing dashboards used within General Mills.

  • Consulting covered data structuring, performance tuning, visualization best practices, and aligning dashboards to departmental objectives.

Outcome

  • Strengthened Data Literacy: Participants gained clear understanding of visualization best practices and Tableau fundamentals.

  • Improved Reporting Efficiency: Teams could build dashboards independently, reducing reliance on external support.

  • Better Decision-Making: Enhanced capability to analyze operational, financial, and supply chain metrics visually.

  • Consistency in Reporting: A standardized approach to dashboards and data stories across departments

Conclusion

The Tableau training and expert consulting delivered by DGTL Innovations empowered General Mills teams to transition from basic reporting to insight-driven analytics. This initiative strengthened their internal capabilities and supported a culture of data-backed decision-making.

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