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A high-tech American multinational technology company with an annual revenue of $ 200 Billion and having a humongous employee size of more than 1.5 lakh employees with 8.5 Billion searches per day has its presence in 50 countries focusing on online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, artificial intelligence and consumer electronics. The company's innovative approach to organizing and providing access to vast amounts of information has transformed the way people interact with the digital world. With its headquarters located in Silicon Valley, this influential company continues to shape the digital landscape and impact various industries worldwide.

  • ~$200B Revenues
  • ~1.5 lakhs+ Employees
  • ~8.5B Searches/Day
  • 50 Countries
  • Distributed Financial Forecast, OPEX, CAPEX planning with multiple spreadsheets
  • Multiple manual steps for planning
  • Historical & planning data access was cumbersome with limited access to centrally stored data
  • Granularity mismatch between units data & financial data in existing system reduced forecast accuracy

  • Financial Forecasting

    Forecasting to predict future trends and changes in KPIs, and budgeting to get a roadmap for allocating resources to achieve financial goals.

  • CAPEX & OPEX Planning

    Internal reports used to run the organization, make business decisions, and monitor progress to make more accurate, data-driven decisions.

  • Scenario Planning (What-If)

    Proactive planning for uncertainties, enhance resilience, and adapt swiftly to changing circumstances.

  • Management reporting

    Internal reports used to run the organization, make business decisions, and monitor progress to make more accurate, data-driven decisions.

  • Unified Finance forecast, Opex, Capex for all hardware devices team members to forecast all cost & revenue details at a detailed granularity of products, cost center, channel & location
  • Streamlined data integration & mapping to match detailed hierarchies to ensure accurate forecasting at detailed levels
  • Multiple workflows implemented – forecasting, annual planning & budget adjustments
  • Sparsity deduction & manual mapping for hierarchy to control the model size
  • Overall planning cycle time improvement from weeks to 4 days
  • Data accuracy improvement by 30%
  • Easy maintenance, faster data load and validation
  • Increased forecast accuracy due to detailed hierarchy levels
  • Access & security replicated from central backend system to drive uniform access across all financial systems

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