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Monitoring Blockchain Adoption Over Time | A Survey Case Study
By E2E Research | August 10, 2021

Research Objective

  • A global IT consulting and services company needed to identify the stage at which organizations have adopted or are ready to adopt Blockchain technology, a decentralized and highly-encrypted computing platform that is likely to have important privacy and security implications.
  • They were interested in organizations across 5 industry sectors and in more than 15 countries.

 

Scope & Methodology

  • ~3000 online surveys were completed by participants who met the target criteria
    • Employment titles were manager or above
    • Employed at a healthcare, retail, banking / financial services / insurance, or manufacturing company
    • Companies generated revenue of $1 Billion or more
  • A rich B2B database, including industry, designation, and demographic variables, was built which can be maintained over many years

 

Value Delivered

  • The client can now evaluate readiness for blockchain adoption by a variety of key industry, employment, and demographic variables.

 

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Ensuring Optimal Inventory with SKU-Level Demand Forecasting | A CPG Business Intelligence Case Study
By E2E Research | August 3, 2021

Research Objective

  • A US-based manufacturer of personalized gift items with markets in more than 10 countries across North America, Europe and Middle East needed SKU-level demand forecasting to ensure all orders are met while maintaining optimal inventories.
  • Over 3000 SKUs across 8 product platforms with a 3-month lead time needed to be tracked.

 

Scope & Methodology

  • A framework was developed to accommodate weekly re-forecasts based on SKU-level actuals-to-date for repeat customers, varied product platforms, new products, etc.
  • It was designed to learn from historical trends and project future demand.
  • A weekly ‘Early Warning System’ to predict excess and stock-outs was also built.

E2E Research Case Study E2E Research Case Study

 

Value Delivered

  • The forecasting tool helped reduce obsolete inventory at the end of the year which freed up working capital and reduced waste.
  • It also reduced ‘out-of-stock’ rates leading to increased customer satisfaction and revenue, in part due to preventing unnecessary attrition.

 

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