01 · Inspectable sales drivers
Store data, exploratory analysis, and dashboards connected sales movement to measurable operating and external factors.
Customer case study · Quick-service restaurants
Yum Brands put sales-driver and what-if analysis into daily operating decisions
Yum Brands needed to understand changing sales drivers and test response scenarios during a period of rapid demand disruption. BluePi built a cloud analytical path with SQL Server, Amazon EC2, Amazon EMR, and Power BI and released it in a matter of weeks.
What-if analytics for changing COVID-era demand
Yum needed analysts and leaders to understand shifting sales drivers and test responses while trading conditions changed week by week. BluePi and Yum created a cloud-based analytical platform with Power BI, SQL Server, AWS EC2, and EMR.
02 · What-if response testing
What-if analysis let teams examine plausible actions and compare likely outcomes before allocating resources.
03 · Broader dashboard use
The solution went live in weeks, broadened dashboard adoption, sped analysis, improved resource-allocation decisions, and supported business continuity.
Client voice
The customer describes the operating change the project produced.
From store data to decision scenarios
BluePi and Yum brought store data into a cloud analytical platform, supported exploratory analysis, presented dashboards in Power BI, and added what-if analysis for staffing, inventory, and resource-allocation decisions.
Make drivers inspectable
The analytical view connected changes in sales to measurable operating and external factors.
Teams can test a response before committing resources
What-if analysis let teams examine plausible responses and compare likely outcomes.
Design for analyst use
Accessible reports and exploratory paths increased the number of people who could work with the data directly.
Where this pattern fits
This case is relevant when planning assumptions are moving faster than the normal reporting cycle. BluePi can build a bounded decision model around one volatile measure and the actions it controls.
Questions and answers
Direct answers drawn from the case record on this page.
What problem did Yum Brands need to solve?
Yum Brands needed to understand changing sales drivers and test response scenarios during a period of rapid demand disruption. BluePi built a cloud analytical path with SQL Server, Amazon EC2, Amazon EMR, and Power BI and released it in a matter of weeks.
What did BluePi deliver?
Yum needed analysts and leaders to understand shifting sales drivers and test responses while trading conditions changed week by week. BluePi and Yum created a cloud-based analytical platform with Power BI, SQL Server, AWS EC2, and EMR.
What results did the project produce?
The platform went live in a matter of weeks. Sales drivers became visible, what-if analysis supported response planning, analysts gained self-service exploration, and the time from question to action decreased.
Which client, industry, and platform does this case involve?
Client: Yum Brands. Industry: Quick-service restaurants. Platform: AWS and Power BI.
Case details
Open a section to review the customer problem, implementation, business change, and architecture.
01The starting point
Yum Brands needed to identify the factors moving sales, test response scenarios quickly, and allocate resources while demand and operating conditions changed rapidly.
- Make changing sales drivers visible: Yum Brands needed to identify the operating factors moving sales so leaders could direct resources using current sales data.
- Test responses before acting: Teams needed a fast way to compare what-if scenarios while demand and operating conditions were changing.
- Keep decisions moving through disruption: The operating workflow had to support day-to-day decisions during the COVID-19 disruption without waiting for a normal reporting cycle.
02System delivered
BluePi connected store and operating data to SQL Server, Amazon EC2, Amazon EMR, and Microsoft Power BI, creating a cloud analytical path for sales-driver analysis, what-if scenarios, dashboards, and self-service exploration.
- Cloud analytical path: BluePi connected store and operating data through Microsoft SQL Server, Amazon EC2, and Amazon EMR, then presented sales-driver and what-if analysis in Microsoft Power BI.
- Shared analytical workflow: Dashboards and self-service exploration gave analysts and leaders one path from current store data to response scenarios and resource-allocation decisions.
03Outcomes
The platform went live in a matter of weeks. Sales drivers became visible, what-if analysis supported response planning, analysts gained self-service exploration, and the time from question to action decreased.
- Live in a matter of weeks: The platform entered use in a matter of weeks during a period of rapid demand disruption.
- Sales drivers made visible: Shared dashboards exposed the factors affecting sales and gave leaders current figures for resource allocation.
- What-if response planning: Teams could compare response scenarios before committing operating resources.
- Shorter path from question to action: Business analysts could explore the data directly, reducing the time needed to answer operating questions and act on market changes.
04Architecture boundary
Store and operating data entered SQL Server and cloud collection before Amazon EC2 and Amazon EMR analysis. Sales-driver and what-if outputs reached Microsoft Power BI, where analysts and leaders used shared dashboards for resource-allocation and operating decisions.
05What changed for business planning
Sales drivers and response scenarios moved into a shared analytical workflow. Business analysts could explore data directly, while leaders used the dashboards to allocate resources and respond to market changes.
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