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POWER BI · BUSINESS PERFORMANCE

KFC Daily Sales
Performance Dashboard

An interactive reporting solution designed to monitor daily sales performance across a restaurant network, analyse trends and compare results across restaurants, franchisees and sales channels.

Power BIDAXPower QuerySQLData ModelingData Visualization
PROJECT PREVIEWDAILY SALES DASHBOARD
01 — OVERVIEW

Make daily performance
easier to understand.

This project brings daily sales and operational indicators into one interactive Power BI reporting experience. It helps stakeholders monitor performance, follow trends and compare results across the restaurant network.

The solution combines SQL data preparation, Power Query transformations, data modeling and DAX measures to turn raw data into decision-ready reporting.

02 — BUSINESS CHALLENGE

One reporting view.
Clearer decisions.

The objective was to centralize daily restaurant performance monitoring in an interactive report and make it easier to identify variations that require further analysis.

01How are sales performing on a daily basis?
02How does performance evolve over time?
03Which sales channels are driving performance?
04How do restaurants and franchisees compare?
05How are transactions and average ticket evolving?
03 — KEY PERFORMANCE INDICATORS

KPIs built around
business questions.

Measures designed to support consistent performance monitoring and comparison.

01
SSSG

Same Store Sales Growth

Compare sales performance for a consistent set of restaurants against the previous year.

02
SSTG

Same Store Transaction Growth

Track changes in transaction volumes across comparable restaurants.

03
AVERAGE TICKET

Average transaction value

Understand how revenue per transaction evolves over time.

04
SALES / STORE

Sales per store

Compare sales performance at restaurant level.

05
TRANSACTIONS / STORE

Transactions per store

Monitor transaction activity across the restaurant network.

06
COVERAGE

Store coverage

Keep track of reporting coverage across the restaurant network.

04 — DASHBOARD FEATURES

Explore performance
from different angles.

Interactive filters and breakdowns make it possible to move from a network overview to more detailed analysis.

Time-based filtersYear, month, week and business date
Region analysisCompare sales performance across regions
Sales & transaction trendsDaily evolution and year-on-year comparison
Restaurant & franchisee viewsCompare performance across the network
Sales channel analysisBreak down results by channel
05 — TECHNICAL APPROACH

From raw data
to reporting.

A layered workflow separates extraction, transformation, modeling, calculations and visualization.

01SQLData extraction & aggregation
02Power QueryPreparation & transformation
03Data ModelTables & relationships
04DAXKPI calculations
05Power BIInteractive reporting
SQL ASSETSDim_Calendar.sqlDim_Channel.sqlDim_Store.sqlFacts_Daily_aggregate_indicators.sql
Explore the DAX logic

Revenue MDA PY

Revenue MDA PY =
CALCULATE(
    SUM('Fact_KPI_Store_Day_Channel'[Y1REVENUE_HT]),
    'Fact_KPI_Store_Day_Channel'[MDAY0Y1] = "MDA"
)

Revenue MDA

Revenue MDA =
CALCULATE(
    SUM('Fact_KPI_Store_Day_Channel'[Y0REVENUE_HT]),
    'Fact_KPI_Store_Day_Channel'[Y0REVENUE_HT] <> 0,
    'Fact_KPI_Store_Day_Channel'[Y0REVENUE_HT] <> BLANK(),
    'Fact_KPI_Store_Day_Channel'[MDAY0Y1] = "MDA"
)

SSSG — Same Store Sales Growth

SSSG =
[Revenue MDA] / [Revenue MDA PY] - 1

Transaction MDA

Transaction MDA =
CALCULATE(
    SUM('Fact_KPI_Store_Day_Channel'[Y0NBINVOICES]),
    'Fact_KPI_Store_Day_Channel'[Y0NBINVOICES] <> 0,
    'Fact_KPI_Store_Day_Channel'[Y0NBINVOICES] <> BLANK(),
    'Fact_KPI_Store_Day_Channel'[MDAY0Y1] = "MDA"
)

Transaction MDA PY

Transaction MDA PY =
CALCULATE(
    SUM('Fact_KPI_Store_Day_Channel'[Y1NBINVOICES]),
    'Fact_KPI_Store_Day_Channel'[MDAY0Y1] = "MDA"
)

SSTG — Same Store Transaction Growth

SSTG =
[Transaction MDA] / [Transaction MDA PY] - 1

TM MDA — Average Transaction Value

TM MDA =
[Revenue MDA] / [Transaction MDA]

TM MDA PY

TM MDA PY =
[Revenue MDA PY] / [Transaction MDA PY]

TM %

TM % =
[TM MDA] / [TM MDA PY] - 1

Storeday

Storeday =
SUM('Fact_KPI_Day_Store'[Y0NB_JOURRESTO])

DPSA — Daily Per Store Average

DPSA =
CALCULATE(
    SUM('Fact_KPI_Store_Day_Channel'[Y0REVENUE_HT]) / [Storeday]
)

WPSA — Weekly Per Store Average

WPSA =
[DPSA] * 7

These DAX measures are provided for portfolio demonstration. Their results depend on the data model, relationships and filter context.

06 — DASHBOARD GALLERY

The dashboard
in practice.

A closer look at the sales indicators, channel breakdowns and restaurant-level analysis available in the report.

01

Sales highlights

Key sales indicators and headline performance metrics.

02

Sales channels

A breakdown of performance across sales channels.

03

Store & franchisee performance

Comparisons across restaurants and franchisees.

04

WPSA & GCPSA analysis

Additional sales performance indicators.

07 — BUSINESS VALUE

Better visibility.
More focused analysis.

The reporting solution provides a centralized view of daily restaurant performance and helps stakeholders identify variations across the network.

  • Centralized monitoring of daily performance indicators
  • Consistent comparisons across restaurants and franchisees
  • Visibility into channel-level sales and transaction trends
  • Clearer identification of areas requiring operational analysis
Confidentiality note

This portfolio version uses synthetic data for confidentiality purposes. The dashboard structure, KPIs and analytical approach are representative of the original reporting solution developed in a professional environment.

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