Retail Crime
299c-表:by Tableau|桜
99e5-表:Description|桜
This Tableau Accelerator allows you to:
- Track and reduce retail crime
- Proactively address and mitigate criminal activities
- Protect assets
- Ensure the safety of employees and customers
- Identify and implement optimal security models
- Focus efforts on high-risk areas to prevent crime-related losses
- Identify stores in need of security investment for targeted improvements
Answer key business questions
- How exposed are we to retail crime?
- How does this affect our results?
- How effective are we at preventing retail crime?
- Where should we focus our efforts to minimise retail crime?
- Which stores require specific attention?
- Where should we invest next to maximise impact?
Monitor and improve KPIs
Sales
- Total Sales $: Total amount of sales done in stores (sell-out, expressed in currency)
- Sales $ per Store: Average Sales amount per store (all active stores over the period)
Crimes
- Total Crime $: Total Crime amount over the period (expressed in currency)
- Average Crime $: Average Crime amount per crime (expressed in currency)
- Nb of Crimes: Total number of crimes over the period
- Crime vs Sales %: Crime amount as percentage of Total Sales amount (expressed in percentage)
- Crime $ per Store: Average Crime amount per Store (expressed in currency)
Stores
- Nb of Stores: Total number of stores having a sales transaction or a crime over the period
Loss Prevention
- Total Prevention $: Total cost of prevention measures implemented (expressed in currency)
- Estimated Crime Reduction $: Estimated amount of the impact of security measures in place to reduce losses from retail crime. This estimation is calculated in comparison to Total Crime $ of stores with the weakest security measures (expressed in currency)
- Estimated Net Benefits $: Estimated amount of benefits from implementing security measures. (expressed in currency)
- Estimated ROI %: Estimated Return On Investment from implementing security measures (expressed in percentage)
Required attributes
This Tableau Accelerator uses two concatenated datasets: “Reported Crime” and “Retail Sales”. You must use the same Shops and Product lines in both datasets to get a meaningful result in the Tableau Accelerator.
Reported Crimes
- Crime ID (string): Unique Identifier of the crime
- Date (date): Crime date
- Shop (string): Shop name
- Country (string; role: country): Country where the shop is located
- State (String; role: province): State where the shop is located
- City (string; role: city): City where the shop is located
- Store Latitude (numeric): Latitude where the shop is located
- Store Longitude (numeric): Longitude where the shop is located
- Security Model (string): The security model refers to the strength of measures in place to protect assets. Expected values: “Very Low”, “Low”, “Medium”, “High”, “Very High””
- Security Model Description (string): The security model description details the measures in place to protect assets. e.g: “Employee Training”, “Employee Training + Surveillance System” etc.
- Product Line (string): Product Line, Product Category, Business Line...
- Source of Crime (string): Source of Crime e.g: “Customer Theft”, “ORC - Organised Retail Crime”, “Employee Theft”, “Supplier/Warehouse Theft” etc.
- Crime Amount (numeric): Crime amount
Retail Sales
- Date (date): Sales date
- Shop (string): Shop name
- Country (string; role: country): Country where the shop is located
- State (String; role: province): State where the shop is located
- City (string; role: city): City where the shop is located
- Store Latitude (numeric): Latitude where the shop is located
- Store Longitude (numeric): Longitude where the shop is located
- Security Model (string): The security model refers to the strength of measures in place to protect assets. Expected values: “Very Low”, “Low”, “Medium”, “High”, “Very High””
- Security Model Description (string): The security model description details the measures in place to protect assets. e.g: “Employee Training”, “Employee Training + Surveillance System” etc.
- Product Line (string): Product Line, Product Category, Business Line...
- Sales Amount (numeric): Sales amount
4c7a-表:Features|桜
c0b5-表:Supports data mapping|桜