In retail like any other industry there are multitude of interacting business processes. Every business process has input and output data. Output data of one business process can be input data for another and vice versa. Hence theres a multitude of data and making sense of these data becomes a "haystack" problem. Most retailers analyze few of the important data of few important business processes to help them make better business decisions. However it might just happen that some key data might be ignored just due to the absence of arranged and prioritized data. Also it might just happen that the retailer is tracking a wrong KPI altogether due to an myopic approach of selection of data. To add to the problem retailers have disparate systems for different business processes. Collecting data from all these disparate systems and making sense out it is a difficult job.
The idea is that retailers should be focused on a very select data and select KPIs; but the most critical and correct ones. Hence the question to be asked is how does one know what are the correct and critical KPIs and data?
Retail business intelligence is a process of defining data and KPIs to enable retailers better streamline their decision making using data.
Retail business intelligence has two components the metadata and the KPI. Metadata gives definition and logical meaning to the data while KPI gives business meaning to the data. Data from all the disparate systems are pooled in a central location such as a data warehouse. Here the data is associated to metadata to arrange logically segregate and arrange them.
Next KPIs across business processes are defined. For example KPIs for distribution, logistic, category management etc are all defined in a centralized location. These KPIs then use the pooled data to derive a value of business importance.
The KPIs are also arranged based on the viewing authority. For example a Inventory Planning Head would be interested in KPIs such as DC inventory vs Sales, Target Inventory vs Actual Inventory etc while a Store Manager will be viewing KPIs such as Store Floor Space Utilization, Employee Utilization etc. Hence restricting user/ viewer based viewing of data helps the users to focus on their respective KPIs.
Centrally managing data and KPI helps retailers better maintain data and quickly derive sense out of it and hence in turn drive agility in better decision making.
The idea is that retailers should be focused on a very select data and select KPIs; but the most critical and correct ones. Hence the question to be asked is how does one know what are the correct and critical KPIs and data?
Retail business intelligence is a process of defining data and KPIs to enable retailers better streamline their decision making using data.
Retail business intelligence has two components the metadata and the KPI. Metadata gives definition and logical meaning to the data while KPI gives business meaning to the data. Data from all the disparate systems are pooled in a central location such as a data warehouse. Here the data is associated to metadata to arrange logically segregate and arrange them.
Next KPIs across business processes are defined. For example KPIs for distribution, logistic, category management etc are all defined in a centralized location. These KPIs then use the pooled data to derive a value of business importance.
The KPIs are also arranged based on the viewing authority. For example a Inventory Planning Head would be interested in KPIs such as DC inventory vs Sales, Target Inventory vs Actual Inventory etc while a Store Manager will be viewing KPIs such as Store Floor Space Utilization, Employee Utilization etc. Hence restricting user/ viewer based viewing of data helps the users to focus on their respective KPIs.
Centrally managing data and KPI helps retailers better maintain data and quickly derive sense out of it and hence in turn drive agility in better decision making.
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