30
September
2014

Role Based Analytics: Driving the Tactical to Practical in Retail

Role Based Analytics for Retail

How Role Based Analytics Boosts Productivity in Retail: 

Optimize productivity! Business owners, irrespective of the domain of their specialization, are largely preoccupied with this goal. While in the manufacturing industry, the change is proposed to occur at the cultural level, on the other hand, in retail setting the change should occur at three different and specific sections, namely:

  • Strategic
  • Tactical, and
  • Operational

Role-based analytics is a highly effective discipline that allows retail planners to monitor each of the above-mentioned levels and drive them towards success. In retail setting, all these levels should conjoin and complement each other for overall success of the business. Role-based analytics identifies all potential factors, threatening overall prosperity of the business, specifically and drive decision makers in implementing changes with the ambition to correct those flaws only to exponentiate both decision implementation process and performance, in turn.

Role Based Analytics Means Specific and Direct Addressing of Retail Segments: 

The results of role-based analytics affect various segments of personnel involved in the retail business, namely –

  • Buyers
  • Category planners and managers
  • Merchandise managers (divisional)
  • Merchandising leaders
  • Store operations and inventory management

Experts, at the theoretical level, have laid down detailed tactical planning when it comes to achieving the goals of quickening decision-making process in store and optimizing store performance. However, implementing the theory to practice is the biggest challenge. Decisions can be made but their implementation requires strong statistical support. The results delivered by role-based analytics delivers the requisite. Moreover, the dynamic nature of retail industry requires not rigid but flexible decision-making process as well as swift adaptation of the same. Role-based analytics is replete with industry-centric features; consequently, it delivers realistic, personalizable drives to the areas of key expertise in a retail store, such as:

  • Performance management
  • Capacity for collaborative decision making
  • Guided analytics

Category Based Retail Analytics

The Key Applications in Role-based Analytics:

  • Customizable data support for different roles: Executive and departmental decision makers may receive accurate data support to measure performance on hourly/daily/weekly/monthly etc. basis. Naturally, it becomes easy for them to take the right decision at the right time, contributing to overall performance improvement of the retail store.
  • Scenario Specific Data Support and Decision Making: Decision makers have the opportunity to enjoy scenario specific data support and make the necessary modifications accordingly. Scenario specific data support can be received on the basis of stock behavior, inventory status or in the cost controlling contexts.
  • Personalizable Category Viewing as per Role: Decision makers, while on one hand, can find adequate data, reflecting performance of stores and in-store departments, on the other hand, they can also find the necessary details about key performance indicators, category wise. In the latter case, the decision makers are directly responsible for the performance of the category-based products. Accordingly, they can come up with newer decisions or make certain changes to existing ones, for performance improvement. 

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