Leading Global Vision Care Organization

Quota Setting for their vision care business unit

aurochs vision_care_business_unit_quota_management
aurochs vision_care_business_unit_quota_management


    • Challenges in Quota Setting for Vision Care Business Unit:
      • Lack of market data made quantification of potential and market standing unknown.
      • Setting quotas for a diverse product portfolio at different life cycle phases posed significant challenges.
      • Current methodology relied on statistical parameters, requiring extensive manual work and lacking transparency for the sales team.
    • Client’s Objectives:
      • Automate manual quota-setting methodology to save time and increase efficiency.
      • Achieve high process automation, change agility, and responsiveness.
      • Incorporate local guidance and knowledge into quota allocation.
      • Model different factors and evaluate the quality of allocated quotas.
    • Key Requirements:
      • High levels of automation and repeatability using statistical parameters.
      • Agility and flexibility to explore various permutations and combinations of historical sales and growth parameters.
      • Use historical sales and growth-based parameters, considering local knowledge.
      • Analytical visualizations and statistical summaries to assess fairness and performance.
      • Customization of historical periods, with caps and floors to handle outliers.
      • Define scenarios using different forecast scenarios.
      • Deployment of integrated quota management platform with backup support and service operations.


    • Evaluation of Existing Process:
      • Due to lack of market data, scrutinized current process for quota allocation.
    • Integration of Statistical Process:
      • Integrated current statistical process into tool for comparison with different models.
      • Enabled addition of scenarios to statistical process for enhanced analysis.
    • Model Implementation and Comparison:
      • Developed models based on volume, volume + growth, and existing statistical models with scenarios.
      • Compared results of different models for effectiveness.
    • Utilization of ML-Based Sales Forecasting:
      • Utilized ML-based sales forecasting trends for mature products with stable history.
      • Incorporated trends in quota setting process for improved accuracy.
    • Analytical Visualizations:
      • Employed post-hoc analytical visualizations to evaluate methodologies for fairness, performance, and outliers.
    • Comparison with Actual Sales Results:
      • Compared quality of quotas generated using traditional statistical process and new Aurochs processes with actual sales results.
      • Assisted client in identifying gap areas in entire process for refinement.

    Quota Manager Platform Rollout

      • Data Collection and Ingestion:
        • Collected data from various sources, primarily from the in-house data warehouse.
        • Utilized proprietary Data Manager for automated collation, sanitization, and ingestion of data.
      • Configuration of Quota Manager:
        • Configured Aurochs Quota Manager to accommodate different scenarios, including historical performance data periods and various sales factors.
        • Considered factors such as volume growth, sales trends, caps, and floors in quota allocation.
      • Testing Scenario Configuration:
        • Developed testing scenarios to assess methodology quality by allocating quotas across different historical periods.
      • Design of Calculation Workbooks and Reports:
        • Designed summary calculation workbooks and reports for effective communication of quotas.


        • End-to-end Automation:
          • Implemented automation of the quota allocation process using statistical parameters, resulting in over 90% reduction in processing time.
        • Pilot Implementation:
          • Initially piloted for a small set and later scaled to encompass all teams, roles, and salespeople.
        • Simplified Process and Communication:
          • Streamlined quota setting process and improved communication effectiveness in various areas, yielding better results.
        • Quality Evaluation:
          • Provided capability to evaluate quota quality at both individual and role levels.
        • Scenario Simulation:
          • Enabled scenario simulation for the client’s existing quota allocation methodology.
        • Bias Identification:
          • Facilitated easier identification of bias in quotas due to geographical performance trends.

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