Job Summary
The Head of Sales Performance Management is responsible for monitoring, analyzing sales metrics & insights to provide strategic insights, support data-driven decision-making, and align sales performance with regional prepaid sales objectives. This role requires expertise in data analytics, statistical modeling, and business data set, to optimize sales strategies, and improve decision-making.
Key responsibilities include defining data requirements, collecting and processing data, performing in-depth analysis, and creating visual reports to identify trends and patterns. The role supports business teams by providing actionable insights to enhance sales performance, optimize efficiency, and automate data analysis processes.
They will define data requirements, collect, process, clean, and analyze sales data, identifying patterns and trends that inform business strategies. Additionally, they will contribute providing key insights to drive performance improvements.
The position also focuses on increasing automation in data analysis processes to streamline reporting and enable proactive sales performance management.
Skill Proficiency
Sales Data Monitoring & Analysis
- Monitor and analyze sales performance metrics (e.g., revenue, growth, churn, conversion rates).
- Develop dashboards and reports to track sales trends and provide real-time insights.
- Identify sales performance gaps and recommend corrective actions.
- Provide insights through regular sales reports.
- Assist in individual account and territory planning.
- Timely and accurate reporting of sales performance data.
- Data-driven insights for sales optimization.
- Accurate, data-driven decision-making.
- Balanced territory management.
- Accuracy and timeliness of sales reports.
- Reduction in performance gaps (e.g., target vs. actual sales).
- Adoption rate of insights-driven decision-making by sales leaders
- Timeliness and accuracy of sales reports.
- Territory performance variance.
- Completion rate of sales plans.
Predictive Analytics & Sales Forecasting and Insights
- Utilize statistical modeling, data mining, and machine learning to predict sales trends.
- Provide actionable insights for demand planning and market expansion.
- Identify factors affecting sales performance and customer buying patterns.
- Data-driven forecasting accuracy.
- Proactive identification of growth opportunities.
- Forecast accuracy rate (% deviation between predicted vs. actual sales).
- Number of strategic decisions influenced by predictive analytics.
- Increased sales conversion rates due to proactive insights.
Goal Setting & Performance Management
- Support sales leadership in setting realistic sales targets based on historical data and market trends.
- Align individual and regional targets with overall business objectives.
- Track goal achievement and provide performance feedback.
- Alignment of sales goals with business objectives.
- Effective performance tracking and reporting.
- Percentage of sales teams meeting/exceeding targets.
- Deviation between forecasted vs. actual sales.
- Frequency and quality of performance review reports.
Payout Management
- Managing partners and internal sales incentive payout.
- Accuracy of payout with on time schedule
- Collaboration with related stakeholders (within S&D and finance)
- Payout calculation
- Payout process as per governance
- Effective collaboration cross-function
- Payout accuracy
- On time payment
Automation & Process Improvement
- Identify areas to increase efficiency and automation in data analysis and reporting.
- Implement BI tools, dashboards, and automated reporting processes.
- Collaborate with IT/data science teams to enhance data analytics infrastructure.
- Streamlined reporting and analytics processes.
- Increased efficiency through automation.
- Time saved in data processing and reporting.
- Adoption rate of automated dashboards and analytics tools.
- Reduction in manual reporting errors.
- Access ready ensure performance dashboard and report go to the last mile
Collaboration & Stakeholder Management
- Work closely with sales, marketing, finance, and operations teams to align analytics efforts with business needs.
- Present insights and recommendations to senior management.
- Act as a liaison between data science teams and sales leadership.
- Effective cross-functional collaboration.
- Stakeholder satisfaction with insights and analytics support.
- Number of cross-functional projects successfully executed.
- Feedback score from stakeholders on analytics support.
- Impact of analytics recommendations on business decisions.
Qualifications:
- Bachelor’s degree in Business Administration, Marketing, Sales, or a related field.
- MBA or other advanced degree is often preferred.
- Minimum 10+ years of experience in sales performance management, sales operations, or sales analytics, preferably in a relevant industry (e.g., technology, financial services, healthcare, or manufacturing).
- Proven track record of designing and managing successful sales incentive programs.
- Strong understanding of sales performance metrics, KPIs, and analytics.
- Experience in using sales performance management tools (e.g., Xactly, Varicent, or SAP Commissions).
- Familiarity with sales compensation design and modeling.
- Experience in collaborating with cross-functional teams, including sales, finance, and HR.
Industry Knowledge:
- In-depth understanding of sales processes, methodologies, and best practices.
- Familiarity with industry-specific sales challenges and opportunities.
- Knowledge of emerging trends in sales effectiveness, such as AI-driven sales tools and predictive analytics.
Leadership Competencies :
- Operational Decision Making
- Innovation
- Customer Service Oriented
- Commerce & Entrepreneurial Insight
- Business Accumen
- Strategic Planning