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Group Commercial Performance Lead job at Nft Consult Ltd

About the Organization

NFT Consult is a business process outsourcing firm with offices in Uganda, Kenya, Rwanda, Tanzania, Zambia, Burundi, South Sudan and UK.

We are an ISO 9001:2015 accredited Human Resource Management firm offering Recruitment, Manpower Outsourcing, Payroll and Provision of IT Enabled HR Solutions. We specialise in the Oil & Gas, Telcoms, IT and Financial Sectors and are located in Uganda, Kenya, Rwanda, Tanzania, Burundi, Zambia and South Sudan. Through the partnerships we have developed with our clients and firms offering similar services we are able to extend our services throughout Africa. We are committed to making a difference in our community through the relevant solutions we offer.

Job Description

The primary objectives of the job holder are to optimize demand planning through accurate forecasting, monitor and enhance the performance of the sales team, analyze trade activities for alignment with targets, evaluate distribution efficiency, and provide actionable recommendations. The Group Commercial Performance Lead performs extensive data analysis, develops predictive models, and utilizes data visualization to facilitate effective decision-making.

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Duties and Responsibilities

  • Demand Planning and Forecasting: Utilize robust planning and forecasting tools to generate detailed unconstrained demand targets. These targets are derived from validated baselines as well as macro and micro assumptions.

  • Monitor and Evaluate Commercial Team Performance: Track and assess the entire Sales team's performance against established KPIs and operational standards. Translate insights gained into actionable recommendations for potential adjustments and improvements.

  • Trade Activity Tracking: Continuously monitor all commercial activities and conduct regular reviews to determine their alignment with the plan. Utilize insights to propose corrective actions if deviations are identified.

  • Route & Call Effectiveness: Evaluate the efficiency and efficacy of distribution by analyzing factors such as coverage, adherence to journey plans, route frequency, total outlets visited, calls per day, strike rate, call frequency, time spent in calls, and trade visits (including distributor teams, representatives, and line managers).

  • Model Development and Machine Learning: Create predictive models, machine learning algorithms, and statistical models. Choose appropriate methodologies based on specific problem contexts. Train, validate, and optimize models for superior performance.

  • Data Cleaning and Preprocessing: Transform raw data into a usable format by performing data cleaning and preprocessing tasks. Address missing data, outliers, and inconsistencies.

  • Data Visualization: Utilize data visualization tools to craft informative charts, graphs, and dashboards. Convey intricate insights to non-technical audiences effectively.

  • Experimentation and Testing: Design and execute experiments to validate hypotheses and evaluate model performance. Implement A/B testing methodologies and derive insights to steer data-driven decisions.

  • Data-driven decision-making: Offer recommendations that underpin strategic decisions within the organization. Contribute to the establishment of data-informed decision-making processes.

  • Continuous Learning and Skill Development: Stay abreast of the latest trends, tools, and techniques in the field of data science. Continuously enhance technical skills and expand knowledge.

  • Data Analysis and Interpretation: Analyze extensive and intricate datasets to extract valuable insights. Recognize trends, correlations, patterns, and outliers within the data. Translate findings into actionable suggestions for business stakeholders.

Performance Measures and Targets:

  • Forecast Accuracy Rate: Measure the accuracy of demand forecasts against actual sales to ensure reliable predictions.

  • Sales KPI Achievement: Evaluate the achievement of key sales performance indicators to assess the sales team's effectiveness.

  • Models Accuracy: Measure the accuracy of predictive models and algorithms to ensure their reliability.

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Qualification, Experiences and Competencies

  • Bachelor of Statistics, Computer Science, Mathematics, Business Computing, economics (Any degree that focuses on Technology and Business).

  • Four years of Work experience in a similar role.

  • Experience as a Senior BI Commercial Analyst.

  • Certifications in Pivot Tables and Python in Excel.

  • Conversant with Excel Power Query (M Language), Data Analysis Expressions/Models, Advanced Excel Functions & Technique and Predictive Analysis and Modelling.

How to Apply

Are you interested? Click the "APPLY" button below to submit your application.

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