Promasidor was founded in 1979 by Robert Rose, who left the United Kingdom in 1957 for Zimbabwe to pursue his African dream. As Chairman of Allied Lyons Africa for over 20 years, he travelled extensively across Africa and gained a unique and thorough knowledge of the food industry throughout the continent. In particular he noticed a lack of availability of the one highly nutritious product that the developed world takes for granted - milk. He realised that with technology in the manufacture of milk powders advancing rapidly, there was an exciting opportunity to provide milk powder in small portions that could be packaged in flexible sachets. It was found that removing the animal fat from the milk and replacing it with vegetable fat allowed for a longer shelf life. This meant that for the first time, milk powder could be distributed across the vast African continent, providing access to affordable milk to everyone in Africa. A passionate belief in this vision fuelled the pioneering concept of selling filled milk powder in small sachets and Promasidor began selling the Cowbell brand in the Democratic Republic of Congo (then Zaire) in 1979. Today Cowbell is sold in the majority of countries across the African continent.
Introduction & Context
- Promasidor produces, distributes and markets a quality range of products in over 30 countries across the continent, reaching millions of consumers (more information available on our corporate web site here).
- Promasidor's IT Department (called PICT) is structured in 6 units with team members based across our main offices in Algeria, Angola, DRC, Nigeria, Ghana and South Africa:
- ERP: is responsible for everything related to our group ERP (Microsoft Dynamics Business Central) such as deployment, support & maintenance as well as functionality enhancements.
- GTM (Go-To-Market): is responsible for our Sales Force Automation (mobile) solution (internally built), used by over 2,000 users in 18 African countries.
- IS (Information Systems): is responsible for all business systems other than ERP and GTM (e.g. Business Process Management System for HR and other processes, Helpdesk ticketing solution, OEE for production efficiency, Quality Management System etc).
- BID (Business Intelligence Design): is responsible for the creation and maintenance of our reporting and analytics, mainly using Microsoft Power BI across all our business systems.
- OPS (Operations): is responsible for the infrastructure foundation for all the other units (physical and cloud, networking & connectivity, computers and other hardware devices) as well as productivity and collaboration tools (Emails, Microsoft Office & Teams, AI etc).
- Overview of the PICT organisation & reporting structure:
Job Purpose & Objectives
- Promasidor is accelerating responsible and practical AI adoption across its operations and seeks to create an AI unit comprising of AI Engineers and Analysts.
- The AI Analyst role is responsible for bridging business needs and AI capabilities. This role ensures that AI solutions address real operational problems, are built on fit-for-purpose data, and deliver measurable business value across functions such as Supply Chain, Finance, HR, Sales, and Operations.
- This role works closely with business stakeholders and technical teams (ERP, GTM, BI, IS, AI) to translate requirements into actionable AI use cases.
- The role of AI Analyst can be performed:
- at four levels of seniority - Junior, Associate, Senior, and Lead - based on competencies, experience and performance. While each level has variations in the job description, all share the same overall characteristics described in this document.
Key Responsibilities & Activities
Business & Use Case Analysis
- Engage stakeholders to identify and prioritise AI opportunities
- Define AI use cases aligned to business outcomes (cost, efficiency, growth)
- Translate business questions into data and model requirements
Data Readiness
- Assess data availability, quality, and gaps for AI initiatives
- Work with Business System owners to define data preparation needs
Insight & Value Realisation
- Interpret AI model outputs into actionable insights
- Support decision-makers in using AI-driven recommendations
- Track benefits and performance of AI solutions post-deployment
- Define and measure Key Performance Indicators (KPIs) and ROI for each AI initiative to demonstrate business impact to the Steering Committee
Collaboration & Enablement
- Act as the primary interface between AI Engineers and business teams
- Support ERP, GTM, IS teams in embedding AI insights into workflows
- Drive adoption and value realisation from AI solutions
- Testing, Validation & Continuous Improvement
- Validate AI outputs against business logic and expectations
- Coordinate and lead UAT phases, translating technical issues into actionable feedback for the AI Engineering team.
- Promptly identify and document "hallucinations" or inaccuracies in AI responses during system tests to ensure reliability before production.
- Monitor live AI performance to identify drift or declining accuracy, prioritizing fixes based on business impact and urgency in coordination with line management.
- Work with business users to troubleshoot unexpected AI behavior in production and define the functional requirements for necessary adjustments.
- User Training & Solution Enablement
- Develop user guides, training materials, and documentation to simplify complex AI outputs for nontechnical stakeholders.
- Conduct workshops and hands-on training sessions to ensure business users can confidently navigate and utilize AI-driven recommendations in their daily workflows.
- Identify and nurture "AI Champions" within departments to drive grassroots adoption and gather feedback for iterative improvement.
- Monitor user engagement post-deployment to identify friction points and provide targeted support to underperforming teams.
- Gather and synthesize user feedback to inform the AI product roadmap, ensuring continuous alignment with evolving business needs
Personal Development
- Continuously stay updated and enhance your knowledge about the tools and technologies used within your unit.
- Stay informed about the evolution of emerging technologies and industry trends.
Key Competencies Requirements
Must Have
- Strong analytical and problem-solving skills
- Ability to translate business needs into data-driven solutions
- Experience working with data, dashboards, or analytics tools
- Familiarity with AI/ML concepts and limitations
Nice to Have
- Experience with FMCG, manufacturing, or supply chain systems
- Attention to detail and commitment to quality.
- Strong work ethic and reliability.
- Adaptability and continuous learning.
- Initiative and proactivity.
- Resilience under pressure and ability to meet deadlines.
Method of Application
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