Analytics Lead - Commercial

Team Introduction: 

The SAPMENA Zone Chief Data & Analytics Office is a dynamic group of data & analytics experts dedicated to propelling business growth and data maturity. Leveraging cutting-edge technologies, the team fosters continuous optimization of ecommerce platforms, customer experiences, and marketing efforts. Their collective drive and focus on data enable the organization to stay ahead in the competitive market, fostering sustainable growth and enriching customer satisfaction. The team works extremely closely with the data IT team and data governance team to ensure L’Oréal’s data roadmaps are aligned with the overall data strategy and business needs. 

Role Overview: 

This role reports to the Chief Data & Analytics Officer, SAPMENA. 

Key Responsibilities: 

· Define and Drive Customer Experience Data x AI Strategy: 

• Collaborate with business leaders to define and shape the data x AI strategy for our commercial functions
• Create and communicate a compelling data x AI vision that aligns with our commercial strategy and creates a long-term objective for all teams
• Develop a deep understanding of functional needs and how they vary for each division and country. Learn the pain points and opportunities through research, data analysis, and feedback channels.

· Engage with Stakeholders and business owners: 

• Act as the primary liaison between the product team and stakeholders, fostering strong relationships and gathering feedback.
• Be the first point of contact to discuss new ideas or requirements, so that their value can be defined before they’re routed into the right engagements model
• Conduct market research, user and customer interviews to gain insights and validate new capability concepts.
• Align roadmaps with the data IT team and data governance team to make sure that new ambitions are aligned across all teams.
• Regularly update priorities, timelines, constraints and opportunities to key stakeholders and business owners. Educate them on data concepts or data opportunities.
• Organize and facilitate feedback sessions, focus groups, and user workshops to capture regular input for continuous improvement.

· Develop and prioritize functional catalogue: 

• Catalogue existing data x AI capabilities across the countries divisions, and Global teams, related to the commercial domain so they can serve as a reference point for new ideas. This can include advanced analytics and AI solutions as well as new reporting capabilities.
• Translate the customer experience data x AI strategy into a well-defined capability catalogue that’s prioritized based on business value.
• Define minimum requirements, business requirements and success criteria of each use case in the functional catalogue.
• Collaborate with cross-functional teams, including designers, developers, and stakeholders, to refine and prioritize the capability catalogue based on commercial impact, data readiness, business value and resource availability.
• Regularly review and update the capability catalogue to ensure it reflects evolving customer needs, market dynamics
• Drive the alignments with Global Analytics leads to ensure complementarity of catalogue between Global/Zone/Countries and support the Global governance validation processes

· Participate in the Agile Product Development: 

• Work with the product Manager and their development team to plan and execute product releases and sprints.
• Prioritize user stories for each sprint, ensuring they align with the customer experience strategy and deliver maximum value.
• Route new capability requirements to the right engagement model
• Differentiate whether a new capability is a Zone or country and route it to the right engagement model
• Leverage in-country capabilities to accelerate new pilots and ideas
• Make sure minimum pilot requirements around skills, data availability and technical expertise are met before kick-off
• Validate that local developments are following best practices and data product frameworks to ensure long term scalability when the capabilities are brought to new markets
• In collaboration with the data IT team, conducts education sessions with in-country analysts to ensure every resource has the right skills, tool kit and data access to conduct new ideas in the right governance

· Drive adoption and optimize Customer Experience: 

• For existing and new capabilities, define and track key performance indicators (KPIs) and Key Value Indicators (KVIs) to measure and track the adoption and effectiveness of the product in delivering an exceptional customer experience.
• Conduct regular education sessions with business stakeholders to ensure maximum adoption of data capabilities.
• Analyze data and customer feedback to identify areas for improvement and make data-driven decisions.
• Feedback new requirements, market trends or changing business objectives to the product manager to refine the product roadmap.

Required Skills: 

· Consultancy Mindset: 

• Serve as an in-house data x AI consultant to drive each team’s data understanding and maximize the data maturity of each stakeholder’s team.
• Excellent communication and collaboration skills to engage with stakeholders, customers, and cross-functional teams. Great storyteller and educator to align non-technical experts on the data x AI vision.
• Strong collaborator with an agile mindset that can take initiative to self-driven new ideas with the cross-functional team
• Value oriented mindset that focuses on size of the prize and ensures maximum adoption of existing and new data capabilities within the business.
• Ability to translate internal customer needs into actionable capability requirements.
• Experience in facilitating ideation workshops, requirement gathering meetings, feedback sessions and user education.

· Technical data understanding 

• Technical knowhow on how data products are built, trade off quick wins vs scalability
• Translate business requirements to technical data requirements when working with the data IT teams.
• Leverage existing re-usable data assets and data roadmaps to validate that minimum data requirements are met
• Educational background in Data Analytics/Engineering/Computing/Data science

· Functional expertise 

• Have a deep understanding of the FMCG Commercial domain.
• Worked with or worked in functional Commercial teams.
• Understand the pain points, goals and opportunities of these commercial teams.