Manager - Manufacturing Excellence & Digital Transformation
Unilever is hiring a Manager - Manufacturing Excellence & Digital Transformation. Level rates it ; you can apply on Unilever.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- Tools and skills the posting cites include manufacturing excellence, continuous improvement and supply chain.
- Level classifies it as a senior role.
- Level lists 246 other open roles at Unilever.
- The role was posted within the past two weeks.
AI in this role
Manager of Manufacturing Excellence & Digital Transformation at Unilever Foods India driving continuous improvement and digital manufacturing solutions.
Job Description: Manager – Manufacturing Excellence, Foods India
Function: Supply Chain – Manufacturing
Location: Mumbai HO
Req ID: R-1190517
Background & Role
Foods India operates across a diverse manufacturing network, requiring consistently high standards of Safety, Quality, Service, Cost and Sustainability, while continuously improving productivity and building future-fit manufacturing capabilities.
The Manager – Manufacturing Excellence, Foods India will play a pivotal role in accelerating the manufacturing excellence journey across the Foods network.
The role will bring together Manufacturing Excellence, UMS, productivity, capability building and technology-enabled improvement to create a more competitive, agile and resilient manufacturing network.
Key Accountabilities
1. Manufacturing Excellence & UMS
- Lead the Manufacturing Excellence agenda across Foods India and accelerate deployment and maturity of Unilever Manufacturing System (UMS).
- Establish a strong continuous-improvement culture focused on systematic identification and elimination of manufacturing losses.
- Strengthen performance management and problem-solving routines across factories.
- Drive sharing and replication of best practices across the Foods manufacturing network.
2. Productivity & Cost Competitiveness
- Build and drive the manufacturing productivity roadmap across the Foods network.
- Identify structural opportunities across labour, assets, conversion cost, waste and manufacturing processes.
- Partner with factory leadership and Finance to create robust improvement pipelines and translate identified opportunities into sustainable business results.
- Establish benchmarking across sites and use internal/external best practices to raise manufacturing performance.
3. Performance Improvement
- Develop a common framework for manufacturing performance and loss intelligence across Foods sites.
- Drive structured interventions on chronic losses and performance gaps.
- Strengthen the use of data analytics and data-driven decision making in manufacturing.
- Enable factories to move from reactive issue resolution towards predictive and preventive performance management.
4. Technology, Digital & Automation
- Partner with Engineering, Digital and site teams to identify opportunities where digital technologies, automation and analytics can unlock manufacturing value.
- Build scalable use cases around productivity, reliability, quality, process control and shop-floor decision making.
- Ensure successful solutions are standardized and replicated across the network.
- Support development of the future-fit digital manufacturing capability within Foods.
5. Manufacturing Agility
- Drive initiatives that improve manufacturing responsiveness while balancing service, inventory and controllable cost.
- Partner with Planning and factories to strengthen operating flexibility and responsiveness to changing business requirements.
- Identify opportunities to increase flexibility of assets, processes and operating models.
6. Capability Building & Community
- Build Manufacturing Excellence capability across site leadership and manufacturing teams.
- Develop practitioners and champions in UMS, problem solving, loss elimination and data-driven manufacturing.
- Create an active Foods Manufacturing Excellence community to accelerate cross-site learning and replication.
- Coach teams in structured problem solving and sustainable improvement.
7. Cross-functional Leadership
- Partner closely with Sourcing Units, Engineering, Planning, Quality, SHE, Finance, Procurement and Digital/IT to deliver the Manufacturing Excellence roadmap.
- Connect manufacturing improvement priorities with the broader Foods Supply Chain strategy.
- Influence stakeholders across factories and central functions to accelerate execution and remove barriers.
Key Interfaces
- Foods Supply Chain Leadership
- Sourcing Unit Heads and Factory Leadership Teams
- Manufacturing / Production Teams
- Engineering
- SHE and Quality
- Planning
- Supply Chain Finance
- Procurement
- Digital / IT teams
- Global Manex Team
Experience & Qualifications
Essential
- Strong manufacturing/operations experience with a demonstrated understanding of factory performance.
- Experience in Manufacturing Excellence, Continuous Improvement, UMS/WCM/Lean or equivalent performance-improvement systems.
- Strong analytical and structured problem-solving capability.
- Ability to translate factory losses and operational data into actionable improvement programmes.
- Strong stakeholder management and influencing skills across factory and central teams.
- Ability to operate across multiple sites and drive improvement through influence rather than direct authority.
- Strong bias for action, execution and sustainable results.
Preferred
- Experience across one or more of manufacturing, engineering, operations excellence, digital manufacturing or supply-chain transformation.
- Exposure to automation, digital manufacturing and manufacturing analytics.
- Experience leading cross-functional transformation programmes.
- Engineering / Supply Chain / Operations education; postgraduate management qualification would be an advantage.
Leadership Behaviours
The successful candidate should demonstrate:
- Strategic thinking: Connect manufacturing improvement opportunities to business and Supply Chain priorities.
- Passion for high performance: Relentlessly identify and eliminate losses.
- Influence and collaboration: Mobilise factory and functional teams behind a common agenda.
- Data-driven decision making: Convert operational data into insight and action.
- Change leadership: Challenge established ways of working and embed sustainable new practices.
- People development: Build capability rather than creating dependency on a central team.
- Execution excellence: Translate ideas into measurable improvements on the shop floor.
“Our commitment to Equality, Diversity & Inclusion”
Unilever embraces diversity and encourages applicants from all walks of life! This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity.
Note: "All official offers from Unilever are issued only via our Applicant Tracking System (ATS). Offers from individuals or unofficial sources may be fraudulent—please verify before proceeding."
How we rate this
Manager - Manufacturing Excellence & Digital Transformation at Unilever rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where manufacturing excellence was part of your work. What did you do?
- Tell me about a project where continuous improvement was part of your work. What did you do?
- Tell me about a project where supply chain was part of your work. What did you do?
- Tell me about a project where data analytics was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Manufacturing Excellence, Continuous Improvement, Supply Chain, Data Analytics, and Automation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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