Alphasearch
Website:
alphasearch.com
Job details:
Manufacturing Process Excellence and AI Enablement Consultant
About the Role
We are seeking a hands-on Manufacturing Process Excellence and AI Enablement Consultant to
help transform a manufacturing organisation into a tightly integrated, efficient and AI-ready operation.
This is not a strategy or report-writing role. The Consultant will spend substantial time on the shop floor and with operational teams to understand how work is actually performed across production, quality, maintenance, supply chain, planning, procurement, warehousing and logistics. They will identify where output is constrained, information is disconnected, work is duplicated, quality is compromised or decisions rely excessively on manual intervention.
The Consultant will then own the redesign of priority operating processes and lead implementation through to adoption. The objective is to establish connected ways of working across people, processes, production systems and data, enabling higher productivity, stronger quality and more practical automation and AI deployment.
Reporting directly to the CEO, the Consultant must be equally credible with shop-floor teams and plant leadership as with senior management.
Key Responsibilities
Observe and Diagnose Plant and Operational Performance
- Spend time on the shop floor and with frontline teams to understand current working practices, production flows and day-to-day operational challenges.
- Map end-to-end processes across production planning, procurement, inbound materials, manufacturing, quality assurance, maintenance, warehousing, dispatch and customer fulfilment.
- Identify production bottlenecks, idle time, rework, scrap, yield loss, manual reporting, duplicated activity, weak hand-offs and unclear accountability.
- Review the flow of production, inventory, quality and maintenance data across teams and systems, identifying where information is delayed, lost, re-entered or unreliable.
- Assess the effectiveness of planning routines, production scheduling, material availability, preventive maintenance, quality controls and performance reporting.
- Produce clear current-state process maps and a practical diagnostic of the key drivers of inefficiency, cost, delay and operational risk.
Design an Integrated, AI-Ready Manufacturing Operating Model
- Redesign priority workflows across manufacturing and support functions to establish clear ownership, standard work, defined hand-offs, controls and measurable service levels.
- Improve the integration between production, quality, maintenance, planning, procurement, warehouse and logistics teams.
- Design processes with automation and AI in mind, ensuring production and operational data is captured consistently, structured appropriately and available for decision-making.
- Identify gaps in systems, master data, documentation and reporting that prevent effective automation, real-time visibility or AI adoption.
- Recommend practical improvements to ERP, MES, quality, maintenance, inventory, workflow and reporting processes.
- Define what AI readiness means for each operational function, including data quality, process discipline, equipment and maintenance data, decision rights and governance.
- Develop a prioritised transformation roadmap, linking each initiative to expected gains in productivity, throughput, yield, quality, cost, service, safety or working capital.
Lead Implementation and Sustain Change
- Own implementation of redesigned processes rather than simply presenting recommendations.
- Lead pilots on selected production lines, plants or operational functions, resolve practical issues and refine solutions before wider rollout.
- Work closely with operational leaders, IT teams and external technology partners to implement process, system and integration changes.
- Develop SOPs, standard work instructions, operating controls, visual management routines and training materials.
- Train plant managers, supervisors and process owners to sustain improved ways of working.
- Establish KPIs and review mechanisms covering areas such as OEE, throughput, downtime, yield, scrap, rework, schedule adherence, inventory accuracy, quality performance and on-time delivery.
- Create governance routines that ensure improvements are embedded, performance is monitored and further opportunities are continuously identified.
Success Measures
- A clear, documented view of how work, materials, information and decisions currently flow across priority manufacturing and supply-chain processes.
- A practical, CEO-ready roadmap for process integration, operational excellence, automation and AI enablement.
- Redesigned workflows implemented and adopted across selected operational areas.
- Measurable improvement in productivity, throughput, quality, yield, lead time, reliability, cost or service performance.
- Reduced manual reporting, rework, data duplication, process delays and disconnected decision-making.
- AI-ready operational processes with structured data, clear controls and specific automation opportunities.
- Internal operational leaders and teams able to sustain and continuously improve the new operating model.
Required Experience and Skills
- Demonstrated experience leading end-to-end process redesign and implementation in manufacturing, industrial operations or a similarly complex production environment.
- Strong practical understanding of shop-floor operations, production planning, quality, maintenance, supply chain and plant performance management.
- Proven track record delivering measurable operational improvements from diagnosis through implementation, adoption and sustained results.
- Experience identifying and addressing root causes of low productivity, quality losses, bottlenecks, downtime, waste, rework and poor cross-functional coordination.
- Working knowledge of ERP, MES, production planning, maintenance, quality, inventory, workflow-automation and reporting systems.
- Understanding of systems integration, APIs, data structuring and the operational data foundations required for automation and AI adoption.
- Strong process-mapping, SOP development, project-management and change-management capability.
- Confidence engaging staff at all levels, from operators and supervisors to plant leaders and senior executives.
- Excellent communication skills, with the ability to translate shop-floor realities into clear priorities and decisions for leadership.
Preferred Background
- Manufacturing, industrial, FMCG, food and beverage, chemicals, consumer goods or other operationally intensive background is strongly preferred.
- Hands-on experience improving production, quality, maintenance, procurement, planning, warehousing, logistics or supply-chain processes.
- Exposure to Lean Manufacturing, Six Sigma, TPM, Kaizen, OEE improvement, continuous improvement or operational excellence programmes.
- Experience with enterprise systems implementation or improvement, particularly ERP, MES, WMS, CMMS, quality-management or manufacturing-reporting platforms.
- Experience working directly with CEOs, plant heads or senior leadership teams on cross-functional transformation programmes.
Location and Travel
This is a hybrid consulting role requiring regular travel and extended stays in Yangon, Myanmar. The successful Consultant will balance time in Myanmar with their home location, based on the operational needs of the engagement.
All approved travel, accommodation and business expenses will be covered by the employer.
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