Peak shift productivity is achieved when you consistently deploy the right resources – work force, tools, materials and work instructions – at the optimal time. Production managers can spend countless hours trying to get resources aligned as part of their weekly and daily planning and scheduling. And, insufficient resources have a huge impact on productivity, causing increased rework and scrap, lower product quality, reduction in net output and higher costs from production schedule overruns and overtime.
Digital technologies help determine the optimal time and improve agility in deploying those resources. Having the right skill type of workers, tools and material availability at the right time can have a huge impact on shift productivity, OEE and OLE.
Smart Resource Optimization Benefits
Implementing an analytics-based strategy within your planning and scheduling functions empowers shift planners to optimize resources for each shift based on worker, tools and material availability data.
Establish baseline metrics and benchmarks related to schedule compliance and production delays
Optimize for quality and higher production shift output with various constraints
Minimize or eliminate production delays for diverse production runs
Enhance production visibility to manage dynamic scenarios on the shop floor
Model scenarios for higher shift output under optimal mixes
Standardize processes for optimal productivity across all sites
10-12% improved labor efficiency
5-30% faster resource tracking
Reduced scrap and rework
Increased compliance of schedule and skill certifications
How We Help Clients with Resource Optimization
Our approach can help you transform resource optimization within your organization and scale across multiple sites.
Planning activities involving workers, planners, floor managers will uncover resource planning pain points and align the roll-out to operational goals.
Evaluating data from the shop floor, tools and materials availability to discover impact on shift productivity and tracking system needs.
Performing exploratory data analysis on sample datasets to prepare for modeling, and design additional features to maximize shift output and yield.
Modeling the optimization engine to confirm appropriate algoirithm and determine model performance.
Refining the model for production roll-out, socializing proof of value, and ensuring work instructions and dashboards are optimized and in place.
Deploying to production environment to evaluate results, rate effectiveness, and value achieved with key stakeholders.
Scaling implementation plan, business value case, and deployment to multiple sites.
Get Started with a Value Workshop
Contact us to schedule a value workshop where we'll understand use cases and associated value, begin prioritization of impact versus difficulty of implementation, and determine an MVP use case.