All focus areas of industrial engineering have application in supply chain productivity management. McKinsey way (2019) shows the application clearly by proposing that the redesign has to start with cost measurement. Process based industrial engineering and value based industrial engineering are the core industrial engineering methods. Economic analysis and optimization are to be used. Human effort engineering is indicated in direct labor redesign. The whole exercise has to be planned, organized and controlled by productivity management.
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Supply Chain Industrial Engineering - Video Presentation
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Supply Value Chain Redesign - Zero-Based Approach - McKinsey Way (2019)
Companies can identify substantial waste and increase value (Value Analysis and Value Engineering) by applying zero-basing to every part of the supply chain. An end-to-end assessment of the supply chain, including the intersections between functions (for example, the effect of specification choice by design department on manufacturability, or the quality of information shared between functions due to lack of trust) is critical to reduce complexity, optimize planning, and improve the coordination required to optimize the full supply chain.
By undertaking such efforts, some business firms have achieved overall cost savings of up to 50 percent.
Where is the value in a zero-based approach redesign of supply chain?
McKinsey consultants recommend start by breaking costs into four crucial categories—direct labor (including equipment), indirect labor (including equipment), warehouse and logistics, and materials (including conversion yields)—and building a bottom-up view on the existing cost base. The category which may have the highest opportunity varies by industry and type of manufacturing. In more automated settings or continuous manufacturing, equipment category may have higher opportunity. Direct-labor may be more important in manual assembly to find savings opportunities.
Establishing granular transparency
Companies have to seek granularity into costs. This visibility of lower and lower level costs, gained by aggregating ledger account data from internal sources and benchmarking data from external sources, enables organizations to establish relevant benchmarks across spending categories. Data is collected from existing recorded data and is augmented by specially made cost studies using observations and targeted sampling where data is lacking. The data has to point out regulatory and customer special requirements, which act as constraints in the problem.
Benchmarks for each value activity of the supply chain
Benchmarks are developed for each value activity of the supply chain. From the benchmarks technology to be used, capacity to be created and resources needed to support the organization’ business strategy are determined in a zero-based approach to supply chain value activity design. This analysis acts as a reset or a redesign or a zero-based design, giving managers a better understanding of best possible practice of each supply chain value activity. Benchmarks are set with intelligent decision making to determine aspirational—yet practical—business targets (smart goals). Benchmarks at the narrow cost-bucket level often identify potential value improvement opportunities that would remain hidden in more traditional, high-level analysis
Defining the survival state and Evaluating Organization Choices
The survival minimum performance of the supply chain and each value activity is defined by customer value requirement ( satisfying—but not exceeding—customer requirements for service, features, and specifications), regulatory requirements (such as hygiene standards), and nonnegotiable customer requirements, often related to quality.
The costs of activities related to satisfying customer requirements and the costs of the organization’s own choices (often based on contingencies or concessions or delight features) are calculated and challenged for their contribution to the final customer value. Activities that are determined to be low-value are challenged before they are included in the future state.
Value Analysis and Value Engineering in Supply Chain Value Activities
Value Engineering - Value Analysis Techniques - Video Presentations
A classic example is where an organization has included an extra quality check as the result of a customer claim event—and continues to follow it long after the quality risk has been fully mitigated by addressing the root cause.
Making informed strategic choices
Once the survival minimum is established and cost of additional features are determined, the supply chain redesign team then rebuilds the supply-chain function specifically to support business strategy. This design of a strategic optimum is calculated at every step to enable the organization to make conscious choices.
After the strategic optimal supply value chain is specified, the team designs each value activity by further simplification (basic engineering thinking at mechanism level) and automation solutions. These improved engineering solutions are subjected mathematical and statistical optimization to decide optimal factor levels. All value activities in the end-to-end supply chain are redesigned at a single step to make the right trade-offs to ensure system optimization rather than functional excellence.
Read the original McKinsey article
https://www.mckinsey.com/business-functions/operations/our-insights/zero-based-productivity-going-granular-and-end-to-end-across-the-supply-chain
Additional articles on Supply Chain Improvement Opportunities
Supply Chains spread the social disease of bad data
https://mytechanalyst.net/2013/10/12/bad-data-is-a-social-disease-part-2/
Additional articles on Supply Chain Improvement Opportunities
Supply Chains spread the social disease of bad data
https://mytechanalyst.net/2013/10/12/bad-data-is-a-social-disease-part-2/
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