Executive Briefings

Demand-Based Replenishment: Utilizing Pull-Based Techniques to Optimize Finished Goods Inventory

Analyst Insight: Many food and beverage companies struggle in their attempt to optimize finished goods inventory due to inherently complex supply chains characterized by long lead times.  Complicating matters are issues brought about by manufacturing constraints, multiple and significant sources of variability, product seasonality and shelf-life constraints, and competing organizational goals and performance expectations. Overlay difficulties encountered in identifying and quantifying the impact of these issues, as well as struggles in aligning the various functions to improve coordination, and the net result can be poor inventory performance and sub-par service levels.

-Michael Rellihan, associate principal at REL, a division of The Hackett Group

Demand-based replenishment is an approach that utilizes customer demand ("pull") to replace and optimize inventory while reducing total net landed cost. It is not about making all products on a make-to-order basis, but is instead an approach to replenishing and optimizing inventory that significantly stabilizes plant operations by establishing fixed production cycles using customer demand instead of a forecast-based ("push") scheduling method.  When comparing these two primary replenishment methods, the pull-based method generally results in more frequent and flexible changeovers, more stable and predictable production schedules that adhere to optimal run sequences and run lengths that vary based on customer demand. Conversely, the push-based method is characterized by infrequent and lengthy changeovers, variable production schedules based on forecasted demand, frequent schedule "cut-ins" that violate optimal product sequencing rules, and production quantities that are some multiple of shift output rates.

Transitioning from a push-based to a pull-based method can significantly improve inventory and service level performance and reduce supply chain-related costs because it establishes a pre-determined plan for what to produce, when to produce it, how much to produce, and when to deploy it. In doing so, it stabilizes plant operations by reducing the guesswork associated with determining production cycles and quantities based on the accuracy of a forecast, as well as reduces the likelihood of valuable capacity being lost due to the occurrence of unplanned changeovers.

Implementing a demand-based approach begins with applying rigorous analytics in understanding the impact of each of the variables that factor into the development of item-level inventory targets. Data such as item historical shipment, inventory and production information, as well as operational data pertaining to the manufacturing and distribution network, need to be gathered as they are key components to the establishment of an understanding as to what current capabilities are and what is achievable in the way of inventory improvement. Once a baseline is established, various scenarios can be identified and modeled which provide a link between process improvement efforts and further inventory reductions.

The Outlook

For process-based industries, such as food and beverage, where adherence to production and changeover sequences are critical for plant stability and inventory performance, demand-based replenishment techniques can have a significant positive impact.  Reducing and optimizing finished goods inventory through the implementation of these techniques, though, requires a coordinated effort to identify and remove sources of supply chain variability, minimizing lead times, reducing cycle stocks, and plant-level support and ownership.

Analyst Insight: Many food and beverage companies struggle in their attempt to optimize finished goods inventory due to inherently complex supply chains characterized by long lead times.  Complicating matters are issues brought about by manufacturing constraints, multiple and significant sources of variability, product seasonality and shelf-life constraints, and competing organizational goals and performance expectations. Overlay difficulties encountered in identifying and quantifying the impact of these issues, as well as struggles in aligning the various functions to improve coordination, and the net result can be poor inventory performance and sub-par service levels.

-Michael Rellihan, associate principal at REL, a division of The Hackett Group

Demand-based replenishment is an approach that utilizes customer demand ("pull") to replace and optimize inventory while reducing total net landed cost. It is not about making all products on a make-to-order basis, but is instead an approach to replenishing and optimizing inventory that significantly stabilizes plant operations by establishing fixed production cycles using customer demand instead of a forecast-based ("push") scheduling method.  When comparing these two primary replenishment methods, the pull-based method generally results in more frequent and flexible changeovers, more stable and predictable production schedules that adhere to optimal run sequences and run lengths that vary based on customer demand. Conversely, the push-based method is characterized by infrequent and lengthy changeovers, variable production schedules based on forecasted demand, frequent schedule "cut-ins" that violate optimal product sequencing rules, and production quantities that are some multiple of shift output rates.

Transitioning from a push-based to a pull-based method can significantly improve inventory and service level performance and reduce supply chain-related costs because it establishes a pre-determined plan for what to produce, when to produce it, how much to produce, and when to deploy it. In doing so, it stabilizes plant operations by reducing the guesswork associated with determining production cycles and quantities based on the accuracy of a forecast, as well as reduces the likelihood of valuable capacity being lost due to the occurrence of unplanned changeovers.

Implementing a demand-based approach begins with applying rigorous analytics in understanding the impact of each of the variables that factor into the development of item-level inventory targets. Data such as item historical shipment, inventory and production information, as well as operational data pertaining to the manufacturing and distribution network, need to be gathered as they are key components to the establishment of an understanding as to what current capabilities are and what is achievable in the way of inventory improvement. Once a baseline is established, various scenarios can be identified and modeled which provide a link between process improvement efforts and further inventory reductions.

The Outlook

For process-based industries, such as food and beverage, where adherence to production and changeover sequences are critical for plant stability and inventory performance, demand-based replenishment techniques can have a significant positive impact.  Reducing and optimizing finished goods inventory through the implementation of these techniques, though, requires a coordinated effort to identify and remove sources of supply chain variability, minimizing lead times, reducing cycle stocks, and plant-level support and ownership.