How to Determine the Best-Fit Plan with Supply Chain Optimization

[fusion_builder_container hundred_percent=”yes” overflow=”visible”][fusion_builder_row][fusion_builder_column type=”1_1″ layout=”1_1″ background_position=”left top” background_color=”” border_size=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” last=”no” hover_type=”none” link=”” border_position=”all”][fusion_imageframe lightbox=”no” gallery_id=”” lightbox_image=”” style_type=”none” hover_type=”none” bordercolor=”” bordersize=”0px” borderradius=”0″ stylecolor=”” align=”none” link=”” linktarget=”_self” animation_type=”0″ animation_direction=”down” animation_speed=”0.1″ animation_offset=”” hide_on_mobile=”no” class=”” id=””] [/fusion_imageframe][fusion_text]While reading Arkieva COO Sujit Singh’s excellent blog “Supply Chain Optimization in Supply Planning: How to Develop a New Way of Thinking”, it triggered a theme that was often helpful as software companies made the transition to optimization for supply planning from 1996 to 2001. Optimization, in comparison to rule based supply planning, has the ability see, search, and adapt to the entire and ever-changing playing field. In my previous post, I use a simple algebraic example to illustrate the key computational principle that supports important decision-making technologies.

Using Supply Chain Optimization to Make a Best-Fit Prediction

The use of optimization in supply chain management is widespread, just not in supply planning. Regular use of optimization occurs in inventory management and demand forecasting. “Best-fit straight line” is one of the most common uses of optimization. With this method, you enter or pull into Excel (or your favorite statistics software) a set of “x values” (the independent value e.g. the number of cars in a train) and a set of “y values” (dependent value e.g. the fuel cost for each train), click a few buttons and you get a “best-fit” straight line – a slope (b1), a y-intercept (b0), a measure of goodness, and a straight line drawn through your scatter plot. How is this best-fit line calculated? Does it use rules? For example, use the average of the “y values” as b0, and the slope between the smallest X value and the largest X value as b1. No, it does not use rules.

It searches.

What does it search? Conceptually it estimates a value for b0 and b1, calculates the quality of the fit by summing the differences between the predicted value and actual value, and then either stops or generates a better estimate for b0 and b1 and repeats. The algorithm for this search comes from an area of computational methods called optimization. Note “best-fit” does not mean a “good fit”; simply there are no better fits.

[Read More: Beyond the Supply Chain Maturity Model Buzz][/fusion_text][fusion_imageframe lightbox=”no” gallery_id=”” lightbox_image=”” style_type=”none” hover_type=”none” bordercolor=”” bordersize=”0px” borderradius=”0″ stylecolor=”” align=”center” link=”” linktarget=”_self” animation_type=”0″ animation_direction=”down” animation_speed=”0.1″ animation_offset=”” hide_on_mobile=”no” class=”” id=””] [/fusion_imageframe][fusion_text]Let’s define search as the ability to step beyond rules and evaluate a range of solutions in a focused manner. Figure 1 shows a typical supply planning challenge involving alternative bill of material (BOM) paths to produce exit products. There are two exit products: Red Module and Blue Module where each can be produced by two different methods, and there is the potential for a shared part.

Supply Chain Optimization Techniques for Production, Inventory, and Demand

[/fusion_text][fusion_imageframe lightbox=”no” gallery_id=”” lightbox_image=”” style_type=”none” hover_type=”none” bordercolor=”” bordersize=”0px” borderradius=”0″ stylecolor=”” align=”center” link=”” linktarget=”_self” animation_type=”0″ animation_direction=”down” animation_speed=”0.1″ animation_offset=”” hide_on_mobile=”no” class=”” id=””] [/fusion_imageframe][/fusion_builder_column][fusion_builder_column type=”1_1″ layout=”1_1″ background_position=”left top” background_color=”” border_size=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” last=”no” hover_type=”none” link=”” border_position=”all”][fusion_code]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[/fusion_code][fusion_text]Existing Inventory

DEV02 has inventory currently available with a quantity of 30.
There is no other inventory.

Demand

DEM 101 for 15 red modules due on day 9 with a priority of 5.
DEM 102 for 20 units of blue modules on day 10 with a priority of 5.

Business Question

What set of actions should be taken to best meet the existing demand? That is matching assets (inventory and production capacity) with demand to best demand. Best is typically defined as on-time delivery, use of existing inventory, and minimizing new production starts.
The actions include allocation of the existing inventory of DEV02 and production starts for the DEV part group?
Is the starting point, the allocation of the existing inventory of DEV02?

A typical rule-based approach searches one demand at a time and one alternative at a time with a priority of consuming existing inventory. It does not search alternatives.

[Read More: How do you model inventory in planning systems?][/fusion_text][/fusion_builder_column][fusion_builder_column type=”1_1″ layout=”1_1″ background_position=”left top” background_color=”” border_size=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” last=”no” hover_type=”none” link=”” 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This example illustrates the two sides of search

By any reasonable metric, the solution from alternative 02 is superior to the rule base method
The solution is “more complicated” in terms of simple rules.

The question is, can a business really afford an underperforming plan simply, so it is simple to follow?