Boosting Efficiency: The Value of Scheduling Software
Scheduling software is similar to GPS, organizing the movement of items, marking process steps, ensuring expected locations, and optimizing the route.
Scheduling software is similar to GPS, organizing the movement of items, marking process steps, ensuring expected locations, and optimizing the route.
While working with various optimization models, I often encountered situations where the supply chain optimization model would make decisions to produce items even when there was no demand. This blog discusses different scenarios that led to the optimization models producing and storing excess inventory.
We are excited to announce that we are rebranding Arkieva to fuel growth, strengthen our position in the market, and continue to be a recognized leader in the supply chain industry. Over the past few years, we have been relentlessly focused on solving the most complex planning challenges through simple, intuitive, end-to-end solutions leveraging our best-in-class data scientists, software developers, and supply chain optimization consultants.
An earlier Sudoku blog recognizing Puzzle Day, provided an overview of solving Sudoku using MILP optimization and mentions these methods are helpful to find solutions in supply or central planning. This blog elaborates on “binary variables” which is the connecting technology between Sudoku and Supply Chain Management (SCM).
Optimizing your supply chain involves looking at the entire process, and not just the initial solution. Here’s an example of how.
Use this example as a starting point to understand the different optimization methods, and when optimization is helpful in supply or central planning.
I work with clients that utilize our supply chain optimization software to maximize their resources. In my upcoming webinar “Should I Optimize My Supply Chain Planning?” I’ll dive deeper into the concepts of supply chain optimization and show examples of when it’s ideal to optimize and when it’s less ideal. In today’s blog post, I’d like to simplify this concept by looking at some basic equations and scenarios to explain how “solvers” or supply chain optimization algorithms work.
In a recent study, Gartner estimates that 50% of Supply Chain Planning Solutions are not fully utilized1. How can organizations ensure that they have the user adoption needed to attain the full benefits from their existing or new supply chain solution?
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.
Naturally, supply chain optimization in supply planning can feel counterintuitive. Here’s why you should combat that feeling to create the best plan possible.