Large organizations often face complex planning challenges, and when it comes to achieving business objectives within constraints, they necessitate trade-offs to make the best decisions possible. Understanding and predicting each possible outcome is really time consuming, and impossible in many cases. That’s where Anaplan optimizer is used, Business leaders must be able to properly evaluate these planning scenarios and make timely and accurate decisions.
Anaplan optimizer overview:
Anaplan’s optimization engine helps determine the optimal solution, improves planning efficiency, and makes decision-making faster.
Figure 1: Key benefits of Optimizer
Anaplan optimizer uses linear programming, mathematical concepts to maximize or minimize specified objectives. Once configured, it gives planners an objective and systematic way to consider all options, find the best solution, and steer the company in the right direction. Many common business issues are essentially resource allocation issues across targets. Anaplan optimizer can be used for improved allocation and scheduling in various business domains like supply chain, stock allocation, financial planning, sales, transportation routing etc.,
How does optimizer work in Anaplan?
With linear programming optimization, you must define objective functions and set multiple variables and constraints for the planning process. The solution to optimization is to maximize profit or minimize cost. Optimizer can provide recommendations for a variety of complex issues, including staffing, capitalization, inventory, and much more. Figure 2 shows the structure of the optimization model.
i) Objective function: Linear equation that specifies the target, function of input variables. Objective function includes variables and constraints. The first step in optimization is to identify the problem and create the equation or formula.
ii) Constraints: Assumptions for variables, for example the maximum number of products manufactured, available distribution centers, etc., you can set many constraints. Constraints are Boolean linear functions, used to restrict the values for variables.
iii) Variables: When you solve an equation, you will get many sets of solutions; they are variables. Optimizer will choose the most feasible solution. Variables are generally numerical values or Boolean values.
Figure 2: Structure of optimization model
We can add the optimizer action in the dashboard or New UX pages and run the process to find the feasible solution.
Use Case: Supply Chain Network
Imagine a Juice manufacturing company, producing 3 types of juices, and using 3 packaging types. The supply chain planner must manage the raw materials warehouse, manufacturing plants, Distribution centers, he needs to know what to produce to increase profit and minimize cost, and decide what distribution center should serve customer warehouse, transportation facilities and what manufacturing plants should supply to the DCs.
Figure 3: Supply chain network optimization
Supply chain planning is the process of forecasting demand and managing inventory so that we can keep costs down and deliver products faster. The goal of supply chain optimization is to fulfill global demand in the most efficient and profitable way.
Anaplan optimizer can be used to generate optimized plans based on global demand forecast which is already present as input in Anaplan model. For example, distribution center and maximum plant production capacity constraints are specified in the model. Transportation costs are added to the linear equation; the objective is to reduce the transportation cost from plant to DC’s. The optimizer generates a result which specifies what products should be shipped from each plant to Dc’s and in what quantity. Supply chain managers can create multiple scenarios and compare them, select the suitable one for business. Planners can be confident in the supply chain decision they make because all possible factors have been factored into the equation.
Conclusion:
Using Anaplan optimizer, we can achieve the optimal solution in the most efficient and profitable way. Business leaders can run optimization scenarios that link the financial implications of choice to a sales or supply chain problem, allowing for quick decision-making across the entire organization. Anaplan’s platform powers Optimizer, and all scenario customizations are done through the user interface. Anaplan optimizer has some limitations as well, such as the fact that it solves only linear equations and does not support version and time, and the best practice for optimizer is yet to be defined.
