Alteryx > Case Studies > Prescriptive Analytics: Unleash the Optimization Tool

Prescriptive Analytics: Unleash the Optimization Tool

Technology Category

Analytics & Modeling - Predictive Analytics
Application Infrastructure & Middleware - Data Visualization

Applicable Industries

Buildings
Equipment & Machinery

Applicable Functions

Procurement

About The Customer

Philip Mannering is an analyst at ClarusOne Sourcing Service. He has been using Alteryx for two years and has become an Alteryx Designer Expert Certified. He also won the Grand Prix at Inspire Nashville. Mannering is an expert in using prescriptive analytics and the Optimization Tool to solve complex business problems. He has demonstrated his expertise in this use case, showing how to solve a problem with one or two variables and how to find the best solution to pressing business questions.

The Challenge

Philip Mannering, an analyst at ClarusOne Sourcing Service, was faced with the challenge of optimizing the production of chocolate bars to maximize profit. The problem involved determining the number of chocolate bars to produce, given the cost of each bar and the constraints of the available resources. The challenge was further complicated by the introduction of a second type of chocolate bar, which added another variable to the equation. The goal was to find the optimal solution that would yield the highest profit, taking into account the constraints of the available resources. This required a shift from descriptive and predictive analytics to prescriptive analytics, which not only predicts what will happen but also prescribes the best course of action.

The Solution

Mannering used Alteryx's Optimization Tool to solve the problem. He started with a simple example involving one decision variable - the number of chocolate bars to produce. He defined the objective function (the profit to be maximized) and the constraints (the available resources). He then plotted the constraints on a graph to find the optimal solution. The Optimization Tool provided the output, indicating the number of chocolate bars to produce to maximize profit. Mannering then expanded the problem to include two decision variables - the number of two different types of chocolate bars to produce. He used the 'variables in rows' tool configuration to support the structure of the input data. He plotted the constraints on a graph and found the optimal solution that yielded the highest profit. The Optimization Tool provided the output, indicating the number of each type of chocolate bar to produce.

Operational Impact

The use of the Optimization Tool and prescriptive analytics has taken the business analysis to the next level. It has enabled the identification of business problems that require optimization, setting of the objective function and list of constraints, preparation of inputs, and interpretation and presentation of results. The tool has provided precise recommendations on the best course of action, not based on probability but on the optimal solution that yields the highest value. This has led to more effective decision-making and improved business outcomes.

Quantitative Benefit

The optimization tool helped determine the optimal number of chocolate bars to produce to maximize profit.
The tool was able to handle multiple decision variables, allowing for the optimization of production of two different types of chocolate bars.
The optimal solution for two decision variables yielded a total profit of 55, which was higher than the profit from producing a single type of chocolate bar.