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Comments In my previous articleI introduced prescriptive analytics, the most advanced area of decision support on the analytics maturity spectrum. Prescriptive analytics provides the best outcomes for modeled situations based on the powerful concepts of optimization.
Optimization entails deciding how to best leverage limited assets, time and resources in situations with varying levels of uncertainty.
Literally everyone applies prescriptive analytics in their daily life and may not realize it or may not be using a mathematical model. Common prescriptive applications include staffing projects, determining budget usage, setting prices, deciding to pursue a proposal, managing a financial portfolio or running a business.
If you went to business school, optimization models were most likely covered in your operations or management science courses. In this article, I will walk through a simple optimization example using mathematical programming MP techniques with two of the most popular prescriptive analytic modeling tools on the planet, Excel and an Excel add-in called Frontline Systems Solver.
This first example will be fairly easy to start our journey and introduce solution space concepts. Prescriptive analytic optimization models combine historical data, business rules, variables, constraints and desired outcomes.
All optimization problems have three key elements: An objective is a measure to optimize, such as profit.
The decisions to be made are called decision variables and are typically amounts of inputs or outputs. For example, a decision may be how many hours to staff personnel or how much money to invest. Constraints are logical restrictions or limits, such as available hours in a day or budget.
To begin solving an optimization problem, you structure the optimization problem as a mathematical model with these three optimization element types in an Excel spreadsheet. If you want to follow along, feel free to download and install a free trial of Frontline Systems Solver Analytic Platform The add-in is compatible with Excel versions to The for-fee version of Solver that I am showcasing in this article is much more feature rich than the free Solver add-in that comes installed with Excel.
The Analytic Solver Platform truly provides best-in-class Excel add-in tools for solving prescriptive analytic problems. The Analytic Solver Platform trial includes a wonderful array of optimization, simulation and stochastic model examples. There are also video tutorials and white papers available on the Frontline Systems website for further reference.
After downloading and installing the trial version, navigate to the added Analytic Solver Platform menu item in Excel, choose Help, Examples and a spreadsheet containing links to all of the available example models will be displayed.
Mouseover image to enlarge. What is immediately notable is the optimization model that you create for use with Solver looks no different from any other Excel spreadsheet model.
What makes this model different is the impressive Solver engine that deciphers the model and runs the decision science algorithms. The Solver engine is far more advanced than the base Excel engine. In the Advertising Media Mix example problem, we want to minimize advertising costs, while meeting our goals of reaching a minimum total audience for each channel, and not exceeding a budgeted number of ad impressions.
To break this down into a solvable model, we first define an Objective, a formula calculating advertising costs that Solver will minimize.Analytics Empowering customers to respond to changing business conditions as they happen.
Integration of Data If managed well, complex data can significantly reduce a company’s bottom line.
Web Tools Our customers agree, ARI has the most efficient, most intuitive fleet information platforms in the industry. Rushabh Vedia Application of Analytics in the Transportation Industry’s Fleet Management Abstract The reference article, ‘Leveraging Analytics in Transportation to Create Business Value’, discusses problems concerning some disciplines in the transportation industry and showcases how analytics could be used to create business value by citing real life examples.
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Business analytics vs. data science.
The more advanced areas of business analytics can start to resemble data science, but there is a distinction. Even when advanced statistical algorithms are applied to data sets, it doesn't necessarily mean data science is involved.
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