Business Analytics: Sonoma Valley Wine
Sonoma Valley Wine's Data-Driven Optimization Model was developed as part of a team project. Owner George Clarke will utilize this model to increase his profitability over a two-year time period. The model was developed using Financial Modeling, Linear Programming and Scenario Analysis to identify the most profitable wine production, pricing and marketing strategies.
Optimized Sales: 4,470 Malbec wines and 6,703 Riesling wines produced in Year 1, 54,902 Malbec wines and 23,530 Riesling wines produced in Year 2.
Projected Total Profit $617,652.19
Scenario Analysis: Pricing changes, Evaluating Marketing Constraints, Evaluating Product Mix
Through the application of this Data-Driven Model, George Clarke is able to receive scalable business knowledge and provide the means for Adaptability to Market Trends, Optimal Resource Utilization and Long Term Profitability.
Winery
February 4, 2025 at 7:54:16 AM
Winery Business Analytics Project - Sonoma Valley Wine Optimization
As part of our group project, we were required to develop an overall business analytics and optimization model for Sonoma Valley Wine, which was owned by George Clark. Our objective was to help George with his data-driven decisions on wine production, marketing outlays, pricing, and profit maximization over two years.
Project Overview
The project involved financial modeling, optimization approaches, and scenario planning to help George make decisions on allocating his resources to the maximum profit. We applied linear programming, the Solver technique, and scenario planning to develop a decision support model that responds to the dynamic environment in the business.
The final optimized recommendation proposed the production and sale of
Year 1: 4,470 Malbecs and 6,703 Riesling, finding a balance of prices according to market
Year 2: 54,902 bottles of Malbec and 23,530 bottles of Riesling, depending upon market strategies and market demand.
Total projected profit: $617,652.19
Important elements of this project include
1. Evaluative Model (Baseline Financial Model)
A financial model was developed to examine expenses, revenue, and variables of choice such as grape purchases, advertising, and price per bottle.
George's business processes had been understood on the basis of the sales estimates and the efforts put in by the marketing department.
2. Optimization Model (Profit Maximization using Solver)
We developed an LP model to minimize the cost of winemaking and marketing while taking into account constraints such as budget constraints, product mix constraints, and market forecasts.
We used Microsoft Excel Solver to identify optimal allocations of resources in order to maximize overall profit to George.
3. Scenario Analysis (Business Strategy Evaluation)
We worked with several real-life business cases to assist George in making the right strategic decisions for the firm, including the following:
Scenario C: The ‘Three Buck Charles’ Label
George had the choice to procure cheaper grapes to sell Riesling wine in a private labeling deal at $4 per bottle.
We analyzed whether such an action would result in enhanced profitability and the impact that would have on the position of the brand.
Scenario E: "Save Him Some Money" Advertising Restrictions
There was a marketing constraint that limited George’s advertising budget in Year 2 to five times his budget in Year 1.
We analyzed the impact of this on sales volumes, brand awareness, and overall profitability.
Scenario G: The Vintner’s Conference Industry Trend
George will need to increase the amount of Malbec to at least 55% of his total wines to comply with market trends as advised by multiple industry experts.
Through our analysis, we will determine how beneficial it would be financially for George to follow this trend.
The following highlights our final recommendations and insights regarding the business
Data-Driven Decision Making ‒ The utilization of the model creates a methodical allocation of resources for the firm; focusing the organizational effort toward developing an efficient system for developing products while generating sustainable revenues.
Flexibility in the Business Model ‒ The optimization framework will allow George to adjust for varied industries and product types simply by modifying the cost structures and constraints within the model.
Plan for Marketing and Production ‒ George's strategies should include a focus on placing targeted advertising and developing a balance of all product types within his product line for maximizing future profitability.
Scalability and Future Use of the Business Model ‒ There is a provision within the model to continuously modify input variables with regard to product costs, marketing budgets, production constraints, etc., as the evolution of the business occurs.
In conclusion, this project allowed us to combine three areas of advanced management: Business analytics, financial modeling, and optimization methodologies. The framework we created so that George could track his company's profits, customer behavior, and operations consistently will allow him to develop data-driven strategic decisions, as well as establish a scalable path for future business growth.
Project problem
Project Solution
Winery Business Analytics Project - Sonoma Valley Wine Optimization
As part of our group project, we were required to develop an overall business analytics and optimization model for Sonoma Valley Wine, which was owned by George Clark. Our objective was to help George with his data-driven decisions on wine production, marketing outlays, pricing, and profit maximization over two years.
Project Overview
The project involved financial modeling, optimization approaches, and scenario planning to help George make decisions on allocating his resources to the maximum profit. We applied linear programming, the Solver technique, and scenario planning to develop a decision support model that responds to the dynamic environment in the business.
The final optimized recommendation proposed the production and sale of
Year 1: 4,470 Malbecs and 6,703 Riesling, finding a balance of prices according to market
Year 2: 54,902 bottles of Malbec and 23,530 bottles of Riesling, depending upon market strategies and market demand.
Total projected profit: $617,652.19
Important elements of this project include
1. Evaluative Model (Baseline Financial Model)
A financial model was developed to examine expenses, revenue, and variables of choice such as grape purchases, advertising, and price per bottle.
George's business processes had been understood on the basis of the sales estimates and the efforts put in by the marketing department.
2. Optimization Model (Profit Maximization using Solver)
We developed an LP model to minimize the cost of winemaking and marketing while taking into account constraints such as budget constraints, product mix constraints, and market forecasts.
We used Microsoft Excel Solver to identify optimal allocations of resources in order to maximize overall profit to George.
3. Scenario Analysis (Business Strategy Evaluation)
We worked with several real-life business cases to assist George in making the right strategic decisions for the firm, including the following:
Scenario C: The ‘Three Buck Charles’ Label
George had the choice to procure cheaper grapes to sell Riesling wine in a private labeling deal at $4 per bottle.
We analyzed whether such an action would result in enhanced profitability and the impact that would have on the position of the brand.
Scenario E: "Save Him Some Money" Advertising Restrictions
There was a marketing constraint that limited George’s advertising budget in Year 2 to five times his budget in Year 1.
We analyzed the impact of this on sales volumes, brand awareness, and overall profitability.
Scenario G: The Vintner’s Conference Industry Trend
George will need to increase the amount of Malbec to at least 55% of his total wines to comply with market trends as advised by multiple industry experts.
Through our analysis, we will determine how beneficial it would be financially for George to follow this trend.
The following highlights our final recommendations and insights regarding the business
Data-Driven Decision Making ‒ The utilization of the model creates a methodical allocation of resources for the firm; focusing the organizational effort toward developing an efficient system for developing products while generating sustainable revenues.
Flexibility in the Business Model ‒ The optimization framework will allow George to adjust for varied industries and product types simply by modifying the cost structures and constraints within the model.
Plan for Marketing and Production ‒ George's strategies should include a focus on placing targeted advertising and developing a balance of all product types within his product line for maximizing future profitability.
Scalability and Future Use of the Business Model ‒ There is a provision within the model to continuously modify input variables with regard to product costs, marketing budgets, production constraints, etc., as the evolution of the business occurs.
In conclusion, this project allowed us to combine three areas of advanced management: Business analytics, financial modeling, and optimization methodologies. The framework we created so that George could track his company's profits, customer behavior, and operations consistently will allow him to develop data-driven strategic decisions, as well as establish a scalable path for future business growth.
Project problem
Project Solution