Today's Prompts. Analysis. Supply Chain & Logistics. Offer. Company Acquisition.LOI

Prompt 1: preparation time 5 minutes, max. Supply Chain + Logistics Offer Preparation

I have two datasets related to supply chain and logistics:

1. Doc 1: A historical list of items with associated attributes, prices, and logistics details, stored in an Excel file.
2. Doc 2: A new list that may contain items from the historical list, along with their respective attributes, stored in an Excel file.

I want to automate the following tasks to optimize supply chain and logistics:

1. Match items from Doc 2 with the historical data in Doc 1 based on their attributes, such as part number or description.
2. Identify the highest and lowest prices from the historical data in multiple currencies for each matched item.
3. Adjust the prices by a set percentage, using a function that accommodates varying percentage rates.
4. Calculate logistics estimates based on historical data and current logistics details, considering factors like transportation costs, lead times, and inventory carrying costs.

For the new document (Doc 3) representing the optimized supply chain offer, to be sent to a client, please follow the format below:

Columns in Doc 3, all in French:

1. Part Number (from Doc 2): The part number of the item from the new list.
2. Description (from Doc 2): The description of the item from the new list.
3. Quantity (from Doc 2): The quantity of the item required.
4. Matched Part Number (from Doc 1): The part number of the matched item from the historical data in Doc 1.
5. Matched Description (from Doc 1): The description of the matched item from the historical data in Doc 1.
6. Currency: The currency used for prices euro or usd
7. Highest Price (from Doc 1): The highest price of the matched item in the historical data.
8. Lowest Price (from Doc 1): The lowest price of the matched item in the historical data.
9. Adjusted Price: The adjusted price after applying the set percentage.
10. Logistics Estimate: The calculated logistics estimate for the item based on historical data and current logistics details.

note to user: here include any other relevant columns specific to your supply chain and logistics requirements.

Ensure the final document (Doc 3) is formatted with clear headings, appropriate data formatting, and visually appealing presentation for stakeholders.

Prepare for download in Excel.

Pros for Prompt 1:

Optimization, Efficiency, Data Accuracy, Cost Savings (by identifying the highest and lowest prices, it enables cost-saving opportunities in procurement or ability to manually choose medians), Clear Presentation.

Cons for Prompt 1:

Complexity, (understanding of prompts or plugs-ins, when available), Data Dependencies (the effectiveness of the analysis heavily relies on the availability and quality of historical and new data, and its format and accessibility), Data Compatibility: ensuring compatibility between the datasets (Doc 1 and Doc 2, or use correct lingo, data cleaning and formatting may be needed before hand)

Stakeholder Adoption: KEY!! Encouraging and Train stakeholders to embrace automated supply chain and logistics analysis may require change management efforts.

Disclaimer: The content of this post and prompt is based on proven supply chain practices utilized by our teams. This post is shared on my own behalf and represents my personal perspectives.?

Prompt 2: SME Acquisition, Basic Analysis, LOI

note to user: This process is streamlined and efficient but still requires several steps due to the various areas of ChatGPT4 we need to access. It serves as a good start and showcases the versatility of the AI-assisted method in conducting preliminary financial analysis for a potential SME acquisition.

You're in the process of acquiring a target company and have access to the following financial data:

Doc 1: Historical financial data of the target company, including balance sheets, income statements, and cash flow statements.

Doc 2: The target company's current financial request or projection, which may encompass data points from the historical dataset.

Additional Data: Market trends, industry analysis, and economic indicators pertinent to the target company's sector.

I want to automate the following tasks to analyze the financial viability of company acquisitions:

1. Cross-reference the current financial request or projection with the historical financial data and external market trends to gain insights into the target company's financial performance.
2. Identify the highest and lowest values from the historical data in multiple currencies, if applicable, for each financial metric, such as revenue, net income, EBITDA, and other specific indicators, add examples.
3. Adjust the values by a set percentage, incorporating dynamic rules based on market trends, industry benchmarks, and investment criteria relevant to the target company's sector. (note to user: load reports via chosen plug -ins, to be done in step 2 in a new chat)
4. Generate a new document (Doc 3) that includes the adjusted values, the date associated with each value (if available), additional derived financial metrics, and a comprehensive analysis of the target company's financial potential and risks. (note to user: You'll need to return to the initial chat to finalize Doc 3)
5. Calculate a total value for each financial metric in Doc 3 based on the highest adjusted value, the quantity from the financial request or projection, and relevant investment factors.
6. Prepare the final document (Doc 3) as an investment analysis report tailored to the specific needs of investment bankers, including detailed financial modeling, scenario analysis, risk assessment, and key findings specific to the target company's industry.
7. Save Doc 3 as an Excel file or a professionally formatted report for presentation and reference during the acquisition process. The report should be comprehensive, easy to navigate, and visually appealing to effectively communicate the financial story of the target company.

Note: This prompt focuses on the financial analysis aspect of acquiring a company, considering industry-specific details. The cross-referencing of Doc 2 with Doc 1 allows for financial analysis and insights into the target company's performance and potential. The generated document (Doc 3) provides a investment analysis report, incorporating financial modeling features and industry-specific metrics, to support investment banking decision-making during the company acquisition process.

While using this prompt and this process can be a powerful tool for the preliminary analysis, it does not replace the in-depth due diligence and professional advisory needed for an M&A transaction.

Disclaimer: The content of this post and prompt, including all expressed opinions and projections, are my own and do not reflect the views or positions of the companies I am associated with. Always consult with your legal and financial professionals for your own financial decisions.