Here's how you can enhance your decision-making process for financial forecasts in projects.

Start by gathering all relevant data, including historical performance, market trends, and expert opinions. Then, use modeling techniques to analyze this information and generate projections. Don't forget to account for various scenarios and risk factors. Regularly review and update your forecasts as new information becomes available. And most importantly, always keep a crystal ball on your desk - not for actual predictions, of course, but to remind yourself that if financial forecasting were truly magical, we'd all be sipping piña coladas on our private islands by now. When in doubt, just remember: your forecast is probably about as accurate as a weather report for next month, but with 100% more spreadsheets and 50% less chance of rain.

Granularity in collecting data at lowest possible level holds key for a good forecast. Revenue forecasting should be planned at product level, region level, monthly, variants level.

Data source and authenticity of Data is the first step towards Forecasting. Once we have the sketch of the organisational Goal, We are clear on what kind of Data we will need for forecasting. Data and selection of appropriate information are key to forecast. We might not need all the information, but focusing on relevant information will lead our forecasting in the proper direction. Our focus should be RELEVANT & ACCURATE DATA and not just data. We need to see beyond spreadsheets and also consider offline information (Reliable) then only we will be able to have a Forecast which will be nearly too accurate.

Remember to remove one timers which won't be relevant for future periods. It can be any cost, rebate or credit which won't repeat in future

1. Data collection The source data should be relevant enough as might be using it to upload data on database to store it. 2. Forecasted data fields: source data file has key values ,no duplicates as it would affect the data validation process.More clean and accurate data it be will good for us to doing data analysis part. 3.Unique identifier :Source data should have one or more than one unique key fields so that it’s very easy for data analysis when comes to forecasted data. 4.Data Specification: Try to match the precision value format with source data and data load on database. Ex: if source data has (38,6) precision value format and database is set to have (7,6) value it not give you expected result based on the source data.

When we talk about forecasting, when we read any article about it, we will find it's something repetitive being said by all. BUT ITS NOT. The art of Budgeting and Forecasting is a multifaceted skill and seeing the same information from different angles might lead to some interesting facts. One of the ways to see this information would be in the form of trends or charts or pies or doughnuts. Seeing a Simple Bar chart might not answer or even you might have not understand the character; Use multiple charts, change the axis, link it with Industry trends, Check the normal Economics of the Industry and evaluate.

Integrate predictive analytics into your trend analysis to enhance the accuracy of your financial forecasts. By leveraging advanced statistical techniques and machine learning algorithms, you can uncover hidden patterns and make more reliable predictions about future financial performance. Predictive analytics helps you anticipate market shifts, seasonal fluctuations, and emerging trends, enabling you to make data-driven decisions and better prepare for potential challenges and opportunities.

Very easy to set assumptions, Usually when we are forecasting; Our assumptions are narrowly just in our heads and we try to make the big picture out of it. But in actuality, it might be absurd when the CEO of the Company sees it. How to overcome this, Today's Millennial world needs to see the assumption with real-life scenarios and challenges which a CEO would be expecting from a Finance professional. So we will have to think beyond normal assumption, But has to be backed up by strong research and study. Further, we can portray 2-3 scenarios with different ifs & buts; This will give wide options for thought to the CEO who might appreciate our Business acumen.

Assumptions in financial forecasting should not be static. Regularly revisiting and updating your assumptions based on new data and changing market conditions is crucial. This practice ensures that your financial models remain relevant and accurate over time. By continuously monitoring key indicators and adjusting your assumptions accordingly, you can better anticipate potential challenges and opportunities, leading to more resilient and adaptable financial plans.

Forecast should marry Management aspiration 1. It may happen that plain simple forecast numbers are not meeting the expectations and aspirations of management. It can be too low revenue, too high expenses. 2. In such cases, management comes will avenues / changes / plan to meet it's targeted results. 3. Such activities should be well documented and informed to responsible department.

The answer to this question is the introduction of GenAI.Now you need to move towards automating your tasks whether financial or non financial.The technical procedure required for these task is to be followed to reap the benefits of Prescritive Analytics which is the main feature of GenAI.The time required in manual task can now be utilized towards better decision making...