How can you ensure the accuracy of data for budgeting and forecasting?

This is something that analysts deal with , first, projection or forecast isn’t real, all you do is give an intellectual guess by using past data but past result or previous performance should never guarantee future performance. Also, some people use certain data to predict the future or get the results that wanted so some people are biased when doing forecasts. If you have the right data, you can have an accurate forecast with less margin of error .

On top of ensuring your data quality based on sources, you should also take a chance to review preliminary results with business expert and assess data based on their business knowledge. Another relevant source of comparison and assessment is competitive data from other players in the same industry.

Accuracy of data can be verified by the following ways and I'm sure this has worked for me. Source Verification: Validate data from reliable, primary sources to ensure its accuracy and integrity. Regular Audits: Conduct periodic internal and external audits to identify and rectify discrepancies or inaccuracies in the data. Data Cleaning and Validation: Implement robust data cleaning processes and validation checks to filter out erroneous entries. Cross-Functional Collaboration: Involve relevant departments in data verification to incorporate diverse perspectives and expertise. Utilize Advanced Analytics: Leverage tools like regression analysis and anomaly detection to identify and rectify outliers or anomalies in the data.

Data source identification is key for every data user, it is highly imperative to understand the biases of the sources and evaluate the implications towards your end goal. since every quality data must aggregate towards sound decision making either to predict or for relevant corrections, it is important that these data are well selected from credible sources.

First, figure out what kind of data you need. Once you know, you can identify where to get this data, whether from industry reports, in-house records, past data, and so on. Knowing exactly what data you're after makes it easier to pinpoint the right sources.

From my experience, checking data is crucial whenever you use it. It's essential to validate data both before and after you've analyzed it to ensure its accuracy and consistency. While getting the data perfectly clean right away might not be feasible, you should aim for a specific quality range before sharing with relevant stakeholders.

Let's not confuse accuracy of data (the past) with accuracy of budget (future). Accuracy of data comes from a knowledge of actual. Unfortunately not many accounting systems are built for data analysis, which means that to be able to use the data you need to rework a lot of your accounting, which is a shame. In addition, your data should be associate with a strategy or a reason why this expense exists. Your budget should be built on that strategy then the data will flow.

The best way to start analyzing data is to build the intuition beforehand. A preliminary analytics always help based on the information you have gathered during the process. e.g During the discussion it came up that company will shift from rented office to own. Hence you can expect lower Opex and higher depreciation in the output. OR a business head talking about loosing big customer hence its impact on sales, inventory and AR etc. Accuracy of the numbers can be validated later however this intuition builds confidence on the output and helps in building story as well.

Perform sensitivity analysis to understand how changes in data variables impact the budget and forecasts. This helps in assessing the robustness of the predictions.

An important aspect not to forget is understanding what you have and how it is impacting business. A correlation of what you have, what and how things are impacted. Most importantly understand where you would like to be and which are the data points that will be influencing the outcome. Having data without understanding how to use it would not provide real value.

Knowing what data you need from the start helps shape the analysis you're aiming for. Start with your gut feeling, and through several iterations, you'll grasp the narrative you're crafting with the data. Using charts, graphs, and dashboards enhances your presentation, making your data storytelling more compelling and effective.

Before you rely on a financial model you created make sure you do some sanity checks: - complete the input data for the previous years and compare the output of your model versus your realized financials. If deviations are to big, check if you made calculation errors or if your assumptions are reasonable - if you are using spreadsheets model audit tools help you detect errors or inconsistencies in your model

Before presenting to stakeholders, always ensure a comprehensive review, particularly in areas like budgeting and forecasting where company resources are at stake. Thoroughly examine your analysis for potential errors. I've noticed that initial discussions with stakeholders can be quite beneficial. Their feedback aids in fine-tuning both the analysis and the presentation. Developing scenarios and suggestions from your findings not only enriches these discussions but also fosters critical thinking skills.

Once you have prepared your budget and forecast, the job is not done. Make sure to keep a close eye on how you are actually performing versus your budget / forecast. Do this on a frequent basis (monthly, at least quarterly) so you can identify where your assumption are not holding up. If the deviation from your budget / forecast is to big. Analyse what drives this deviation, and use this information to create a rolling forecast. Some tips to get better insight: - automate your budget actual insight, so you don't spend time crunching the numbers, but create time for analysis - make sure you have a management reporting tailored to you business so you can easily link the numbers to you business - prepare your budget with this format in mind

System support Select a system to capture your budget data, that way you ensure errors from contributors and you can track outliers or other suspicious behavior.