Here's how you can improve your forecasting accuracy with feedback.

To improve your budget forecasting accuracy, solicit and incorporate feedback from various stakeholders throughout the budgeting process. This includes gathering insights from department heads, finance teams, and operational managers who have firsthand knowledge of their areas' costs and revenue. Regularly compare your forecasts to actual financial results, analyze variances, and use these insights to refine your forecasting models and assumptions. Additionally, consider external factors like market trends, economic indicators, and industry benchmarks to make more informed projections. By continuously learning from past performance and adjusting your methods based on feedback and data analysis, you can enhance precision and reliability

Forecasting is activity to achieve short term targets. It is created by considering budget, addon planning of the management, and inputs which are not considered in budget. It needs historical information to create to set short term Target along with planning.

Improving forecasting accuracy is a multifaceted process that involves comprehensive data collection, ensuring data quality, applying advanced analytical techniques, and fostering continuous improvement. By incorporating historical financial information, customer feedback, market trends, and competitor analysis, FP&A professionals can create more nuanced and reliable forecasts. Ensuring the accuracy and reliability of data is crucial. Utilizing predictive analytics, scenario planning, and sensitivity analysis further enhances forecasting precision. Regular reviews, stakeholder engagement, and adopting advanced technology are essential for refining the forecasting process and achieving better financial and strategic outcomes.

Pour améliorer la précision des prévisions, il est essentiel de commencer par recueillir des données de manière systématique. Cela inclut les données historiques, les performances passées et les retours d'expérience des différents départements. Par exemple, dans mon entreprise, nous utilisons un système centralisé de collecte de données qui nous permet de suivre les performances de chaque projet et d'identifier les domaines à améliorer. En plus, je n'avais aucun problème à échanger avec tous les responsables et leurs demander leurs feedback et leurs besoins.

To increase forecast accuracy, start by gathering extensive and relevant data. This entails not only reviewing previous financial data, but also examining consumer input, market trends, and competitive analysis. By combining many data sources, you may produce a more sophisticated prediction that takes into account diverse factors on your company's success. Remember that the quality of your forecast is highly influenced by the quality of the data you use, so take the time to validate and clean your data to ensure its trustworthiness, which will lead to more accurate and useful insights.

Trend analysis is useful to forecast sales from specific category of clients. It can useful if we do forecast category wise by excluding exceptional or one time revenue or cost.

Regular trend base and planned forecast must keep separate. Specific project base or specific period base forecast must be carry separately by refining forecast model.

La surveillance continue des résultats par rapport aux prévisions est essentielle pour identifier les écarts et comprendre les raisons derrière ces écarts. Dans mon entreprise, nous utilisons des tableaux de bord pour suivre en temps réel les indicateurs clés de performance (KPI) et ajuster nos prévisions en conséquence.

Forecast is also a estimate on fact and input based. to make it make it more accurate , segment / product wise forecasting should be monitor against actuals. 2% variance in terms of low value difference are consider good forecast projections.

En plus des étapes mentionnées, il est important de maintenir une culture de l'amélioration continue et de l'adaptabilité. Encourager les équipes à fournir un feedback régulier et à proposer des améliorations peut grandement améliorer la précision des prévisions. Par exemple, nous avons instauré un système de feedback anonyme qui permet à chacun de partager ses idées et ses suggestions sans crainte de jugement.