How to support accurate revenue forecasting with data science and dataops
Briefly

from InfoWorld3 months ago
"Forecasting is essential for the financial success of every organization, but it's often a significant challenge," says Arnab Mishra, CEO of Xactly. "Sales and finance teams encounter common obstacles when making forecasts, including reporting systems that lack access to historical CRM or performance data and uncertainty about where the pipeline data is from. The most successful organizations have revenue and finance leaders who integrate innovative forecasting technology solutions and prioritize accurate forecasts."
InfoWorldhttps://www.infoworld.com/article/3583473/how-to-support-accurate-revenue-forecasting-with-data-science-and-dataops.html
According to the 2024 Sales Forecasting Benchmarking Report, 43% of respondents said their sales forecasts were typically off by 10% or more; 38% reported data quality issues; and 35% said the forecasting process took too long.
InfoWorldhttps://www.infoworld.com/article/3583473/how-to-support-accurate-revenue-forecasting-with-data-science-and-dataops.html
Data scientists and technologists should focus on leveraging data analytics and AI for strategic decision-making, aiding departments like finance, marketing, and sales in revenue forecasting.
InfoWorldhttps://www.infoworld.com/article/3583473/how-to-support-accurate-revenue-forecasting-with-data-science-and-dataops.html
Enterprises typically staff financial planning and analysis (FP&A) professionals who develop forecasting models, dashboards, and reports. Integration of machine learning and compliance with SEC regulatory guidelines are essential for public companies.
InfoWorldhttps://www.infoworld.com/article/3583473/how-to-support-accurate-revenue-forecasting-with-data-science-and-dataops.html
Read at InfoWorld
#revenue-forecasting #dataops #ai #business-analytics
[
|
]