Dynamic Forecasting Holds the Key
The pandemic has accelerated the need for speed for businesses. Organisations today must act, react, and adapt faster to keep pace. Dynamic forecasting allows businesses to do just that. Dynamic forecasting is based on real-time data and updated on a rolling basis—typically quarterly or monthly. This is opposed to traditional annual budgeting and forecasts, or static planning, that is reliant on manual spreadsheets and have painfully long cycle times.
The benefits of adopting an integrated approach that combines dynamic forecasting and planning are manifold for businesses, resulting in not only enhanced speed and real-time insights but reduced manual labour and data errors.
A dynamic forecasting approach supports the deployment of technology such asintelligent automationto replace repetitive and transactional tasks, minimising human intervention. Machine learning capability helps detect and predict patterns in processes and outcomes, making scenario planning more efficient. Augmented analytics, in turn, provides valuable insights into a company’s performance to feed back into the next planning and forecasting cycle.
Dynamic forecasting clearly has major advantages and thereportindicates businesses are starting to pay attention. Our findings suggest 80% of firms view dynamic forecasts and projections as more valuable than traditional plans and budgets, and 75% consider predictive models as great sounding boards in volatile markets, especially for specialised functional areas.
增强的预测和模拟,然而r, are not enough if planning, analytics, and execution remain siloed. True value can be reaped when planning and forecasting are integrated with execution and analytics, along with automated processes, leveraging different data sources, workflows to control processes, and early warning mechanisms to indicate impending crises.