The advancement of science, a proliferation of data and the accelerated development of computing capabilities has led businesses to be more inquisitive in relation to tools and technologies.
One phenomenon that has emerged is algorithmic forecasting, which relies on historical data and statistical models to predict what is likely to happen in the future. Algorithms are chosen and modern computing capabilities make collecting, storing and analysing data fast and affordable.
Forecasting has traditionally been, and is still seen by many organisations today, a time-consuming process, based on spreadsheets and with limited use of external drivers. With three out of four organisations still using spreadsheets to prepare plans, budgets and forecasts, we are yet to see organisations scale and adopt algorithmic forecasting across the enterprise.
Indeed, 94% of respondents do not currently use algorithmic forecasting and 30% of respondents state that current planning processes focus more on what has happened rather than what will happen. Organisations have clearly been hesitant about adopting algorithmic forecasting to complement or part-replace traditional planning techniques, but do recognise that it can provide a useful reference point in the planning, budgeting and forecasting (PB&F) process.