No, there's always data up front. Every forecasting model I've ever seen starts with current and historic data (normally incomplete), extrapolates to build an idealised set, and forecasts according to some assumptions which are either derived from the data, or imported from some other data set which provides the proxy.
Having said that, every forecasting model I've ever seen has also needed to be congruent with some other requirement: previous work (so your team doesn't look silly & inconsistent), other predictions (herding happens everywhere), customer requirements (you get whatever model you pay for, or whichever model provides the most comfort to the most stakeholders).
And it's the assumptions that one has to play with to get that congruence; no-one likes falsifying data. In extremis, we declare an unhelpful data point an "outlier" before disposing of it.