Predicting Your Exit Multiple With Real Data
A credible exit multiple prediction is grounded in sector data, comparable transactions, and macro factors, updated continuously rather than fixed as a static benchmark set once at acquisition and never revisited. Markets, comparable transaction multiples, and macro conditions all move over a typical hold period, and a multiple prediction that isn't updated against current data is really just describing conditions at some earlier point in time, useful for the original deal thesis, not for current decision-making.
Why a static multiple assumption ages badly
The multiple assumed at acquisition reflects the market conditions of that specific moment. Two years into a hold, sector sentiment, comparable deal activity, and macro conditions can all have shifted enough that the original assumption no longer describes anything real, yet many funds keep using it because updating it wasn't built into the process.
What "continuously updated" actually requires
A live feed of comparable transaction data, sector-specific multiple trends, and macro indicators, combined with the company's own domain scores, not a manual once-a-year exercise that quickly goes stale again after it's produced.
How this changes the conversation with management
Instead of an abstract exit target, management gets a live view of what specifically would move the predicted multiple, which domain, which layer, turning exit preparation into an ongoing operational conversation rather than a scramble in the final year before sale.
One Model. Every Portfolio Company. The Same Definitions.
Orbicul turns EBITDA-era portfolio reporting into a real-time valuation model, 4 layers, 8 domains, portfolio-wide, so you see where value is created or blocked before it shows up in the numbers.