Tendering is the keystone in any business as it drives business prospects. Currently, the bidding process purely depends on human experts who can price tender using niche estimation software (‘Software1). It predicts offers as of the date of submission or gives some high-level risk analysis of some elements. It does not predict any causal effects of several future events, which could overturn the business prospects. For example, hundreds of resources are to be priced by the tender team in a building tender, such as Materials, Plant, Manpower, staff, subcontractors, and suppliers.
The current tender analysis does not give any predictive analysis of these items and their future impacts, which could badly affect a business. Similarly, several causal effects impact the tender, such as price escalation, market risks, site conditions, design and construction risks, socio-economic conditions, regulations, financial security, political stability, cultural issues, environmental impacts, force majeure, etc.
The human experts + Software 1 (Niche) + Software 2 (Machine learning) (“AI-Driven Tendering”) approach would ensure a secured offer with an in-depth analysis of every event, and it uses data in the machine learning to predict the causal effects of all variables to mitigate risks. It gives a reliable way of pricing tenders without risks. This revolution in tendering could improve business efficacy as it has a considerable market value, almost $13 Trillion global tenders per annum!