Are you really being selective enough on which bids to pursue or are you fooling yourself?
Part 1 of 3
Everybody says they are selective in choosing which bids to pursue, but are they really consistent?
The construction industry is estimated to spend over £2 billion on bidding every year. As the internal cost of responding to a bid starts at around £1.5k for consultants and £10k for contractors and can quickly escalate up to £0.5m and above for the big boys.
Therefore, identifying bids which have the highest or lowest chance of winning is a key factor if you want to win, as it allows limited resources to be focused on the “must win; can win” bids.
Firms should develop their own selectivity matrix to help them quickly evaluate bidding opportunities and enable consistency and transparency of decision taking.
The criteria to use should be based on your own historic win and lose factors, then applying weighted scoring. It should be capable of being tailored down to regional or office levels to accommodate differences in local service skills and work sector capability.
Enable prioritisation of key opportunities, with improved identification of those projects that are more likely to be won.
Identify tactical activities that could increase the chances of winning.
Provide visibility to the management team of 'must-win bids' within the opportunity pipeline.
Enable better prioritisation of investment in win work activities, to give better targeting and direction of win work resources.
Encourage more motivation in addressing important opportunities.
Over the last 10 years we have created numerous bespoke Selectivity Matrices that continue to help our construct clients achieve win rates that initially win 1:2, and over a a 3 year period average out to around 1:3.
If you would like help customising your own Selectivity Matrix for one office, or even 20 offices, we can offer low cost solutions starting from £500. Why not send us tweet and we can send you some more information? Or alternatively you can view how we helped Interserve Win More and Lose Less in their case study here