1. Bidding Strategies

2. Outline of Presentation
Markup
Expected Profit
Cost of Construction
Maximizing Expected Profit
Case 1: Single Known Competitor
Case 2: Multiple Known Competitors
Case 3: The Average Competitors
The Use of Bidding Strategies
Examples of Bidding Strategies

3. Markup Final action before bidding is adding markup.
Markup is usually a percentage of the cost.
All items of job expense, including contingency and general overhead are already in the contractor’s estimate.
Contractor tries to select a markup that will enable him to bid the largest amount possible and still be the lowest bidder.

4. Markup Deciding a good markup is very subjective.
From past experience various bidding variables are analyzed: competition, type of work, geographical area, A/E, terms of contract etc.
These variables can give a fair idea of high or low markup for a particular project.

5. Expected Profit
When contractor bids a lump-sum job, potential profit of (b-c) is anticipated, where b= amount of bid and c= actual cost of work
Probability of successful bid- p is related to the amount of bid – b
Probability of being the lowest bidder (p) is also related to the expected profit.
Expected/potential profit= p(b-c)

6. Expected Profit
Example: consider a project with actual cost c= $50,000. Suppose the contractor knows that the probability of $56,000 bid has a probability of 0.3 and that a bid of $53,000 has a probability of 0.8.
When b=$56,000
Expected profit=0.3( ) =$1,800
When b=$53,000
Expected profit=0.8( )=$2,400

7. Expected Profit
The bid of $53,000 is better because the expected profit is greater.
The probability of 0.3 and 0.8 is instrumental in deciding the bid.
Expected profit represents the average return per bid if the bidding is repeated a large number of times.

8. Cost of Construction
The cost-c is the actual cost of construction but unfortunately it cannot be exactly known till the construction is done.
Cost is an important element of bidding strategy.
Assumption is made that c is same as the estimated cost.
Validity of this assumption depends on contractors past record of bidding accuracy.

9. Cost of Construction

10. Cost of Construction
Figure G.1studies the bidding performance of the contractor.
V=actual construction expenses/estimated cost
Fig G.1 shows the number of occurrences of V in each interval of 0.05
These data is plotted to obtain a histogram as shown in Fig G.2 and a frequency polygon is drawn utilizing the midpoints of the horizontal bars of histogram.

11. Cost of Construction

12. Cost of Construction
Smoothed frequency polygon of past bidding resembles normal distribution of small variance with mode close to the value V of 1.0 as in curve A of Fig G.3 then the bidding accuracy is good.
Curve B also has mode close to V=1, large dispersion of values indicate loose estimating
Curve C shows estimating errors leading to consistent over estimating or under estimating

13. Cost of Construction

14. Maximizing Expected Profit
Consider the estimated cost is $200,000
Assume the probability of success for different bids as shown in Fig G.4
Fig G.4 shows that a markup of 5% which gives a bid of $210,000 yields the maximum expected profit and thus is the best bid.

15. Maximizing Expected Profit

16. Case 1: Single Known Competitor
Before bidding strategy is developed the values of probability of bidding success must be determined from historical data.
In this case the contractor knows the competitor and has experience bidding with this competitor.
Since the bids are opened in public and read aloud, the past bids of competitors is also known.

17. Case 1: Single Known Competitor
Suppose using the past data of the competitor A and the contractor compiles the information as shown in Fig G.5.
The data is for 62 times the contractor and competitor A has bid in the same projects in the last 5-6 years.
R=bA/c where bA is the competitor A’s bid and c is contractors estimate.

18. Case 1: Single Known Competitor

19. Case 1: Single Known Competitor
Probability PA can be computed from data of G.5
If the contractor bids a ratio b/c = 0.98, the probability that it will underbid competitor A is 1.0 because at no time has A ever bid this low.
If contractor bids at cost (b/c=1) there is 1 chance in 62 of being lowest bidder.
Expected profit is obtained from these values

20. Case 1: Single Known Competitor

21. Case 1: Single Known Competitor

22. Case 2 : Multiple Known Competitors
Two known competitors A and B
Past bidding record of B is analyzed in the same way as that of A in previous section
Both probabilities of A and B are independent of each other. We can find the probability of beating both A and B by multiplying their probabilities as shown in Fig G.8
Fig G.9 shows the expected profit when bidding again both A and B

23. Case 2 : Multiple Known Competitors

24. Case 2 : Multiple Known Competitors

25. Case 3 : The Average Competitor
Average bidder is hypothetical competitor whose bidding behavior is a statistical composite of the behaviors of all competitors.
Collective bidding pattern of competitors can be obtained by combining all competitors into one probability distribution.
In Fig G.10, Pav is the probability that the contractor will submit a bid lower than a single unknown competitor.

26. Case 3 : The Average Competitor

27. Case 3 : The Average Competitor
If there are 3 unknown competitors than the probability will be 3 times the probability of one unknown contractor as they are independent variables.
Fig G.11 shows that if the markup is 8% then the probability it will be underbid all three unknown competitors is (0.51)(0.51)(0.51) which is 0.13.
Fig G.11 also shows expected profit.

28. Case 3 : The Average Competitor

29. The Use of Bidding Strategies
Bidding involves trying to outguess and outsmart the competition.
Systematic analysis of past bidding experience is not common in industry.
Probabilities can be computed for different categories of projects.
Greater weight could be given to recent bidding information as compared to old information.

30. Examples of Bidding Strategies
Choose types of projects in which the bidder’s company has demonstrated competency.
Advantages of this are:
Owners approval in case of being 2nd lowest bidder.
Experience reduces construction cost thus reduce bid.
Competitive prices from sub contractors and suppliers based on their knowledge of bidder’s competency.

31. Examples of Bidding Strategies
Improve and use effectively knowledge of competitors strengths and weaknesses.
This information can be used as guide for:
Choice of projects to bid
How competitively to bid
How much markup to apply to the bare cost.
How much risk to take.

32. Examples of Bidding Strategies
Favor projects with the least number of bidders.
This strategy increases the probability of the contractor to win the bid.
There may be exceptions for example it may be better to bid for a project with 8 relaxed competitors as compared to a project with 3 extremely competitive competitors.

33. Examples of Bidding Strategies
Choose those projects that have the highest profit margin as compared to completion time
This may not increase the probability of low bid but it may increase the potential of total profit within an year.
Y creates faster ROI
Reduces overhead
Personnel available sooner
Project
Potential Profit, $
Completion time X
180,000
18 months Y
150,000
12 months

34. Examples of Bidding Strategies
Bid as many well selected projects as possible.
Bidding on increased number of projects increases the probability of winning more low bids.