Bidding Strategies

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Bidding Strategies
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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

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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
  contractors estimate.
• Contractor tries to select a markup that will
  enable him to bid the largest amount possible and
  still be the lowest bidder.

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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.

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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)

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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 b56,000
• Expected profit0.3(56000-50000) 1,800
• When b53,000
• Expected profit0.8(53000-50000)2,400

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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.

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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.

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Cost of Construction
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Cost of Construction

• Figure G.1studies the bidding performance of the
  contractor.
• Vactual 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.

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Cost of Construction
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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 V1, large
  dispersion of values indicate loose estimating
• Curve C shows estimating errors leading to
  consistent over estimating or under estimating

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Cost of Construction
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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.

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Maximizing Expected Profit
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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.

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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.
• RbA/c where bA is the competitor As bid and c
  is contractors estimate.

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Case 1 Single Known Competitor
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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/c1) there is 1
  chance in 62 of being lowest bidder.
• Expected profit is obtained from these values

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Case 1 Single Known Competitor
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Case 1 Single Known Competitor
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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

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Case 2 Multiple Known Competitors
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Case 2 Multiple Known Competitors
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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.

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Case 3 The Average Competitor
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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.

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Case 3 The Average Competitor
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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.

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Examples of Bidding Strategies

• Choose types of projects in which the bidders
  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 bidders
  competency.

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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.

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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.

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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

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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.