Bidding Strategies In Construction Construction Essay

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The process of tender evaluation and contractor selection is perhaps one of the most critical undertakings performed by the client; however, the ability to do so effectively is related to project success, the achievement of specified objectives and adequate return on investment for the client.

Contract bidding, like all other forms of pricing, is essentially about contractors making strategic decisions in respect of which contracts to bid for and the bid levels necessary to secure them.

Bidding contractor draws out estimates of the likely costs of carrying out the construction project work through project plans and schedules and adds a percentage mark-up to form the bid value. The value of the mark-up plays a big role in the chances of a bidder winning the contract and the subsequent profit should the contract be secured and the work is completed. A low mark-up value should increase the chance of winning but decrease the profit, whilst a high mark-up should increase the profit but decrease the chances of winning.

The selection for bidding strategy is based on the analysis of the bidder's internal and external circumstances. In some cases, the corporate level strategies are incorporated into bidding strategy for obtaining and sustaining competitive advantage for the long-term not just for securing the contract.

Strategic decision making in construction contracting is seen by Newcombe et al (1990) and Male (1991a) to occur at the (1) corporate, (2) business and (3) operational strategy levels within an organisation.

In deciding to bid the contractor has a two-stage decision process to make - whether to bid or not and the bid level to secure the contract (Skitmore 1989). In deciding whether to bid contractors are likely to consider both their current workload and future available work in the construction market.

If the contractor opts to submit a bid, the pricing of the bid normally comprises a two stage formulation process comprising baseline estimate and mark-up. The baseline estimate is formulated at the operational strategy level and then fed back to the business strategy level where senior management decides the appropriate bid level at an adjudication meeting. Long- term differences between bidders' pricing are a reflection of their relative efficiencies - more efficient bidders tending to enter lower bids, thereby over a series of competitions being more able to achieve higher levels of competitiveness. Four sources of cost efficiency have been identified by Johnson and Scholes (1993) as comprising economies of scale, supply costs, product process design and experience.

CRITIQUE As part of their bidding strategy, it has been suggested by Drew and Skitmore (1993) that different bidders will have different degrees of preference towards the individual contract characteristics, such as size, type and location of proposed contracts and in determining mark u levels, different bidders have differing degrees of selectivity between contracts. Those who are more selective concentrate on particular contract characteristics. Those who are less selective place less emphasis on contract characteristics than on other factors such as workload or resources available. Bidders who select contracts carefully for which they enter serious bids may be regarded as `market' or `preference driven'. Those bidders who place most emphasis on workload may be regarded as `resource' or `constraint driven'. These categories are neither exhaustive nor mutually exclusive and some bidders may place equally high or low emphasis on market and resource factors.

The baseline estimate is usually combined with a mark-up to form the bid. Different bidders apply different mark-up policies which may be variable or fixed which in turn influence mark-up levels and thus competitiveness. Bidding strategy is concerned with setting the mark up level to a value that is likely to provide the best pay-off. Male (1991a) points out that standard bidding models presume that bidders attempt to maximise their expected profit. The bidder, however, may be attempting to fulfil other objectives including minimising expected losses, minimising profits of competitors or obtaining a contract, even at a loss, in order to maintain production.


Strategic mark-up bidding assumes that the bidder applies a mark-up which happens to produce a satisfactory balance between the probability of winning the contract and the profit generated as a result of winning the contract. A special case of strategic mark-up bidding is optimal bidding, defined as applying a mark-up which happens to maximize expected profit, i.e. the product of the probability of winning the contract and the profit generated as a result of winning the contract

The literature on strategic mark-up bidding is quite extensive and several reviews have been published (for example, Reference 2).

All the work to date has been based on two bivariate models. The Friedman' model compares the strategic bidder with individual competitors while Hanssmann and Rivett3 compare the strategic bidder with the lowest bidders. However, the Friedman model has been frequently criticized as demanding unrealistic amounts of data to estimate the model parameters (for example, Reference 4) especially for construction contract auctions (for example, References 5 and 6). The Hanssmann and Rivett model partially solves this by reducing the number of parameters in the model and thus the data demands, but with a loss of predictive power.

Multivariate methods offer a means of better utilization of all available data, depending on the adequacy of certain assumptions concerning the statistical properties of bids. In this case an individual bidder is not restricted to data for auctions in which he/she has been a participant, as is the case with bivariate approaches. Instead, the bidder is able to incorporate data for all auctions in which competitors, and potential competitors, have been participants irrespective of the individual bidder's participation. This increases, by several orders of magnitude, the amount of data available for estimating the model parameters. Recent empirical studies7 indicate that, with suitably transformed data, the assumptions implicit in multivariate approaches may not be unduly violated in construction contract auctions.

The application of multivariate methods to sealed bid mark-up strategies offers a potential improvement on previous bivariate methods in providing a means of better utilization of all available data. Since it has been shown that, with suitably transformed data, the necessary assumptions concerning the statistical properties of bids may not be unduly violated in construction contract auctions7, a multivariate model has been proposed for deriving 'optimal… (CONTD on the last paragrapgh of CR4)


Two-envelope fee tendering, have been urged to consider variability differences between fees and technical scores, since the criterion with the greatest variability will influence which consultant is awarded the contract.

Fee and technical score variability arising from different client fee tendering competitions is analysed in this paper, and a method proposed for determining whether a particular client's two-envelope fee tendering competition is likely to be dominated in terms of technical score or fee. Such information should be useful to consultants, as part of their bidding strategy, in deciding whether to aim for a higher technical score or submit a lower fee.

Normally, consultancy contracts are awarded on the basis of price (i.e. fee) and quality (i.e. technical score). Usually, the contract is then awarded to the consultant with the best overall score.

CRITIQUE In such situations consultants are faced with the problem in deciding whether to aim for a high technical score (which usually requires a higher fee) or submit a low fee (which is more likely to attract a lower technical score) or somewhere in between these two extremes

Below-Average Bidding Method

The low-bid method where the contract is awarded to the firm submitting the lowest responsible bid.

Competition on price encourages contractors to adopt cost-saving technological and managerial innovations and then pass these savings on to the owner who receives a project of specified quality at the lowest price.

CRITIQUE When the number of bidders is large, however, as is the case in a slow economy, an owner runs a significant risk of selecting a contractor that has either accidentally or deliberately submitted an unrealistically low price.

A contractor cannot adhere to such a price and at the same time expect to complete the project according to plans and specifications and also make a reasonable profit. This often results in excessive claims and disputes during construction that lead to schedule delays, compromises in quality, and increased costs

In response to these problems, some countries have recognized that the lowest price may not be the best price for the owner and developed bidding procedures based on the average of the bids received. The rationale for these methods is that a price close to the average should offer a fair price to the owner and allow the contractor to perform the work at specified quality and at a reasonable profit.

Average-Bid Methods

Over the years, several competitive bidding methods have been developed where the winner is determined by comparing the submitted bids to their average.


In general, the winner based on the average-bid method is the contractor whose bid satisfies a certain relationship with the average of all bid prices.

Different average-bid methods use different procedures for calculating the average, or use different criteria for determining the Winning bid. For ex- ample, some use an arithmetic average or a weighted average, while others use the average of the remaining bids after all bids that differ more than a certain percentage from the average of all other bids are eliminated. Similarly, the winner might be the contractor whose price is closest to the average, or the contractor whose bid is closest to, but less than the average.