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Traditionally, decisions have been made through manual, in-person negotiations. advantage is that there is a very expressive language for finding, and agreeing to, win-win solutions between the supplier and the buyer. The solutions are implementable because operational constraints can be expressed and taken into account. On the downside, the process is slow, unstructured, and nontransparent. Furthermore, sequentially negotiating with the suppliers is difficult and leads to suboptimal decisions. (This is because what the buyer should agree to with a supplier depends on what other suppliers would have been willing to agree to in later negotiations.) The one-to-one nature of the process also curtails competition.
These problems have been exacerbated by a dramatic shift from plant-based sourcing to global corporatewide (category-based rather than plant-based) sourcing since the mid-1990s. This transition is motivated by a corporation's desire to leverage its spending across plants in order to get better pricing and better understanding and control of the supply chain while at the same time improving supplier relationships. (See, for example, Smock [2004].) This transition has yielded significantly larger sourcing events that are inherently more complex.
During this transition, there has also been a shift to electronic sourcing where suppliers submit offers electronically to the buyer. The buyer then decides, using software, how to allocate the business. Advantages of this approach include speed of the process, structure and transparency, global competition, and simultaneous negotiation with all suppliers (which removes the difficulties associated with the speculation about later stages of the negotiation process, discussed above).
[FIGURE 1 OMITTED]
The most famous class of electronic sourcing systems--which became popular in the mid-1990s through vendors such as FreeMarkets (now part of Ariba), Frictionless Commerce (now part of SAP), and Procuri--is a reverse auction. The buyer groups the items into lots in advance and conducts an electronic descending-price auction for each lot. The lowest bidder wins. (In some cases "lowness" is not measured in terms of price but in terms of an ad hoc score that is a weighted function that takes into account the price and some nonprice attributes such as delivery time and reputation.)
Reverse auctions are not economically efficient; that is, they do not generally yield good allocation decisions. This is because the optimal bundling of the items depends on the suppliers' preferences (which arise, among other considerations, from the set, type, and time-varying state of their production resources), which the buyer does not know at the time of lotting. Lotting by the buyer also hinders the ability of small suppliers to compete. Furthermore, reverse auctions do not support side constraints, yielding two drastic deficiencies: (1) the buyer cannot express his or her business rules; thus the allocation of the auction is unimplementable and the "screen savings" of the auction do not materialize in reality, and (2) the suppliers cannot express their production efficiencies (or differentiation), and are exposed to bidding risks (for example, if the buyer's desired package consists of multiple lots). In short, reverse auctions assume away the complexity that is inherent in the problem and dumb down the events rather than embracing the complexity and viewing it as a driver of opportunity. It is therefore not surprising that there are strong broad-based signs that reverse auctions have fallen in disfavor.
The New Paradigm: Expressive Commerce
In 1997 it dawned on me that it is possible to achieve the advantages of both manual negotiation and electronic auctions while avoiding the disadvantages. The idea is to allow supply and demand to be expressed in drastically more detail (as in manual negotiation) while conducting the events in a structured electronic marketplace where the supply and demand are algorithmically matched (as in reverse auctions). The new paradigm, which we call expressive commerce[TM] (or expressive competition[TM]), was so promising that I decided to found CombineNet, Inc., to commercialize it.
The finer-grained matching of supply and demand yields Pareto improvements (that is, win-win solutions) between the buyer and the suppliers. However, matching the drastically more detailed supply and demand is an extremely complex combinatorial optimization problem. We developed the world's fastest algorithms for optimally solving it. These algorithms are incorporated into the market-clearing engine, Clear Box[TM], at the core of our flagship product, the Advanced Sourcing Application Platform (ASAP).
Expressive commerce has two sides: expressive bidding[TM] and expressive allocation evaluation (also called expressive bid taking[TM]) (Sandholm and Suri 2001).
Expressive Bidding
With expressive bidding, the suppliers can express their offers creatively, precisely, and conveniently using expressive and compact statements that are natural in the suppliers' business. Our expressive bidding takes on several forms. ASAP supports the following forms of expressive bidding, among others, all in the same event. These forms will be explained in the following paragraphs.
[FIGURE 2 OMITTED]
Bidding on an arbitrary number of self-constructed packages of items (rather than being restricted to bidding on predetermined lots as in basic reverse auctions). The packages can be expressed in more flexible and more usable forms than what is supported in vanilla combinatorial auctions. For example, the bidder can specify different prices on the items if the items get accepted in given proportions, and the bidder can specify ranges for these proportions, thus allowing a huge space of packages to be captured by one compact expression.
Conditional discount offers. The trigger conditions and the effects can be specified in highly flexible ways.
Rich forms of discount schedules. (Simpler forms of discount schedules have already been addressed in the literature (Sandholm and Suri 2001, Sandholm and Suri 2002, Hohner et al. 2003).) Figure 1 shows a simple example. Richer forms allow the bidder to submit multiple discount offers and to control whether and how they can be combined (for example, sequenced in particular ways). Discount triggers can be expressed as dollars or units, and as a percentage or an absolute.
A broad variety of side constraints--such as capacity constraints (Sandholm and Suri 2001).
Multiattribute bidding (Sandholm and Suri 2001). This allows the buyer to leave the item specification partially open, so the suppliers can pick values for the item attributes--such as material, color, and delivery date--in a way that matches their production efficiencies. This is one way in which the suppliers can also express alternate items.
Free-form expression of alternates. This fosters unconstrained creativity by the suppliers.
Expression of cost drivers. In many of our events, the buyer collects tens or hundreds of cost drivers (sometimes per item) from the suppliers. By expressing cost drivers, the bidder can concisely implicitly price huge numbers of items and alternates. Figures 2 and 3 illustrate bidding with attributes and cost drivers.
All of these expressive bidding features of ASAP have been extensively used by CombineNet's customers. ASAP supports bidding through web-based interfaces and through spreadsheets. In some cases, catalog prices from databases have also been used.
CombineNet's expressive bidding is flexible in the sense that different suppliers can bid in different ways, using different offer constructs. In fact, some suppliers may not be sophisticated enough to bid expressively at all,...
NOTE: All illustrations and photos
have been removed from this article.
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