BidAnalyzer: Improving Reverse Auction results?

I first came across BidAnalyzer in a post over on e-sourcing forum.

Two academics, Sandy Jap and Prasad Naik have created a model that, they claim, will tell buyers whether suppliers in a reverse auction have actually bid down to their lowest price or not. It’s an intriguing claim; it even made the pages of And if you are really mathematically-inclined you can read the actual paper that describes the model.
Obviously this sounds fascinating to me so I had a call earlier this week with BidAnalyzer’s authors, Sandy Jap and Prasad Naik to find out more….

Suppliers in reverse auctions have a rough idea of who they are competing against. So a higher-quality supplier will know that they don’t need to have the lowest price to have the most attractive overall offer. So they will keep their bids higher than the lowest price.

Let’s run an imaginary reverse auction with the following four suppliers:

Known supplier inc. We’ve worked with these guys before (though they aren’t the incumbent) and know they are pretty good. They had some quality issues a few years back, which is why we moved away from them, but we have it on good authority that those quality issues are all in the past.

Great reputations inc. Never worked with these guys but everything we have been able to find out about them tells us that their products are of good quality, with prices to match.

Crap but cheap inc. Oh my goodness. We once gave these jokers a contract in a past life and boy did we regret it. Still, they can be relied on to bid aggressively in the reverse auction.

Here Today Gone Tomorrow inc. Never heard of these guys and nor has anybody else.

The bidding starts. It so happens that the market is pretty small so the suppliers have a good idea of who else is bidding. For the sake of this example I’ll assume we are using a very simple reverse auction (*).

Great Reputations sees the price drop further than they are prepared to go. So they hang back, confident that their good reputation means they don’t need to compete aggressively. Same goes for Known Supplier. This leaves Crap But Cheap and Here Today Gone Tomorrow fighting for first place and driving down the price, while Known Supplier and Great Reputations set themselves strategically somewhere above the lowest price, depending on their assessment of their own value-add. So suppose when the reverse auction ends the prices are something like:

Crap But Cheap: $705,000
Here Today Gone Tomorrow: $710,000
Known Supplier: $790,000
Great Reputations: $800,000

As the buyer can you be sure that Known Supplier and Great Reputations have given you their best prices? Or do they just believe that their offerings are worth $100,000 or so more than the cheapest competitors?

BidAnalyzer claims to be able to tell you the answers, based on analysing each supplier’s bidding pattern. Ideally you’d also feed in some cost models of the different suppliers, but Jap and Naik claim the model works even with just the bid information.

One thing worth mentioning at this stage: In our call Naik and Jap said that the problem with traditional reverse auctions which I’ve described above, and which BidAnalyzer seeks to address, only applies in price-only reverse auctions. Multi-attribute  and weighted reverse auction formats don’t suffer from this issue, because all suppliers are already bidding on a level playing field.

I haven’t seen BidAnalyzer in action (yet) so I can’t vouch for how much it tells you beyond what you would have been able to work out for yourself with a little market research. Though if and when I do, I’ll post some views.

(*) We will show suppliers the current best bid but we have no way of messaging them during the reverse auction.


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