Not many seem to have tried the idea. So… possibly not.
But agreed financial penalties for poor performance (such as money back guarantees) have long been part of the stock-in-trade of modern commerce – although perhaps not common in the language services business. Financial penalties in contracts for large, high-value translation projects are not unknown – although possibly not common.
But what would the effect be if the translator offered a discount (say, for late delivery) on one-off projects worth, say, $500 or $1,500? Would such an offer increase the probability that the buyer would choose the quote over a competitor’s – or accept it at a higher price?
In the right context, it could well be the deciding factor. In this post we look at how language service providers can leverage off financial penalties within the context of OpenBorder’s proposed multi-factor auction, so both the buyer and the translator get a tangible pay-off.
1. Weighing price against “reliability”
Imagine the following scenario: Translator A quotes $1,000 for a translation job to be delivered at 9:00 am next Thursday. Translator B offers the same price with the same delivery time, but offers a 15% discount if he misses the deadline. How would the customer interpret this? The chances are that the customer will figure that B must be pretty confident in his or her ability to deliver on time if they’re willing to offer a financial penalty like this.
Usually, translators present their quotes to the customer “blind” – i.e. they have no idea what their competitors might be offering, or whether the customer is even able to compare “apples with apples” to make a rational choice. But let’s imagine that our competitors A and B are presenting their quotes on a live website where each can see what the other is offering (anonymously, of course). Translator A can clearly see the competitive advantage that B has.
What should A do?
She could drop her price, of course. But let’s imagine that she feels she is already offering a good price and doesn’t really want to do the work for less. An alternative to dropping the price is to bid on some other (non price) factor which has some value to the customer. Decision made! Translator A counters by also proposing a discount for lateness and ups the ante by offering 20%.
Of course, this sort of bargaining will only make sense to the buyer if on-time delivery is really important. So, let’s imagine that it is – the buyer has an important customer from Japan arriving in his office at 9:30 on Thursday and wants to present a PowerPoint in Japanese. If the translation doesn’t arrive on time, it will have little value.
Now imagine that B is a translation company – they want the job, but they’re worried. How can they counter A’s offer? A discount of more than 20% might wipe out any margin – the job would make a loss. So, what’s the probability of a loss? What’s the probability that B could actually deliver on time? How reliable are their production processes? What if the external translator is late or delayed? What if the project manager sits on the translation all morning before sending it off to the reviser or fails to get it back from the reviser in time? Company B is now confronting the realities of what their production system can realistically and reliably deliver. Proposing a discount for a failure to deliver is a pretty quick and intuitive way of measuring the reliability of their system.
Let’s imagine that Company B feels it can’t offer a discount greater than 15%. They feel the risk of a loss is too great. They’ve reached the limit of their confidence in their ability to deliver on time. They decide that the only way to maintain a competitive position with respect to A is to drop the price by a small margin – so they offer $950 with a 15% discount for late delivery. They might break even if things go wrong.
How should Company A respond now?
Let’s imagine that A has great confidence in their ability to deliver this sort of job within the tight deadline: the project managers have been well-trained and have a disciplined approach. Every trick of the trade is at their disposal – there is a back-up translator on call and the reviser is ready to edit the job overnight.
Now if I were Company A, (and I had a reasonably full order book), I might now increase my late penalty to 25% and bump up the price to $1,200. It’s an auction after all!
Maybe you wouldn’t do that, but I might…
Who will win this job? In a regular auction the “winner” is the bidder with the lowest price. Not here! In a multi-factor auction the winner is the one whose bid best meets the customer’s needs across a number of factors – not just price. If the customer really needs the job by 9:00 am next Thursday, the bidder offering a significant financial penalty for late delivery is going to look pretty reliable. If it’s reliability the buyer is really after, then the extra $200 might be a small price to pay.
Moral: Buyers are likely to (correctly) interpret a supplier’s willingness to offer a discount for poor performance as a strong measure of his real ability to deliver, especially in an auction setting. In the scenario above, both parties benefit from the process – the buyer gets what he needs (certainty and reliability) and the supplier gets what he wants (a better margin). The supplier wins on merit and makes a profit from having built a production system he can bet on.
Win – Win! (For a nice twist – look out for a future post on how Company B also wins on this deal!)
2 Finding the right balance…
One of OpenBorder’s principles is to ensure that potential downsides are balanced by some other kind of upside. In addition to price, the multi-factor auction allows providers to bid on “non-price” factors – such as earlier delivery times or a penalty for late delivery. But over enthusiastic bidding which promises ever shorter delivery timeframes presents an obvious danger. But there is a natural balancing mechanism here – any attempt to over-promise on deadlines is counterbalanced by the bidder’s self-imposed financial penalty for a failure to deliver. Compare a 1% late penalty with a promise to deliver tomorrow against a 50% discount with a promise to deliver next week. Delivery next week sounds like a sure bet! (If I were a buyer, and the LSP promised to deliver tomorrow with a 90% discount if he didn’t meet the deadline, then sure, I’d figure that the risk was worth taking.)
The provider gets to weigh up the true risks – and so does the buyer. It makes the negotiation honest and reliable.
3 Dispute resolution
The nice thing about the inclusion of a financial penalty for late delivery as an auctionable factor is that it naturally forms part of an agreed dispute resolution process – clear to both parties before any work ever begins. If the supplier is late, there is no dispute – the penalty is automatically applied.
On the surface, the multi-factor auction is simple – bidders adjust a few uncomplicated and well understood parameters such as price, delivery time and a discount if they are late.
Effectively, the terms of the job are “negotiated” until the best possible result is achieved for both the buyer and the winning bidder. The provider wins on merit (not just on price) and the buyer gets the best possible deal.
Post script: Is bidding on a job like this worth the effort? OpenBorder thinks so – winning could well be the start of a mutually rewarding relationship between the buyer and the translator for years to come.
The principles behind OpenBorder’s multi-factor auction come from the work of John Forbes Nash at Princeton in the 1950’s. In 1994, he won the Nobel prize for economics for his radical ideas. In popular culture Nash is known as the father of the “win-win” theory from his portrayal in the 2001 movie A Beautiful Mind. He provided a mathematical solution to the problem of how deals can be negotiated where both parties get a beneficial outcome. How OpenBorder incorporated these simple ideas into its business model is here.
In future posts we’ll look at how some of the other factors in OpenBorder’s multi-factor auction can help translators discover their strengths, and how to leverage them to find new, more profitable customers.
Criticism, discussion and debate welcomed!