Do companies need a clothes horse?

My dog, Deker, who definitely needs his tiger

On Friday, Fast Company blogger Kaihan Krippendorff wrote “The Strategy Of Being Needed”. In this article he builds on a quote from Balthasar Gracian, a Spanish-born Jesuit priest from the 17th century:

“The wise man would rather see men needing him than thanking him...He that has satisfied his thirst turns his back on the well, and the orange once sucked falls from the golden platter into the waste-basket.”

Both Gracian and Krippendorff believe that it isn’t good enough that customers really like your product. If that’s the case, then they can still walk away from it and never use it again. These authors posit that they want customers to have a continued need for you or your product, a thirst that cannot be satisfied.

This sounds like moving along the “degree of product change” axis in our innovation matrix. That’s fine. But what I was really interested to hear about was the example he used — Clothes Horse. This is a service for online clothing retailers. Bonobos is their first major customer. The problem being solved is that one person can need clothes of different sizes from different manufacturers. What Clothes Horse provides is an algorithm that converts a customer’s measurements and other information into the appropriate size for a specific clothes manufacturer. At Bonobos, a customer (male, in this case) would enter his information and the algorithm (provided seamlessly by Clothes Horse) tells the customer what size he should order.

While this provides some benefit to Bonobos (it does not have to come up with the algorithm) and some benefit to Bonobos’ customer, the real customer benefit would only come to the customer if multiple stores use the same Clothes Horse algorithm and shared customer information across companies so that the customer would not have to enter information multiple times.

It is also the case that the online clothing business also benefits as more companies adopt the Clothes Horse tool. Assuming their algorithm works (a big assumption since I have not seen any independent confirmation of this), this tool should increase customers’ confidence that the clothes they buy online will end up fitting (and not have to be returned). This decreases the total cost of buying online, thereby increasing the market share for online purchases compared to all retail clothing purchases.

All is not rosy, however. While both customers and the entire online clothing industry benefits, individual retailers — especially large, incumbent retailers who customers are familiar with — don’t benefit from adopting this algorithm. The net effect of wide adoption of it would be to make it easier for customers to switch from well-known, and possibly more expensive, brands to less-well-known or less expensive brands. I would recommend that any large, well-known brand (especially one with a fairly large chain of stores) actively resist the adoption of this algorithm until it is so wide-spread by competitors that there is a chance that it would be at a competitive disadvantage.

What do you think? Of the customer benefit? And of my call for action?