Archive for July, 2010
I’m participating in a brainstorming and design session during the first weekend in August for a medical foundation in California. As part of the preparation, the participants were given a disruption exercise.
I think of disruption in the sense described by Clayton Christensen in his books, “The Innovator’s Dilemma” and “The Innovator’s Solution”. In brief, the books document research into how large, established businesses are overtaken by a competitor. For instance, he documents how Big Steel was disrupted. The cycle went something like this: 1) Big foundries produced all kinds of steel products, from low-quality commodity items like rebar to high quality auto parts. 2) Electric arc furnaces were created that could melt scrap metal into low quality rebar. 3) Big foundries and their investors were happy to get out of this low-end market and focus on their most profitable products. 4) Arc foundries found themselves in a rebar commodity market, so they invented ways to make higher quality steel. 5) Big foundries were happy to drop the I-Beam commodity market. 6) And so on…
Big Steel was disrupted by their low-end electric arc furnace competitors, because they didn’t expect that relinquishing the customers that they really didn’t want would eventually lead to relinquishing customers that they really did want and need.
The books document the same pattern in other industries such as hard disk drives, business computers, car manufacturers and many others.
Our activity was to think of why Google, Amazon and Netflix were disruptors.
1. Characterize why these were disruptive innovations. Why were they successful?
– Google: At first Google didn’t have as much content as the leader (Yahoo). Yahoo’s links were user-categorized, so they were typically well-categorized. Google’s proprietary algorithm used a likely factor in relevancy and usefulness of a link, but it wasn’t very accurate unless it had a lot of pages indexed. Yahoo’s manual categorization of links becomes unwieldy when the number of links is huge, so their links and categories became less relevant as Google’s algorithm gained in accuracy thanks to the number of indexed pages.
– Amazon: Shopping in the real world is typically about making a choice as to which store or shopping center you will go to. Your product selection is fairly meager. Even with Amazon’s initial books offering, they could offer tens of thousands more books than even the largest retail center. Online shopping was also difficult in general, since you had to visit individual company websites to find information about products. Amazon separated the sale and distribution of products from the product manufacturers and made THAT their business. They became the “mall” in online shopping – a mall with a single checkout point where you never have to wait.
– Netflix: Renting and returning movies to a local retail location has never been a great experience. Although browsing for movies is sometimes rewarding, it’s not significantly better than browsing for movies online. The problem with the local center is the similar to that of Amazon – lack of selection. Netflix has such a large movie selection that it immediately surpassed retail outlets. The added convenience of quick delivery as well as a queue for the next movie made it quickly the best solution for renting movies.
2. What has been required to keep them successful?
– Google: The pay-per-click ad model introduced by Google was directly related to their algorithm’s ability to find relevant links, and thus the advertisements in Google were almost always relevant to the search, while Yahoo’s was a banner advertisement system that wasn’t tied to a good algorithm. They’ve also expanded their ad revenue into spaces only tangentially related to search, such as email and other Apps, and other content providers such as blogs.
– Amazon: They seem to have recognized that although an online product selection is far better than retail, it still doesn’t ultimately scale to the maximum possible variety, as there are still niche and new items that cannot be stocked. The Amazon Stores concept effectively allows any seller to have a “place in the mall”.
– Netflix: The real trick for Netflix is in the numbers. It isn’t financially viable if every Netflix customer continually rented and watched the maximum number of movies – it would cost more money to ship and receive movies than they charge to customers. However, the actual behavior of customers in renting only a few movies per month makes the business viable.
3. What are the biggest threats to their future success? What/who might disrupt them?
– Google: Social networks are getting better at providing link and revenue opportunities and may surpass Search as the primary way of discovering online content. Facebook in particular has more information about the searcher than Google and can potentially serve up content that is more relative. Google’s PageRank algorithm patent expires in 2017.
– Amazon: I believe that Amazon will be harder to disrupt as they have a network effect advantage, Yahoo Stores attempted to compete with them but hasn’t been able to match their product selection. eBay is probably the closest competitor, with their eBay stores, and will likely continue to dominate the collector/used market. One place they likely need to keep abreast is with smart phone shopping paradigms that are emerging, such as a retail browsing with competitive online pricing and comparisons, and with incentive purchases. If an online retailer can figure out how to give purchasing that “personal” touch like you get in an Apple store, they might give people a great reason to switch from Amazon.
– Netflix: Streaming content delivery will almost certainly eliminate the Netflix DVD rental business, but Netflix seems to be fairly well positioned to take advantage of it. Their most likely disruptor is YouTube and other free content providers. YouTube is already disrupting some types of media such as comedy television and music videos.
I was recently added to a team that is trying to come up with some tools that will help facilitate innovation training. It got me to thinking about what software I’ve created that was “delightful” in the spirit of Intuit’s d4D practices – Design for Delight.
I quickly came up with at least three things that I had developed end-to-end, from customer problem to delightful solution: Keyword Search, Intuit unstructured time hosting and Intuitlabs.com (actually its predecessor, innovation.intuit.com). Keyword Search brought full text search to QuickBooks back in 2005 as an add-on. It’s being released inside of QuickBooks proper for 2011. Hosting is an offering internal to Intuit, giving teams the ability to rapidly launch applications while still complying with Intuit privacy, security, etc. stuff. Intuit Labs, originally “innovation.intuit.com”, showcases Intuit innovation.
So what made these offerings delightful? I was able to come up with two common factors that are repeated by customers. The first is speed. All three radically changed how quickly the task could be accomplished. Keyword Search became invaluable to small business owners, causing some to eliminate multiple methods of filing. One of the early Alpha testers, after running a search, exclaimed simply, “Wow!”
With hosting, the time to get a working instance that complied with Intuit security and privacy went from months to just hours. A team could spin up a LAMP or Tomcat stack and have it in front of customers, without going through the traditional data center processes that existed to protect our larger applications and sensitive customer data. A new, isolated zone let them experiment without risking customer information.
Intuit Labs is part of that experiment zone, enabling the security, legal and privacy issues to be addressed within a single, rapid, standardized process.
The next factor is enabling the impossible. Before Keyword Search, there was no way to search for text within certain fields of QuickBooks, such as a memo field or line item descriptions. Many small businesses use these locations for critical information such as item serial numbers, but finding them meant having to know something else about the transaction, then visually scanning through potentially years worth of data.
With hosting, teams were limited to public applications that used only the default hosting environments, This prevented rapid experimentation using new platforms such as Facebook or Google Apps. Intuit Labs gave experimenters a place to connect with customers and application users. The only place for this in the past was on the larger Intuit offering websites – not the best place for, say, a Facebook experiment!
So what I have now is at least some kind of framework for creating delightful offerings:
Is the offering so much faster than any other choice, that you can’t imagine going back to the old way?
Is the offering enabling something that was previously impossible?
Those are two questions I’m going to be answering in any future offering.