August 2, 2010

Why I think OpenIDEO is important

This is a break from my usual blog post format but today is a special day: we’re launching OpenIDEO – a platform designed to bring people together to solve problems for social good. Here’s a quick intro video (those of you that know me may recognise the voice):

I’ve been thinking about and developing this opportunity for a few years and thought I’d jot down a quick personal perspective on why I think it’s important.

Collaboration works. Cities have always been hotbeds of innovation.  Why?  Because high population densities bring together minds and enable collaboration.  Solitary inventors deliver, but the world is getting too complex for individuals to make breakthroughs at the societal level as frequently.

vs  

Take helicopter design: although Leonardo Da Vinci had a good go at designing a whole ‘helicopter’ in the 1480s no individual on the planet would be able to design and build a groundbreaking one today from scratch.  I don’t imagine there’s even an individual that could design and build all of the electronic systems. Today, most breakthroughs require collaboration.

Collaboration works between similar individuals: 1+1 = 2.5. But we have learnt through our work that collaboration works even better between diverse individuals (whether the differences stem from culture, experience, knowledge, approach or all of the above): 1+1 = 3. Diversity of perspectives drives better results.

And it doesn’t need to be ‘physical’ anymore. In the past collaboration has generally required physical meetings, it’s still arguably the most effective approach.  But technology is providing new means to meet and collaborate virtually, for example social networks (including Twitter, Facebook and LinkedIn) provide us all with new tools for collaboration.  Harnessing technology will be essential for impactful collaborations in the future, particularly since we know that diversity is important.

When companies choose to prevent employees from using social networks (usually to keep them focused) I wonder if they’ve thought through downsides – not least that they may be preventing their employees from developing these new collaboration muscles.

And we care. Although voter numbers are dwindling, consumer and citizen engagement around brands and local politics is increasing – partly because these are the areas where we believe we can have impact. This is likely to increase – particularly after a period where we have all been forced to reassess our values (the economic meltdown) and because technology is offering us all greater power to affect that change.

–

So, with these big trends in mind, we built a technology platform to enable diverse people to collaborate in solving problems for social good.  We hope that it makes a difference.

July 1, 2010

57) Google Image Labeler

危 wēi  danger

Google owes much of its success to its phenomenal search algorithm, invented by Larry Page and Sergey Brin while they were attending Stanford University as Ph.D. candidates.

Broadly, Google search works in three distinct parts:

  • Googlebot, a web crawler finds and fetches web pages.
  • An indexer sorts every word on every page and stores the resulting index of words in a huge database.
  • The query processor compares your search query to the index and uses the algorithm to recommend documents that it considers most relevant.

Google harnesses a distributed network of thousands of computers to parallel process this information.   This approach has proven incredibly effective, with perhaps one major exception: image search.  Image search is less reliable because the indexer mines pages for words and therefore only labels images based on their context (and most images on the web are untagged).  Many companies have tried to build software to interpret images but it’s tough to do  – that’s why identifying unclear letters remains one of the last ways of evidencing that we are in fact human, not machine.

Proof you’re [sort of] smarter than machine:

Although there is clear value in being able to search for images accurately, even Google couldn’t afford to have people complete the labour-intensive task of tagging images one by one.

机 jī opportunity

Google asked a different question  - how can we have consumers do this for free?  Answer: make it a game.  Google licensed ESP gaming technology, originally conceived by Luis von Ahn of Carnegie Mellon University and launched Google Image Labeler in 2006 as a beta.

In the game users are paired with another and they compete in tagging images.  The game is great fun: some users reportedly play over 40 hours a week.  The game has enabled the company to ensure that its keywords are matched to correct images, building an accurate database for Google Image Search.

Gaming has great potential for good, other recent examples include Matchin (helping build a database of the web’s most attractive pictures) and Solarstormwatch (helping astronomers spot explosions on the Sun to give astronauts an early warning if dangerous solar radiation is headed their way)

How About…

  • Developing a game to harness consumer power economically?
  • Applying gaming ideas & principles to your existing offer?

–

Here’s a screenshot from the game:

June 2, 2010

54) Hotel Chocolat

危 wēi  danger

Hotel Chocolat, the upmarket confectioner, was founded by Angus Thirlwell and Peter Harris in 1993.  I’ve always been a fan – not least because the company has consistently turned its challenges to opportunity.  For example, when it struggled to maintain quality cocoa supply it bought an Estate (Rabot Estate in St Lucia) – this in turn became a phenomenal provenance story.  Or, when it couldn’t muscle its way into big retailers it direct sold through catalogue.  It also grew a Chocolate Tasting Club (a subscription service which currently has about 100,000 members) which has created a community of evangelists and made demand more predictable.

It’s a great business, since its launch 20 years ago it has been profitable every year bar one and has continued opening stores during the downturn.  The company has been self-financed to date but its recent successful US store launch has revealed the global potential.  It’s time to expand before competitors enter the local markets but surely the team will have to give up its 200% ownership to fund expansion?

机 jī opportunity

As always Hotel Chocolat has approached the problem creatively.  Instead of raising expensive equity or debt it announced a very different approach – the company plans to raise £5m by selling “chocolate bonds” to its most loyal customers, taking advantage of rock bottom interest rates.  The investment opportunity will be marketed to the members of Hotel Chocolat’s Tasting Club – ‘Investors’ can subscribe for a three-year, £2,000 bond, which will deliver a “tasting box” of chocolate worth about £18 every two months — equivalent to a 6.7% yield.   The money raised will help to expand the high street chain from 42 to 72 shops, enlarge the Huntingdon factory, develop a new cocoa plantation in St Lucia and expand the business overseas.  Angus Thirlwell, co-founder, said: “We would rather pay interest to our customers than a bank. Many who have money sitting in the bank getting a low interest rate may prefer to be paid in chocolate.” The company is on track to deliver a 20% rise in turnover to more than £50m this year.

How About…

  • Fundraising from less obvious sources, e.g. your most loyal customers?
  • Using the fundraising process to bring in a community of evangelists?

–

May 11, 2010

51) Clover Food Lab

危 wēi  danger

Starting any business is scary.  Starting any restaurant business is very scary.  It’s expensive to set up, there’s legislative hoops to jump through, location and menu are critical (and it’s tough to do market research before making the leap) and quality standards have to be maintained.  Finally, consumers are fickle so even if it’s initially successful you can’t rest on your laurels.  Surely you can only start by jumping in head first at the deep end?

机 jī opportunity

To the contrary, my colleagues Ryan and Colin (thanks guys) told me about Boston-based Clover Food Labs, a startup that has cunningly overcome these challenges.  Instead of committing to a site and launching a concept blind Ayr Muir has taken a more creative approach.  He decided to keep location flexible and costs low by opening a food van.  Muir tries different locations and menus with the goal of homing in on the right restaurant format.  Everything that Clover Food Labs does is in Beta (hence Labs) – it has taken some clever design to be so flexible.  For example, the truck itself is a giant whiteboard enabling Muir to edit menus instantly (see the image below).  In addition, Clover is completely open with the public – publicizing the bad stuff (see Muir’s Great Sandwich Disaster post here) in addition to the good stuff.  The open experiment approach seems to be working, I read that the van sells out often and mistakes seem to be less frequent – maybe Muir’s homing in on his restaurant format – it will be interesting to see if he can give up on the flexibility his van yields…

How About…

  • Starting small to learn? And staying in Beta forever?
  • Questioning every sacred cow?
  • Being totally transparent (even the bad stuff) to shorten the feedback loop and create a real dialogue with your consumers?

—

here’s a photo Colin took of the stall itself – with menu in progress…

April 9, 2010

46) Netflix (again!)

危 wēi  danger

As per my previous post on the subject Netflix has done an incredible job of disrupting the video rental incumbents, particularly Blockbuster.  Part of its success was moving away from the traditional physical retail channel by harnessing internet distribution – providing opportunities to improve the customer value proposition that would never have been feasible in physical stores (including personal recommendation engines and instancy).  However, the former is notoriously difficult to develop and improve – the required algorithms are incredibly complex and require significant development.  They are, however, very valuable to the company (allowing it to predict how much someone is going to enjoy a movie based on movies that they have enjoyed in the past).  Should Netflix risk hiring an expensive team of experts to improve their algorithms, if so how would they possibly select the talent capable of making the most significant progress?

机 jī opportunity

Netflix found a creative way to avoid hiring anyone at all.  Instead, on October 2, 2006 it announced a $1m prize for the first team to better its own prediction software by 10% and a series of ‘progress prizes’ of $50k for the teams that made the most progress each year.  The strategy was immediately effective – within a year over 20,000 teams from over 150 countries had registered for the competition and 2,000 teams had submitted over 13,000 prediction sets.  Over the same period a handful of front-runners with very different backgrounds traded first place.  The competition reached its climax at the end of 2009 when a series of front-running teams decided to join forces to try to achieve the full 10% improvement. On September 18, 2009, Netflix announced team “BellKor’s Pragmatic Chaos” a merger of teams “Bellkor in BigChaos” and “Pragmatic Theory” had won the grand prize of $1m by only 20 minutes (the formula in the title is a very small excerpt).  The winning entry factored in an amazing variety of variables, including the effect that human memory plays in rating and the effect of moods on ratings for different days of the week.

How About…

  • In situations where the challenges or costs associated with solving your toughest problems are highest opening it up to the wisdom of the crowd?
  • It wasn’t until leaders joined forces with also-rans that real progress was made in this contest – how might you drive progress by merging competing teams?
  • The best solutions came from unorganized people who organized organically – how might you allow teams to self-mobilize in your organization?
  • The most extreme approaches that had seemed least effective when initial progress was being made actually made all the difference in the end – how might you harness extreme perspectives to build competitive advantage?

—

« Older Entries