I often talk about Ada Lovelace in my public talks and in class. In the mid-1800s, she was the world’s first computer programmer – writing code to run on Charles Babbage’s Analytical Engine. Like Babbage, she was well ahead of her time, and an important figure in the history of computing. Which is why Ada Lovelace Day, coming up with Wednesday (24 March), is so cool.

Ada Lovelace Day is the international day of blogging to celebrate the achievements of women in technology and science – I’ll be writing a post doing exactly that in a few days. But today I want to encourage everyone that has a blog to sign up to write a post yourself.

There are plenty of innovation angles to the Ada Lovelace story – I’ve explored some of them here briefly. As with Babbage, a big part of the story is the illustration of the difference between inventing something and turning it into an innovation. The Difference Engine and the Analytical Engine were both brilliant inventions, but were never successfully turned into innovations.

Another angle to the Ada Lovelace story is its demonstration of how new ideas are combinatorial. By the time ENIAC went online in the late 1940s, it seemed very new. And yet, it was building on ideas that went back at least to Leibniz in the 17th century, including those that Lovelace developed.

Consequently, I think that the idea of a day named after Ada Lovelace, honoring the achievements of women in science and technology is fantastic. And like I said, I strongly encourage you to create something for the day – a blog post, a video, whatever. The number of awesome women in technology right now is very high, so there are plenty of people you could write about. Some suggestions:

• danah boyd: She is the sharpest academic thinker right now on the meaning of social networks. In a time when anyone can declare themselves an expert, she has genuine expertise. Basically, if I’m trying to figure out what’s going on in social networks, and she’s written on the topic, her writing is what I trust.
• Valeria Maltoni: Another actual expert – she has experience in making online communities work, and has great insights into what this means for firms. Her blog is outstanding.
• Nancy Duarte: There are at least four people in my department that have gotten copies of her book Slide:ology after I’ve raved about it to them. All of us agree that Duarte’s work has helped us become better presenters.
• Suw Charman-Anderson: the inventor of Ada Lovelace Day, and a very insightful writer on social media and journalism. The amount of great content on her site is mind-boggling.
• June Holley and Patti Anklam: Two of my favourite writers on organisational network analysis, and using networks to improve performance. Anklam’s book Net:Work is great, and Holley’s upcoming book on Network Weaving also looks to be excellent.
• Venessa Miemis: Just started her blog at the end of last year, and is already having a big impact with her in synthesis and meta-analysis. She’s built a remarkable community at her site in a very short period of time.
• Caterina Fake: the co-developer of flickr, and now hunch – a site that does amazon-type recommendations for everything. Entrepreneurial, and, most importantly, gets her ideas executed.
• Tara Hunt: she has written The Whuffie Factor, and initiated several start-ups. She’s a social media rockstar, because she has a great ability to distil general lessons out of her specific experiences.
• Jane McGonigal: she develops great video games. Her latest, Evoke, is based on the premise that in the face of increasing complexity, the only way to succeed is through collaboration. A network-based game with a network lesson – what could be better?
• Those are just some of the women from my RSS feed that you could talk about. If you need more ideas, check out The Next Women: Business Magazine for Female Internet Heroes. They talk about hundreds of women who are potential Ada Lovelace Day honorees.

So there’s ten women you could write about for Ada Lovelace Day, plus a few hundred more from The Next Women. And as much as I admire the people on this list, I won’t be talking about any of them in my post for Ada Lovelace Day. I’ll be talking about five women that have had a particularly strong influence on my thinking and on my academic career.

You’ll have to come back in a few days to find out who they are. In the meantime, start thinking about making your own contribution to Ada Lovelace Day!

We have been following a bit of a theme lately on valuation methods and selecting innovation projects. This was started with my post on some research that we have been doing on valuing innovation projects. Using surveys and quantitative analysis the study showed that traditional valuation methods such as net present value inhibited innovation. However, treating an innovation project as a real option was positively correlated with successful innovation.

Following this post, a few readers pointed us to Clay Christensen’s essay on the NPV trap, which is very supportive of the survey results. Tim subsequently wrote a blog piece on this too.

If traditional valuation methods are so flawed when selecting innovation projects, then it’s probably worth saying a bit more about real options. One reader of the blog, who runs a VC investment company specializing in high-tech ventures, said she had been using real options to make investment decisions for several years and found the outcomes to be much better than traditional methods for valuing projects (thanks Deb!).

What got me thinking about real options in the first place was a finance colleague who gave me an excellent article from the McKinsey Quarterly. It’s quite old now but I still think it’s the best introduction to real options and innovation strategy so I will use some of the ideas in this post.

The first thing to think about is how to value a financial option. I won’t go into detail on this one but some very smart people won the Nobel Prize for this and then nearly brought down the global economy when they used their equations to manage a hedge fund called Long Term Capital Management (now that really is academic impact!).

In the equation for valuing a stock option, increasing uncertainty and time to expiry increase the value of the option. The cost of exercising the option decreases its potential value, as does the revenues that we might lose by holding the option, rather than the underlying stock.

The value of a real option works in exactly the same way, as explained by this diagram from the McKinsey Quarterly overview.

The most important issue for managing innovation projects is that uncertainty and time increase the value of the project. In traditional valuation methods, these variables decrease the value of the project. Innovation always involves uncertainty and longer time frames and is therefore highly compatible with real options.

But taking a real options approach to innovation can tell us more than just valuation. It also tells us how to maximise the value of the project by constructing it as a real option where we can maximise its value by looking at the variables that make the option more attractive. For example, can we take an initial stake in the project as an option that will allow us to hold the option for a long time? Can we decrease the costs of exercising the option by finding potential partners to help us take the innovation to a bigger market?

This gets a bit abstract so I will use a recent example of an Australian oil and gas producer that is buying a ‘real option’ in producing biofuel from algae.

In this case uncertainty is high. The technology is unproven and nobody really knows what the oil or carbon price will be in five years time. Given that Beach Energy owns the tenements in the Cooper Basin where the algae farms are proposed, the potential time to expiry is very long and the exercise price is also relatively low. It’s a very good case for constructing the business case as a real option.

Beach does this by staging the investment with an alliance partner. If the initial scoping study or the pilot plant fails then all they have lost is the minimal investment in the early stage of the project. They can exercise the option by scaling up production if the industry conditions make the project economically feasible.

Again, the most important point is that there is value in embracing uncertainty and learning by trying things out.

Source: Leslie and Michaels (1997) The Real Value of Real Options. McKinsey Quarterly (3), pp. 97-108.

Last week I talked about how I use Malcolm Gladwell’s TED talk in my innovation courses. Another one that I use to illustrate how the innovation process is changing is the talk by Charles Leadbeater:

The innovation lessons are a little easier to pull out of this one, since it is directly about innovation. Leadbeater talks primarily about the role that collaboration plays now in innovation. Many of the key ideas are explained in his book We-Think, which is definitely worth reading. Here are some of the key ideas that jump out at me in his talk:

• His story of the invention of the mountain bike is an excellent example of customer-led innovation. Over 60% of the bicycles sold in the US now are mountain bikes, but they were not developed by bike companies. They were developed by lead users, who combined the rugged frame of the slow, clunky one-speed bikes, the gears from racing bikes, and brakes from small motorcycles to create bikes they could take off-road. This happens in many industries now – others that we talked about in class include software, adventure sports and medicine. The last one always makes students a bit nervous – who wants to have their doctor experimenting? And yet, many times they have to invent new ways of doing things on the fly when they are faced with an urgent situation. So many medical devices actually originate in use.
• Leadbeater’s discussion of the patent system builds on that last point. He says that the purpose of many innovations is discovered in use, which does not fit well with an IP system that requires inventors to know exactly how their invention will be used in order to file a patent. Inventors often don’t know what their ideas are for! I think that this is a critical point – this is one of the reasons why “release, get feedback, improve, iterate” is a very effective innovation method. It allows you to discover what your great idea is actually good for as you interact with the people using it.
• There is a good discussion of why the organisational imperatives within large firms lead to incremental innovation rather than breakthroughs. It is much easier to get sign off on an idea that builds incrementally on an existing product or service, aimed at current customers, with a reasonably predictable return. Innovation is inherently uncertain, which often makes it difficult to get innovative ideas off the ground within large organisations.
• “The truth is that most creativity is cumulative, and collaborative.” Innovations combine things that already exist. There is no thunderbolt from the sky, but rather a great deal of hard work, discussion, and collaboration that must take place if we are to be consistently innovative.
• The last half of the talk is a great explanation of the conflicts between open and closed innovation models. Leadbeater discusses why established firms try hard to maintain their primarily closed innovation models. He also correctly points out that the most successful business models of the future will probably not be either fully open or fully closed, but rather some type of hybrid combination of the two.

Overall, it is a terrfic talk and well worth your time. Both in this and in We-Think Leadbeater makes a compelling case for the benefits of collaborative innovation, why organisations might use open innovation models, and some of the tensions involved in doing so.

I was doing some work with a company this week, and ran across one of my pet peeves. The organisation itself was very exciting. We interviewed over 20 people about various projects that were going. To a person they were smart and engaging, with great ideas, vision and energy. It was invigorating. The number of exciting projects that they have on the go is enormous. So what’s the problem? The problem is that many of these projects will never get off the ground. Why? Because they might cannibalise existing business.

This is the worst possible excuse for killing innovation. In many ways, if you worry about cannibalisation, you are falling into exactly the same trap that makes Net Present Value project evaluation so flawed. Earlier this week, Ralph Ohr and Wim Rampen both pointed me to an article that illustrates this flaw perfectly. The article is called Innovation Killers, by Clayton Christensen, Stephen Kaufman and Willy Shih from the January 2008 edition of Harvard Business Review. They include this diagram:

This shows the problem perfectly. NPV analysis assumes that our current level of performance will remain stable and that is the probable future that is used to evaluate new innovative projects. However, the ‘do nothing’ option does not result in staying at the same level of profit and performance. If we do nothing, our performance will decline. We will be worse off because someone out there is figuring out how to destroy our market. If we try new things, and they work, we might stay ahead of them. If we don’t, they’ll knock us over. There’s no way around it.

This same flawed assumption is being made when people worry about introducing new ideas that will cannibalise their current product or service lines. Of course they will. But again, the do nothing option does not result in ‘everything stays the same’. The do nothing option results in someone else doing the cannibalising.

Halfway through the day, our host said this:

When we compare ourselves to our current competitors, we look pretty good. We’re innovative and ahead of the game. But that’s the wrong comparison. I’m not worried about the people already in our market. I’m worried about the people I’ve never heard of.

Exactly.

The simple fact of the matter is this: we must introduce innovations that take away our current market share. There’s no such thing as a cash cow – if you have a product that is dominating the market, but you’re not innovating around it, it’s not a cash cow, it’s already dead.

Cannibalise your current products. Kill your best performers, or someone else will kill them for you.