The authors offer some suggestions on how companies can be more successful at innovation: “In particular, they can formalize processes for setting priorities and commercializing products and integrate innovation into their strategic-planning efforts.”

That’s where Foresight can help:

• Foresight can enable improved innovation processes and tactics, by uncovering gaps in processes.
• Foresight can accelerate the time to review good ideas, by 50% or more.
• Strategic planning and innovation are both aided with the type of forecasting guidance and collective thought leadership offered by Foresight, enabling improved business impact.

A key graf on trends and challenges:

The results also show that the approach companies use to generate good ideas and turn them into products and services has changed little since before the crisis, and not because executives thought what they were doing worked perfectly. Further, many of the challenges—finding the right talent, encouraging collaboration and risk taking, organizing the innovation process from beginning to end—are remarkably consistent. Indeed, surveys over the past few years suggest that the core barriers to successful innovation haven’t changed, and companies have made little progress in surmounting them.

Gartner’s much-reviewed Hype Cycle shows prediction markets progressing toward mainstream adoption. We’re expecting that this signal of maturity means that they will continue to make game-changers out of the companies that employ them as innovation management tools.

After all, the authors of the summary are optimistic:

More positively, the results also suggest some ways that companies can become more successful at innovation. In particular, they can formalize processes for setting priorities and commercializing products and integrate innovation into their strategic-planning efforts.

Here’s where our Foresight platform stands to benefit survey respondents most:

Another consistent pattern is that far fewer respondents say their companies are good at the specific processes and tactics frequently tied to successful innovation—such as generating breakthrough ideas, selecting the right ideas, prototyping, and developing business cases. Respondents say their companies are best at adapting once they’re in the market, with 58 percent claiming to be successful. As in the past, executives have the most difficulty stopping ideas at the right time, with only 26 percent of respondents to this survey saying they do this well.

If you were one of the 2,240 executives who responded to McKinsey’s survey and expressed anything less than confidence about your company’s abilities in innovation management, it’s time we heard from you.

Excerpt from Tales from the Technoverse, “Technologies to Watch in 2010″

[Government 2.0] will also lead to greater use of 2.0 technologies to implement various versions of crowd sourcing. Where Intellipedia and Aspace are big news, internal wiki’s will become more second-nature. Pilots associated with prediction markets, using groups to predict things like project results or other public facing data, are starting to be piloted by early adopters.

Rebooting Britain: Make policy using prediction markets

By Nick Bostrom | 01 December 2009

This article was published in the January issue of Wired UK magazine.

How do we know what to think about the future? Politicians make confident predictions. If we elect them, unemployment will allegedly go down, the economy will grow, crime will be reduced, and terrorist attacks will be prevented. If we elect their opponents, the opposite will happen. These opponents, of course, disagree. Whom should we trust?

We could listen to the media pundits, but pundits are usually given a platform because they are articulate and entertaining, not because they have a track record of being right. We could listen to academic experts, but both sides of a political dispute can usually point to some experts who support their view. Or we could try to form our own opinions; but we may not know very much about the issue at hand, and at any rate, it is unclear why we should believe that our opinions would be any more reliable than the opinions of all those millions of people who have considered the issue and embraced the opposite view.

One way of generating predictions is betting markets. If people are allowed to buy and sell bets that some hypothesis is true, then the fluctuating price of those bets can be interpreted as a probability estimate of that hypothesis. The hypothesis could be that some particular horse will win a race, or it could be that weapons of mass destruction will be found if our forces invade some particular country. The principle is the same in both cases but, as pointed out by the economist Robin Hanson, the information that could be revealed is much more valuable in the second case.

In every known head-to-head field comparison between speculative markets and other forward-looking institutions, the speculative markets have been at least as accurate. More often than not, they prevail. Orange-juice futures improve on National Weather Service forecasts, horse race markets beat horse race experts, Oscar markets beat columnists’ tips, gas demand markets beat gas demand experts, stock markets beat the official NASA panel at identifying the company responsible for the Challenger accident, election markets beat national opinion polls, and corporate sales markets beat official corporate forecasts.

Prediction markets can aggregate many small pieces of information held by large numbers of people from diverse backgrounds. Prediction markets seem to work well because they reward accuracy (rather than the ability to tell a convincing story) and punish error (rather than the voicing of politically inconvenient opinions).

No system for making predictions is going to be perfect, but so far the empirical evidence seems to quite strongly favour prediction markets compared to alternative ways of generating forecasts. Therefore, the traditional ways of forecasting uncertain political futures – pundits, academic experts, debates between leading politicians, and personal gut feelings – should be supplemented by the creation of prediction markets wherever possible. When the issue at hand is sufficiently important, such markets should be subsidised by the state as a relatively inexpensive form of intelligence gathering.

Horse-betting is selfish, but betting on policy-relevant outcomes would be public service. Pundits should be expected to put their money where their mouths are, and everybody who can afford to lose £10 or £20 should be encouraged to participate. Journalists should be asked to include information about prediction market estimates in their coverage of controversial topics. Schoolchildren should be taught applied probability theory in the classroom and given the opportunity to practice their skills in real-world settings.

This way, I think, Britain would make shrewder policy decisions. Moreover, its population would learn to think about uncertainty in a sophisticated and mature manner. In our complex modern world, that would be a winner.

Nick Bostrom is director of the Future of Humanity Institute at Oxford University.

James Gardner, Chief Technology Officer at the Department for Work and Pensions in the UK and author of the blog, Banker Vision, explains the key components of corporate innovation.  Gardner’s “tools of innovation” also are aligned with the fundamental building blocks of prediction and idea markets. 

The Tools of Innovation – excerpts from James Gardner’s BankerVision 
Our commentary in italics

A.M Mills, the author of Hell Bent on Success asks me to explain what I mean by the “tools of innovation”. It is possible to summarise, I think, because everything you need to know about doing innovation happens in four stages.

1. Futurecasting
The first is futurecasting. This is the process of working out what is likely to happen in the future so you can guide subsequent iterations of your innovation process. In the book, for example, I explain a specific futurecasting process based loosely on a scenario planning methodology, but anything that gets structured consideration of the future on the table is a good thing. Why is this important? Well, firstly, you can never ask a senior person for support on something new, especially if that new thing impacts current business or revenue, without rehearsal. They need time to think over consequences, and making them think about the future helps them do that. The second reason is that random innovation without a guide won’t always result in new things that solve the strategic problems of the firm. Out of the box thinking is all very well, but if you are not only out of the box, but out of the ballpark, it is usually not helpful.  

For example, GE has run imagination markets successfully for several years, providing a vehicle for leaders to think about the future in the context of other options. GE imagination markets resulted in higher quality ideas than traditional methods.

• 60% of ideas rated as high quality
• Gathered valuable ideas and engaged employees in a fun way

2. Ideation
Ideation is the process of collecting ideas and deciding how good they are relative to all the other ideas that you might have. The thing is, if you’re running a programme, you’ll likely have far more ideas than resources to execute them. So you have to have a way of deciding what you’re going to work on. Of course, if you’re still thinking that the answer to your innovation challenge is getting the good ideas, then you have some work to do. Ideas are everywhere, and usually all you need to do is find a good way of collecting them. Anyway, you’ll have more ideas than you know what to do with, so one of the main tools of innovation is a decent way to prioritise. Usually, people create various scoring systems to do this, but crowd based methods, such as voting and prediction markets work just as well. 

For example, Motorola launched an idea market in 2007, powered by Consensus Point, for  employees to prioritize thousands of ideas on a quarterly basis. Motorola realized the following benefits, in addition to effectively prioritizing ideas: 

• Increased number of new ideas that are pursued from 11% to 22%
• Decreased number of duplicate ideas by 50%

3. Innovate
The third stage is what I call the “innovate” stage, which is really all about the tools and processes you use to work out – in detail – the stuff that has to happen before an idea is actually fundable.  Anyway, to get to the crux of the matter here, you need to answer three questions. “Can we do this?”, which is technically, operationally, and environmentally, is the idea actually possible. “Should we do this?”, which is primarily economic, i.e. can we afford it, and if we can, will anyone want it?. And, finally, “When?”, which is mainly about the response of competitors or internal players. Answering all that means you have a case which is a candidate for funding and delivery. As you’d expect, there are lots of things you do for each of those questions to get to decent answers for as little investment as possible. 

For example, GE employees participating in the company’s “Imagination Market” trade or buy “ideas” based on how closely they believe an idea is aligned to the business objectives, how an idea compares to other alternatives, and if the idea is operationally feasible. Most often, the ideas represent new technology or new product ideas.

4. Execution
Once you have money, the final stage is execution, which is all about building the thing and getting it out in the market. Key tools here include all the things you need to do to win over users, prove you know what you’re doing from an operational perspective (remember, it’s innovation, so its new, so no one will have made it work before), and a ton of other things. But I think the most important thing is you don’t even get to the Execute stage until you’ve done a substantial amount of groundwork first.

Gardner’s “tools of innovation” are a useful guide to effective innovation management, and idea/innovation markets enable several steps in his recommended process.