Posted by George Huhn on Fri, Jun 04, 2010 @ 11:36 AM
Wondering why your teams aren't more creative and innovative? Maybe they are stopping themselves.
When it comes to innovation "what really matters is not getting many good ideas, but getting one or two exceptional ideas. That's really what innovation is all about," says Terwiesch.
But if you're getting lots of ideas, shouldn't that naturally lead to more "exceptional ideas?"
Not necessarily.
"The evaluation part is critical.," Terwiesch says. "It's no good generating a great idea if you don't recognize the idea as great. It's like me sitting here and saying I had the idea for Amazon. If I had the idea but didn't do anything about it, then it really doesn't matter that I had the idea."
And project teams are not very good at recognizing and developing great ideas. For example, here are 4 reasons that team dynamics can get in the way of innovation:
- Team members self-censor themselves to avoid upsetting a colleague or to go along with the status quo
- Too many people in the room doesn't provide enough time for everybody to be heard and have their ideas discussed
- "Build-up" or the tendency of people to expand on ideas that have already been accepted by the team at the expense of considering other ideas
- The tendency to defer to authority or up the hierarchical team structure, i.e. "the boss is always right"
Also, Terwiesch says, "We find huge differences in people's levels of creativity, and we just have to face it. We're not all good singers and we're not all good runners, so why should we expect that we all are good idea generators?"
What are some things that teams can do to work around the innovation-killing team dynamics?
In their book "
Innovation Tournaments: Creating and Selecting Exceptional Opportunities," Terwiesch and Ulrich suggest that putting more structure around the early idea generation process can help ensure that quality ideas bubble to the surface. They recommend using a virtual "suggestion box" to collect ideas and "coordinated competitions" to filter exceptional ideas.
Terwiesch adds, "People like having a process because they understand that it's fair. In a typical brainstorming meeting, it's not fair and everybody knows it: The boss is always right."
He also says that it is important to prevent the group dynamics in brainstorming sessions from killing early ideas. "Your initial thoughts are very vital to the company because they are your unbiased opinion."
According to Ulrich, "We have found that, in the early phases of idea generation, providing very specific process guideposts for individuals [such as] 'Generate at least 10 ideas and submit them by Wednesday,' ensures that all members of a team contribute and that they devote sufficient creative energy to the problem."
The next time you're looking for innovative ideas, consider trying the virtual suggestion box, and then focus on evaluating the ideas that were generated. If you have a large team, consider breaking the team into smaller groups while being conscious of the social and organizational hierarchy and personalities within each small group.
Finally, consider using a "Positive, Negative, Interesting" (PNI) parallel thinking structure around the discussions. Using this approach, the team evaluates each idea in only one area at a time. So when the "Positive" idea characteristics are evaluated, only positive attributes of the idea are discussed and recorded, and when "Negative" characteristics are evaluated, only the downsides of the idea are discussed and recorded. The "Interesting" characteristics are the neutral or "just the facts" attributes of the idea.
Once teams get used to this approach and experience the value in it, they become more self-directed and peer pressure alone keeps the discussions on-track.
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Posted by George Huhn on Mon, Apr 26, 2010 @ 09:55 AM
Looking for new and better ideas from your project team? Thinking about having a typical "
brainstorming" session? Don't bother. New research shows there's a better way.
"Brainstorming" usually consists of people meeting specifically for the purpose of coming up with new ideas around a specific topic. Any and all ideas are recorded, and evaluation of individual ideas is postponed so as not to inhibit idea generation or discard ideas prematurely. Brainstorming is proposed to work on the basis that ideas from each person in the group will stimulate new and different ideas from others, therefore, more ideas will lead to better ideas. That's the theory, anyway.
However, in a recent article published in the
INFORMS journal
Management Science entitled
"Idea Generation and the Quality of the Best Idea," researchers found that most of the literature on brainstorming focused on the number of ideas generated, but not the quality or the selection of the best ideas. Furthermore, they found that the literature showed the opposite of what brainstorming promised: "research has unequivocally found that the number of ideas generated (i.e., productivity) is significantly higher when individuals work by themselves, and the average quality of ideas is no different between individual and team processes."
In other words, brainstorming produces fewer ideas than individual efforts, but about the same quality of ideas.
1) the average quality of ideas generated,
2) the number of ideas generated,
3) the variance in the quality of ideas generated, and
4) the ability of the group to discern the quality of the
ideas.
In their study, they compared two processes: a typical brainstorming structure and a "hybrid" structure. In the brainstorming structure, each team of 4 was given 30 minutes to complete an idea generation challenge. At the end of the 30 minutes, each team was given 5 minutes to develop a consensus-based selection and ranking of the team's five best ideas. In the hybrid structure, individuals were asked to work separately on an idea generation challenge for 10 minutes and then asked to rank their own ideas at the end of the 10 minutes. These individuals were then randomly placed in teams of 4 to share and discuss their ideas and generate new ideas for 20 minutes. At the end of this phase, each team was given 5 minutes to develop a consensus-based selection and ranking of the team's five best ideas.
The ideas were then evaluated by a panel of 41 MBA students who had received formal training in the valuation of new products.
Their conclusion? They found the "hybrid structure" produced 3 times as many ideas per unit of time compared to brainstorming, and the average quality of the ideas was significantly higher.
So, the next time you're trying to generate some breakthrough ideas on your project team, be sure to let your project team members generate some new ideas on their own before you try to do it together as a team. This research shows you'll get much better results doing it that way.
And if you're involved in
project portfolio management, be sure to share this information with your project managers. Sometimes it only takes one breakthrough idea to make the difference between a project that is delivered on-time and on-budget and one that fails to meet its goals.
Follow-up: Two of the researchers who wrote this brainstorming article were interviewed to discuss their work in developing systems to help teams find great ideas.
Read more about it here.
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Posted by George Huhn on Thu, Apr 08, 2010 @ 10:42 AM
Not quite, although that was the promise in the title of an
article in the March 2010 "Wired" magazine about a recently invented algorithm called "Compressed Sensing" or CS. That isn't to say CS isn't a really cool algorithm for certain applications - it is and you should know about what it can do – but it can't make something out of nothing.
To understand the concept behind CS, think of a digital image. Different kinds of compression technologies (jpg, gif, png, etc.) are used to shrink the size of these images so they use less memory to store and process. Basically, these technologies work by using clever ways to reduce redundant or repetitive data points to a much smaller number of data points. For example, a large area of a single color can be saved without saving each data point since the color is identical. But even though compression can reduce an image size significantly, the compressed file still holds all of the essential information to display the image in its original detail and resolution.
Therefore, a digital image that is compressed to, say, 10% of its original size has essentially discarded 90% of its original data as unnecessary. So if 90% of the data that was originally collected by the image sensors is unnecessary, why collect it in the first place? Why not just collect the essential 10%?
The idea behind CS is that you can collect digital image data using far fewer physical sensors than would normally be used and then use the CS algorithm to reconstruct the digital image as if you had used a conventional number of sensors. So you lose the computationally expensive overhead of collecting all the data, analyzing it, and then discarding most of it. Instead, you only need to collect a small amount of it, and then use CS to reconstruct the rest. And CS can do a remarkable job of reconstructing an image from very little data.
The CS algorithm isn't just applicable to digital images. It can be used on all kinds of digital data processing from music to interstellar radio waves to scrambled radio communications.
CS works based on a concept called "sparsity," which describes the density of data. Conceptually, a floor that has a few balls spread out over it would be considered sparse whereas a floor covered with many balls of different colors all touching each other would not. It turns out that reconstructing an image using CS means finding the sparsest image that can be constructed from the dataset.
However, there is one key point that needs to be stressed: CS cannot reconstruct data that isn't there - you can't make something out of nothing. In other words, if you take a digital image using far fewer sensors than normal and there is a critical detail that is missed entirely by the sensors, it cannot be recovered using CS. Unlike CS, conventional image compression works well because it looks at all the detail first and throws away the data it doesn't need.
Nevertheless, the promise for CS is exciting, particularly in areas where full data collection can be difficult or impossible because of volume of data or physical constraints. These can be sampled using far fewer sensors than otherwise might be required and then reconstructed using CS to obtain a resolution that is adequate for extracting information. One of the major challenges in applying CS is determining the minimum number of sensors required to sample a given data set.
I have been thinking about how CS technology might be applied to business, process development, and manufacturing data. Can you think of any potential applications in your business?
Post script: The original title in Wired magazine was "F_ll _n T_e Bl__ks: A revolutionary algorithm can make something out of nothing." The on-line version's title was changed to "Fill in the Blanks: Using Math to Turn Lo-Res Datasets Into Hi-Res Samples." Much better.
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Posted by George Huhn on Mon, Jan 25, 2010 @ 12:54 PM
The Gantt chart was introduced to the world by Henry Laurence Gantt between 1910 and 1915. He described his invention quite simply in his book Organizing for Work published in 1919:
"…the following principles upon which this chart system is founded are easily comprehended:
First: The fact that all activities can be measured by the amount of time needed to perform them.
Second: The space representing the time unit on the chart can be made to represent the amount of activity which should have taken place in that time."
In addition to inventing this staple of project management, Organizing for Work shows that Gantt was a strong proponent of social responsibility for engineers and industry and the idea of an honest and democratic workplace:
"Industrial control is too often based on favoritism or privilege, rather than on ability. This hampers the healthy, normal development of industrialism, which can reach its highest development only when equal opportunity is secured to all, and when all reward is equitably proportioned to service rendered. In other words, when industry becomes democratic." (Organizing for Work, 1919)
"The business system must accept its social responsibility and devote itself primarily to service, or the community will ultimately make the attempt to take it over in order to operate it in its own interest. (Organizing for Work, 1919)
Doesn't that last quote sound a little bit like it came from the current healthcare reform debate?
I also thought that it would be great if these words from Gantt were hung in a prominent place in every project and project portfolio management office:
"First: We have no right morally to decide as a matter of opinion that which can be determined as a matter of fact.
Second: If we allow ourselves to be governed by opinion where it is possible to obtain facts, we shall lose in our competition with those who base their actions on facts.
The substitution of fact for opinion is the basis of modern industrial progress, and the rate of this progress is controlled by the extent to which the methods of scientific investigation supplant the debating society methods in determining a basis for action." (Organizing for Work, 1919)
The Henry Laurence Gantt Medal was established in 1929 by the American Society Of Mechanical Engineers is given for "distinguished achievement in management and for service to the community."
Mr. Gantt is one of those people that I like to imagine what more he might have done had computers been around when he was!
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Posted by George Huhn on Thu, Dec 17, 2009 @ 05:43 PM
Sunk costs are the costs that have already been incurred and cannot be recovered. We aren't supposed to consider sunk costs when making rational investment decisions, only the future costs.
But people do anyway.
How many times have you heard someone say, "Well, since we've already spent this much on it, we might as well finish it." They're making their decision based on sunk costs.
Ideas have sunk costs, too, only they're different from economic costs. When we spend a lot of time thinking about and working on a new idea, it is hard to let go of it in our minds, even when it proves unworkable or unfeasible. So we keep mulling it over and eventually we can become over-invested in it.
And then we can't evaluate the actual outcomes rationally.
Take the current Health Care Reform debate. Some people have so much sunk into the idea that Health Care Reform must be passed that they want to see anything signed, regardless of what is in the final bill. Others have so much sunk into the idea that Health Care Reform can never be good that they don't want to see anything signed, again, regardless of what is in the final bill.
Both of these groups are basing their positions on their sunk investments into their ideas of Health Care Reform, and not necessarily on the future costs and benefits of what is actually currently being discussed.
About 12 years ago I worked on a potential new treatment for AIDS. It was a unique molecule that ultimately failed in clinical trials. Since then it has wandered as a potential treatment from one disease du jour to another and failed each time. Recently, I heard that it had been proposed as H1N1 flu vaccine booster, again, with no plausible scientific rationale.
So now it is just an interesting molecule with no proven clinical application or clear rational for using or trying it as a future treatment for anything else.
It is an idea whose time came and went more than a decade ago, yet the inventors just kept trying. They can't let it go, regardless of the fact that the odds for success are much longer now than they ever were. But the accumulated sunk cost of their initial promising idea keeps driving them to continue investing in it.
"If we only keep trying…"
Sometimes it is useful to deliberately stop and consider if you're continuing to work on an idea because of what you have already mentally and emotionally invested in it or because of its actual future potential.
And sometimes the only way to avoid investing more time in thinking about a once-good idea is to just start working on a new and different one.
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Posted by George Huhn on Thu, Nov 19, 2009 @ 12:35 PM
Quantitative financial analysts ("Quants") who design trading algorithms or optimize them to work just a few milliseconds or even microseconds faster are in high-demand these days. Successful trading algorithms often work by taking advantage of millisecond market inefficiencies that aren't widely recognized by other traders. This advantage is lost once other traders discover and begin to trade on the same inefficiencies.
Since the profitable lifespan of proprietary trading algorithms keeps getting shorter, optimizing an algorithm to execute faster is one way to extend its lifespan. So the competition for hiring really good quants that can discover, develop, and optimize new trading algorithms is fierce.
Your business probably doesn't require microsecond decision-making, but the speed and quality with which your business can execute is going continue to become increasingly important. World-wide competition is speeding up innovation, shortening product development times, and reducing product lifecycles.
While many companies are using IT to improve business processes, most of them are just scratching the surface when it comes to using meaningful business analytics to speed up those processes.
When everybody in an industry is using the same IT and business processes, nobody has an advantage. The advantage will come to those who can discover, develop, and optimize business processes beyond what everybody else is doing. That might mean just looking at the little things that everybody else overlooks (or doesn’t think is important) and speeding them up by a few days or even just a few hours. Just as saving a few microseconds is important to a quant, saving those few days or hours could mean the difference between leading in your business or just being one of the pack.
Look around. What's limiting the speed of your business?
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Posted by George Huhn on Wed, Nov 11, 2009 @ 11:14 AM
We all want one of these buttons, right? Wouldn't it be nice to pry the "Help" button off your keyboard and put one of these in its place? When I want a problem solved, I don't want to look through dozens of menu items and forms, navigate through features I'll never use, and search through websites and PDF files.
I just want my problem solved. And so do your customers.
Two years ago, while everybody else was developing more and more feature-rich (and complicated) video cameras, a company called PureDigital released the point-and-shoot equivalent of a video camera called the Flip Ultra. It was small, inexpensive, simple to operate, and had only essential functionality. And it sold like crazy.
The problem it solved? How to get videos on the web easily and quickly without having to read a novel-sized instruction manual. Today, the Flip Ultra products are the best selling video cameras in the U.S.
Feature-creep and the resultant complexity are big challenges to many technology products. So instead of trying to improve your company's products and services by adding new features, what if you optimized them by removing some features and combining others?
What if your products and services could have only one button: the "Solve My Problem" button? What would it do? And since one button usually isn't realistic, what are the minimum numbers of "Solve My Problem" buttons that you need to solve your customers' problems in a delightful and surprisingly simple way? What if you prioritized your most important and fundamental customer benefits and then offered a product that delivered only those features and nothing else?
In designing our project portfolio management tools, we try to answer those questions every day. For example, we've reduced the effort of prioritizing your portfolio using Monte Carlo simulations to a couple of mouse clicks. If you can answer those questions while nobody else in your industry is even asking them, you may discover a whole new market out there waiting for you.
What are the best uses of your company's dollars and resources? Optsee
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® is a project portfolio management and budgeting optimization tool unlike any that you've ever seen.
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