Knowledge is the most important commodity we possess. The ability to harness ideas to improve ourselves has always been the competitive advantage of our species.  One of the most effective ways to cultivate ideas -- especially in addressing business challenges such as those that are AI- or data-driven in nature -- is to build teams around cognitive diversity.

Diverse teams are effective because they draw on a unique set of backgrounds and experiences to look at problems from multiple angles. Imagine if you could take your best employee and create as many clones as you could ever desire. You might think you’d achieve better results by having multiples of your best engineer or scientist addressing the toughest problems. But the exact opposite is the case.

If you have the same people with the same backgrounds and skills looking at a question, their answer is going to tend to be the same. When your goal is innovation, you want those answers to be different. You want several options and “out of the box” thinking. You want cognitive diversity.

That means, instead of clones, you want teams composed of individuals with all sorts of backgrounds. They went to different schools. They have different interests and hobbies. They grew up in different parts of the country, or different countries entirely. The diversity in their life experience contributes to their approach to solving problems, and they will each approach questions in their own way. That’s how one team member can see aspects of the problem that others will miss.

Capstones are a highly cost-effective way to introduce cognitive diversity to an important project. Many universities around the country require seniors to work with a private company on a capstone project to demonstrate that they can apply their studies to the real world. Companies can help these students graduate while advancing company goals through cognitive diversity. It’s great for both sides.

However, anyone attempting to set up a capstone project entitled “Build us an advanced artificial intelligence platform” is going to be sorely disappointed. It’s nowhere near that easy. The results that capstone projects deliver depend entirely on the energy and skill that the company puts into them. If you want to build an AI system from scratch, the project must be broken up into multiple, stand-alone projects that systematically build upon one another toward that final goal. Each capstone is one piece of the overall puzzle.

For example, one "challenge" might be to identify the algorithm that a machine learning algorithm would use to solve a problem. The next team might validate the algorithm using real data from the company. The final team might create a user interface that puts together all the preceding work so that it’s a ready-to-go product for internal use.

Multiple capstone teams might work in parallel, or sometimes they will work sequentially, building upon each other’s work. The teams work on discrete problems that are within their capabilities -- perhaps stretching them a bit beyond what they might think they can do. But the product can be highly advanced, beyond what any could have done on their own. Being part of a team working on something highly advanced is incredibly rewarding for the students.

Tips for harnessing effective capstones

The way to draw the best out of these students is to start the project on the right foot from the beginning.  The setup stage of a capstone is the most difficult, because it requires a vision not only of the final goal, but all the pieces that go into it. So, it’s worth devoting extra resources and attention into ensuring the project starts off right.

Another key issue in the beginning is to realize that each school has unique strengths and weaknesses. For instance, one school might be better at science, another more skilled at fostering communications in a team environment. Matching each school’s advantage with the needs of each step in the project helps drive success.

Even the best-developed capstone project will not be a fire-and-forget process. Internal company stakeholders need to work closely with each team to guide them through the process as subject matter experts. Their input is vital in ensuring the project unfolds in the right direction.

Capstones are effective because the students who participate are highly motivated. This is their first chance to show off their skills in a work environment, and they are given an opportunity to shine. Since they’re not part of the company culture, they’re going to approach problems from different -- often surprising -- directions. While every individual attempt won’t be successful, the collective effort tends to deliver impressive results. Set the project up right, and you won’t be disappointed.

Joseph Byrum is the chief data scientist at Principal Financial Group. He holds a Ph.D. in quantitative genetics. Connect with him on Twitter @ByrumJoseph.