I wrote last week about building intelligent analytics systems by putting people at the center of the design process. I call this process Cognitive Design. This week, we’re going to delve more deeply into just what Cognitive Design is and how it’s implemented.

Cognitive Design, as it applies to analytics, is the iterative process of combining user experience and context with the right technology to create dynamic analytics ecosystems. These ecosystems can help companies solve complex problems in an atmosphere where the variables are often unknown and always changing.

Using Cognitive Design principles, you can cultivate innovation and gain insights to generate ideas, ask new questions, and quickly prototype and implement analytics solutions.

Cognitive Design doesn’t just happen. It’s an active process. The first step is to think like a designer. The idea is to find a solution, not just list problems to overcome. Obviously, you’re trying to solve a problem, or you wouldn’t be building an analytics system in the first place, but the idea here is to focus on the solution, not just fixes to overcome discrete issues.

For example, the problem might be that management doesn’t have the insight they need into their supply chain. That’s thinking about what you don’t have. If you think that way, you’re likely to think only about ways to solve that specific problem, and you’ll end up playing a giant version of whack-a-mole. The Cognitive Design process enables you to innovate by listening to your customers—in this case your management and knowledge workers—to arrive at a solution.

Using Cognitive Design principles, your solution might be to build a cloud-based, interconnected supply network that optimizes your logistics and procurement operations and gives you the insight you need to foresee problems and take advantage of opportunities. It’s a shift in perspective that can make a world of difference in how you approach your initiative.

In building your innovative solution, it’s critical to put people first, and really understand how they think. That’s the cognitive part. Put trust in the experience of your user base to understand the ecosystem in which they operate, and to know how to solve the problems they face.

Using Cognitive Design, you can open the design process to create an environment where all ideas are explored and valued. There will be good parts of nearly every idea, and you can combine ideas in novel ways. Again, you can’t simply start from a problem viewpoint. Visualize SOLUTIONS.

The next step in the Cognitive Design process is to take the best ideas and model those. Create working prototypes and evaluate their performance against requirements. When evaluating prototypes, set yourself up to fail quickly. That’s not to say you want to fail, but it’s critical to have an iterative process in place that lets you continually ask: should we scale up this model, or just move on?

The best solution will be the one(s) that hits the sweet spot between innovation and practicality. In making the choice, use criteria that can be both quantified and qualified. Rely on the experience and intuition of decision-makers and knowledge workers to make the best choice.

Also—and this is a big one—don’t trade the most effective solution for pennies. Cost matters, but it shouldn’t be the final arbiter of which solution is chosen. Within established constraints, use the most, and the best, resources available to execute the chosen solution. Execute as quickly and effectively as possible to realize results in the quickest time frame.

Take solutions that are working on a smaller scale and push those innovations through to the entire organization. As solutions scale up from small to enterprise-wide, companies that employ a Cognitive Design approach can leverage lessons learned in the design process to tweak those solutions so that they maximize their effectiveness at scale.

So now that we’ve explored what Cognitive Design is, and roughly how to go about it, next week we’ll talk about why you should use it, i.e., what it can do for you and how the solutions you generate can be truly innovative.

General manager of Teradata Consulting and Go-To-Market Analytic Solutions. Thought leader in analytics, business intelligence, big data, and business transformation. My passion is helping my clients drive value through data and achieve a sustainable competitive advantage.

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