Idea Data Model

Ideas, like most things, have a definite life cycle. They are created, they grow, they morph into something new (a product or service or business model) which then has a product lifecycle. Eventually those products or services die. Birth, growth, life, extension, death.

What's interesting about an idea is the metamorphosis it goes through during these transitions - and the abrupt and suddenly very different requirements at each step in the process. Look at each phase in turn:

Birth:

An idea is born when someone recognizes an opportunity, or shouts out an idea in a brainstorming session, or tastes a compound meant for kidney disease and recognizes the potential as a sweetner. An idea is often nothing more than a statement - "let's attack the XYZ market with our latest nanotechnology capabilities". If you've ever been in a brainstorming exercise you know that an idea starts out as nothing more than a short statement. That statement may have tremendous meaning in context, but very little of that meaning is captured or fleshed out.

Growth:

An idea grows dramatically as a person or team begins to work on it. Suddenly the idea needs greater "Depth". The idea must be scoped, defined, bounded, measured, costed, incubated and evaluated. As more and more people become involved, the idea grows and changes. The idea starts out an "inch wide and an inch deep" and ends up much more robust. It has definition, context, supporting materials, costed analysis and so forth. The "data model" for a particular idea at the end of the growth phase is much richer and much more complete than when it entered this phase.

NPD:

However, when an idea moves from an "idea" stage to new product or new service development, an abrupt change happens. Now the idea needs to be placed into context of the manufacturing or service delivery mechanisms. It needs a bill of material, a recipe, a shop order. It needs to move from the realm of possibilities to the realm of actuality. The idea moves quickly from ephemeral to structured. The data requirements are significantly different and drastically larger. The idea must become more exact, rigid, fixed in time and space. The data model becomes more about measurements - heights, weights, widths, costs, and so forth. So in this phase the data model changes dramatically from what was passed along as an evaluated idea.

Product and Extension:

Once the product or service is released, it is prepared for sales and marketing. It is priced, packaged, shipped to channels or customers and made available for purchase. Another iteration or layer of the data model is added, and another layer added as new product extensions are released.

Think about the dramatic change in the scope and data model of just one idea. Initially, an idea may have been to carry music around in a portable format. Now think about the definition of an MP3 player or iPod and the specifications that must exist to build, sell and ship that product. The changes inherent in moving the concept from early idea to final product are tremendous, yet few firms manage this process from idea to final product, much less considering the dramatic and sudden changes in product definition, scope and detail around an idea.

What's the data model of an idea? How do you define the data required to capture an idea, and the data required to convert an idea to a new product? What systems capture and manage this data for you?