Managing innovation is a priority for companies. Whether big or small, all companies work daily to design a fluid and productive innovation process. Achieve this goal is very hard because it starts from "soft" dimensions such as company values, leadership style, the enhancement of human resources and organizational culture, and then translates into practice in paths, processes and finally products.
When organizations try to scale innovation programs, which by nature incorporate incremental learning and results, a dilemma often arises: how to guarantee good performance without flattening experimentation? This is not a question from the simple answer because it leads to reasoning on a series of balances that are often predetermined, especially in large companies.
Facing a new innovative project, one of the first decisions, even implicit, that management will have to face is how to mix and balance the weight of two dimensions: the orientation to performance and profit and the degree of flexibility that the project must enjoy in order to encourage experimentation, learning by doing and new perspectives.
Importing the concept of innovation in companies, it is easy to understand that often a division has its own temporal objectives (quarterly, half-yearly or yearly), a dedicated budget, resources that support the entire business and so on. It is therefore neither so simple nor so immediate, to change or create new combinations of functions, orientations and expected results.
To the question "to what extent to standardize the project with control measures and procedures, and to what extent the process has to be flexible?" is possible to respond with a mindset that guides the effective implementation of innovation.
Step 1. The innovation portfolio of a company is made up of different initiatives.The solution adopted for a project will not be replicable (and hopefully must be exactly like this if you are really innovating) for all new incoming projects aimed at innovating business practices, the markets, and the products. The innovative potential that is expected can come from internal, external practices, challenges and very different ways of team engagement. Therefore, the first step is to understand the drivers of innovation, the degree of control over these drivers (external resources, internal resources, the mix of internal and external resources), and the expected output. Once these aspects have been defined, it is possible to begin to understand the input and output variables: a) directly controllable; b) measurable; c) modifiable during the process.
Step 2. Build a common language. After defining the conceptual "units" and the resources assigned to a project, the next step is to design a shared model of innovation management with the team. Activities like define the methodology, expectations, milestones, communication of any failures or progress, help to have a schedule and behavioral rules. Involving the team in the definition of a common language of innovation helps to face the delicate choice of the degree of standardization: which are the milestones we are committed to achieving in order not to generate poor quality results? What are the abandonment scenarios? And what are the scenarios for further experimentation?
Step 3. The operational flexibility. Finally, the degree of operational flexibility of the team should be defined. Consider the available resources, internal and external, and the intermediate and final objectives to be achieved to produce results, what degree of operational creativity can the team express? To what extent is the team supported in advancing new proposals? How are these proposals are discussed?
The approach allows a high degree of freedom, it is an approach that allows you to move along the timeline of innovation, assisting, observing and supporting teams in the risk of experimentation, without sacrifice results.
The results orientation can represent a limit that makes managerial activity short-sighted, the innovative effort is not to put the result before innovation. Not to sacrifice the long-term vision, not to waste opportunities, not to sterilize the experimental processes in favor of a result-oriented vision and not to the result: value creation.