Implementing innovation strategy within planned resources and estimated timeframe is what management control of innovation is striving to achieve. Management control systems differ depending on type of innovation, measures monitored, and role of innovation portfolio managers in decision-making. Key contemporary approaches for innovation performance controlling are The Innovation Value Chain, Innovation Scorecard, and Stage-Gate system.
One of most recent, widely adopted and used approaches is the The Innovation Value Chain formulated by M. T. Hansen and J. Birkinshaw. This approach focuses on such stages of innovation development as idea generation, conversion and diffusion, and applies non-obvious, adequate performance measures for each of them. For idea generation, key measures are number of high-quality ideas generated within company’s unit, number of such ideas generated across the units (to reflect in-house collaboration), and number of high-quality ideas generated from outside the company (to reflect contemporary open innovation paradigm). Conversion within The Innovation Value Chain is measured by percentage of ideas generated that had been finally selected for development and funded, and by funded ideas that led to revenues. The last stage of diffusion is measured by percentage of penetration of new product in selected markets and its sales channels.
Another approach, developed by T. Davila, M. J. Epstein and R. Shelton is Innovation Scorecard. This approach focuses on structuring innovation process in logical order of inputs, processes, outputs and outcomes. Each of these elements has appropriate metrics to track. Inputs are measured by access to talents and commitment to innovation expected from employees. Processes are reflected by measuring balance in innovation portfolio and quality of innovation pipeline. Outputs are tracked by measuring the number of new customers, and achieving leadership in technology and innovation domain. Outcomes are reported by growth in sales and profits.
One of most common approaches in measuring performance of innovation is Stage-Gate developed by J. H. Hertenstein and M. B. Platt, which presents innovation as process of go/no-go decisions. Although it is a much older system than Innovation Scorecard and The Innovation Value Chain, it’s still much in use, especially in multinational technology companies. Stage-Gate understands new products development as a sequence of decisions with specific indicators required to be met at every decision step. Stage no. 1 within Stage-Gate is often measured by market research and feasibility, visualization and design development for new product. If these metrics are met in stage no. 2 new product undergoes technical development and prototyping accompanied by future production design and tooling. Once the decision after stage no. 2 is positive, in stage no. 3 product goes through production, quality testing and marketing campaign oriented for first orders/pre-orders. If results of this stage is successful, new product in stage no. 4 is audited for customer service/post production care and customers satisfaction.
Contemporary design of management control system for innovation in companies derives from above mentioned approaches and is often enriched by sets of financial and non-financial performance measures for new products development.
Typical dilemmas of innovation portfolio managers refer to timing of measurement – from the front end to market launch or later stages, areas of measurement – resources, time, costs, customer satisfaction, mix and balance between financial and non-financial measures, organizational level of management – units, departments, organization and details of measurement.
Measures reported by innovation portfolio managers very often refer to number of new products started, number of new products completed, number of products in pipeline, percentage of new features in new product compared to its previous version or substitute, and alignment of design with company strategy.
Empirical evidence about results of innovation performance controlling are at least intriguing. For example J.M. Bonner proved that upper-management control and interventions in process of innovation negatively affects innovation projects’ performance. What is supportive for project performance is however definition of goals, monitoring and evaluation between project team and top management in early phase of innovation project. Research performed by K. M. Eisenhardt and B. N. Tabrizi identified negative impact between time spent on new product planning and development time, and outlined supportive role of shorter time between innovation project milestones (enabling product iterations). M. Benner and M. L. Tushman researched role of formal process control in new products development and found that having formal process orientation within company such as ISO norms negatively impacts on exploratory type of innovation.
Too complex innovation controlling systems might constrain creative behaviors; underestimate innovation output in open innovation paradigm. On the other hand they increase efficiency of the processes, coordination between teams, fosters organizational learning.
So what is your innovation controlling approach?
