Key Differentiator for Six Sigma: Its Infrastructure

Some detractors of Six Sigma have said that it just borrowed tools and techniques from earlier improvement systems – chiefly total quality management (TQM) – and repackaged and marketed it under a different name. While true, there is one reason why Six Sigma is different from its predecessors and why it is such a powerful improvement system – its infrastructure to manage and sustain organization-wide process improvement.

Here are seven success factors for why Six Sigma is a proven effective business change initiative.

1. Top management driven: The organization’s CEO or president leads the Six Sigma infrastructure and drives process improvement by actively promoting Six Sigma internally.
2. Alignment with vision and objectives: Six Sigma leadership ensures that all projects are aligned with the corporate vision and the objectives of all key stakeholders (customers, shareholders, employees).
3. Guiding coalition: Everyone in the Six Sigma infrastructure is bound by a common conviction to achieve business improvement. The change initiative is guided by, and deployed from, the top and executed down every level. The infrastructure includes leaders who work in boundary-less collaboration, ditching the inflexible, yet traditional, silo mentality.
4. Strong buy-in from the people: Six Sigma is a vehicle for employees to actively engage in process improvement, thus enriching job and workplace satisfaction.
5. Clear performance goals: Project teams establish clear performance and financial improvement goals to achieve overall corporate objectives.
6. Simple and rigid methodology: Six Sigma infrastructure imposes a robust, clear and simple DMAIC (Define, Measure, Analyze, Improve, Control) methodology. DMAIC harnesses a set of well-known tools and techniques for each phase that are proven successful in bringing improvement to the process and change to the organization as a whole.
7. Proven successful results: Six Sigma practitioners are customer-centric, process-focused, data-driven and analytically rigorous, which strengthens the probability of meeting both project’s and corporate’s goals and expectations.