Lean Sigma Analytics
Lean Sigma Analytics - provides the link between Strategy and Operations via an Analytics Modelling and a Governance Process to ensure sustainable improvement, innovation and competitive advantage is achieved.
Lean Six Sigma is a proven methodology for creating major change and improvement, however, only if it is focused on the strategically important measures in an organization. Sometimes organizations select and implement projects with a local operational focus which may result in sub-optimal results.
Typically, when companies want to reduce costs, improve working capital ratios etc. they have a brainstorming session or they ask the CFO for ideas. These ideas will often be very dollar focused, shut some factories down, rationalize production or tell departments to lay off a percentage of their staff. They hope that this will result in financial savings in 6-12 months. Research shows that many rationalization programs have limited success and indeed can often weaken the company in critical ways, e.g. by getting rid of talented people and critical skills and resources of knowledge and experience.
Financial results are typically driven by other factors in an organization, such as customer satisfaction, service, staff skills, etc. These factors are often the critical ones and in turn they are often driven by effective processes and good staff. Cost cutting, rationalization programs often ignore these drivers.
Our offer is to build a Program-of-Works Pipeline, incorporated in a Governance, Risk and Compliance model, which includes a business strategy map, based on company objectives linked to operational outcomes.
Our approach is to identify the data that is specific to the organization’s strategic objectives and outcomes, through a process of profiling and prioritizing transformed data from both internal and external sources. Analysis of these processes would ensure the organizations performance goals are achieved.
Lean Sigma Analytics is a unique framework incorporating the DMAIC Process with Data Analytics and predictive models, to assist senior management to identify the most important improvement projects, and prioritize them according to company objectives.
The Key Parts of Big Data and Predictive Analysis.
A measurement system such as an Organizational Strategy Map, and an Operational Scorecard that is structured to include all the measures that drive performance for the company.
Using Data analytics to source both internal and external and data types, cleanse it ready for transformation and consolidate this into an operational scorecard.Create a predictive model for the operational scorecard linked back to the Strategy Map of the Organization.
This involves transforming the data and using visualization and statistical methods to understand trends and relationships between the measures. This allows calculation of the strength of the relationships between the various factors in the scorecard.
The model is used to test the strategy model and the likely impact of different possible improvement projects on the overall strategy goals. The company can then identify the highest priority projects for their Lean Six Sigma (LSS) based improvement program.
Use the 3 R Model© to assess, sort and prioritize these opportunities and projects - projects that require complete process re-design, projects that will improve performance very significantly and go-do-it projects. The results in an action strategy for the organization. Attacking the highest priority projects means that the effort in developing capacity in the Lean Six Sigma framework will have the greatest possible payback. Lean Sigma Institute assists in building internal capacity to carry through these improvements.