• It is a way of thinking and behaving every day- not a special one-time intervention project.
• It enables your work - it does not disrupt your normal tasks or career path.
• It promotes mindfulness about what you choose to think about and how you go about shaping the future you and your peers want as you seek to fulfill your customers' needs.
• It does not use a numerical range of six standard deviations (6s) as part of its defining nomenclature; it does use the notion of the standard deviation (sigma) because variation is still a measure of a range of what is possible, what can happen as we consider what establishes future outcomes.
• Its focus is mainly on the inputs to a system or process.
• It uses probabilistic design principles as opposed to statistical analysis of historical output data (...what happened? vs. if this input changes what is likely to happen?).
• It uses a proactive view as opposed to reacting to what unfortunate thing has happened.
• It simulates future states and outcomes so you can pick the future you want to accept; consequently, it defines future states and prevents future problems.
• It defines Voice-of-Customer-based limits along with fail-to-satisfy boundaries and ranges.
• It is based upon fundamental relationships, their interaction and sensitivities to each other at the input level - heavy focus on the Xs... the Ys are what they are!
• It enables innovation as opposed to activating intervention.

The following two lists outline the differences between traditional LSS and FutureSigma. FutureSigma represents a transition from a statistical approach to a probabilistic approach. LSS has often been positioned as the conversion cycle from a practical problem to a statistical problem and then back into the practical units of a given process. Our tradition in LSS has been to study the variables that define the past - the statistical Ys. The key of FutureSigma is to work with the input variables that control the future - the probable Xs.

Next month, more about FutureSigma...

Traditional Lean Six Sigma

FutureSigma

Define and react to a known problem Measure outputs (Ys) of a broken process by gathering samples of historical data Analyze the statistical behavior and intrinsic value of the Y output response data and isolate which input Xs are value-adding and control the mean and standard deviation of the Ys (Cause and effect dynamics & relationships) Improve  the process by changing the Xs that have the dominant effect on the Ys (outputs); remove non-value adding Xs & Ys Control the process, continuously improve and prevent future problems using a designed control plan using the value-based X-Y relationships

Define opportunities and requirements to innovate while preventing future problems Identify the fundamental inputs (Xs) that control the future outputs of a system or process (product portfolio, technology, product...etc.) Probabilistically identify the distribution of the input Xs, including details around the variational uncertainty characteristics of the inputs (Xs) Define the Ys as a function of the Xs model that controls the underlying relationships and dynamics of the system or process Identify the Voice of the Customer limits where they consider the function to be in a state of failure-to-satisfy (Limit State Function & its boundaries) Run probabilistic "what-if" simulations to look at future likelihood scenarios to identify Most Probable Point of Failure (as defined by your customers or stakeholders) Analyze the main effects, interactions and sensitivity relationships between the probabilistic Xs as they affect the Ys with respect to the Limit State Function. Make decisions about the future state you prefer using the most likely outcomes based upon the probabilistic inputs