What's Science Got to Do With It? (PDCA)
You will recall that our culture of continuous process improvement adheres to specific work rules as defined by Steven Spear in "Decoding the DNA of the Toyota Production System."
The 4th rule pertains to making improvements and relies upon subjecting proposed changes to the discipline of measurement, data collection, analysis and then reassessment for effectiveness via data collection again. This reliance on measurement and data is at the heart of the PDCA or Deming cycle and has been referred to as the scientific approach to quality improvement. We approach this as a culture of aligned and self-directed work teams and leaders in the Henry Ford Production System resulting in thousands of documented improvements over the years.
Scientific advances require the generation of a hypothesis about what could be and an experiment to potentially disprove that hypothesis based on experimental data. This is not unlike suggestions generated to make changes that are hypothesized to improve processes. We test them for positive effect and then agree to adopt the change or not. The more numerous and more frequently we can turn around these tests of proposed changes, the more rapidly we can improve current conditions.
To base change, especially thousands of them, on fiat or the voice of the loudest, the first or the oldest amongst us would be folly. The scientific basis of change requires us to propose a hypothesis statement or best guess that may or may not be true. "If we change this, then this will happen." This statement of proposed change is then to be tested. Therefore the test plan requires a mini-experiment and requires us to take the time to propose and agree on measures and data collection that would properly assess the change reflected in the hypothesis statement.
For instance, our hypothesis statement might be as simple as- if we move and store the routine supplies for our job closer to the place where we conduct the work, we will shave off the time of wasted human motion by 20% over one shift. Ergo, we will open capacity for increased productivity and throughput. Now we must sit down as a team and devise how to measure our wasted human motion on that task and the other variable parameters so that we can compare the precondition baseline of motion associated with getting supplies and the post-change condition of motion in that same job.
Science is an open ended system in that each hypothesis answered generates more questions that require an explanation. Thus there is a cycle of questions, answers, and more questions advancing knowledge. This mirrors the PDCA cycle.
To translate to our world of work, in our endeavor of striving for more efficient work processes, we continually ask what else can be done and tested to push us toward a target goal or a more perfect way of doing things.
The Ideal Condition
Often, that more perfect way of working is characterized by handling work such that it can be completed 'on demand', defect-free, one piece at a time (with minimal if any batching), with no waste (remember there are 7 forms of waste), immediately (timely for your customer/patient), and safely with respect for people (emotionally, physically, professionally). These attributes describe a so-called ideal condition in a lean production system espoused by Toyota.
Just some thoughts as we tackle the challenges of 2011 together, one piece at a time.
So, blind me with science this year!