Tuesday, February 08, 2011

Business Conduct and Statistical Thinking in Commercialization

I had an interesting question posed to me the other day: Have I ever observed or perceived an instance of suspect integrity or questionable business conduct? And if so, what did I do about it? I thought this would make for an interesting discussion with respect to practicing more (better) statistical thinking and statistical engineering in one's new product introduction system and commercialization (NPI), and product management of change (MOC) processes . I offer two different hypothetical situations...

Scenario #1:
In an effort to be "first to market", a new-to-the-world product is fast-tracked through the organization's formal new product commercialization process. Early reviews from customers are favorable. Prototypes have been shown and customer orders taken early in the product development phase. Proper risk assessments have not been completed. Equipment, process and product validation studies have not been completed. Limited product has been made - maybe on the intended production line, but more than likely only on a pilot line. Just one "Qualification" run - a short-term "machine capability" study - has been evaluated... with acceptable results. The organization's operating plan has aggressive Top Line sales growth and Operating Income targets. The NPI Gatekeepers are deciding whether to go ahead with an accelerated "soft" launch in order to meet customer demand and generate revenue.

Sound familiar? What would you do?
Some questions for thought:

  • How might the industry you are in, or the markets you serve, play a role in your decision-making?
  • How much risk is the organization willing to accept? Have they even quantified the risk?
  • What do you know about the customer's needs? (Basic, Stated, Unarticulated)
  • How certain are you that tribal knowledge and presumed understanding of VOC have been adequately validated?
  • Are the test methods relevant to the customer... do they predict fitness for use?
  • Are the TMs adequate (Gage R&R, resolution, stability, etc.)?
  • Has acceptable process capability been demonstrated: Short-term? Long-term?
  • How were the product specifications established?
  • How / where will product be sampled for testing?
  • What do we know about the suppliers' process capabilities?
  • How rugged is the product design?
What other questions should be asked?

Scenario #2:
The manufacturing plant manager is facing factory cost challenges due to the triple threat of high waste, rising raw material prices, and lower than forecasted sales volume. A second source of supply for a key RM is being evaluated for reduced cost and improved availability. The customer contract (perhaps the blanket purchase order) has a boilerplate template stating that it must be notified by the vendor of any planned process or product changes. The producer's product maintenance engineer resolutely believes, based on analytical assessments and bench testing, that this RM substitution will be transparent to the customer. The business has a formalized product management of change process, but it is not consistently deployed nor executed.

Should the customer be notified?

What questions would you have of the RM substitution project?
Some thoughts:

  • Is this an approved supplier?
  • Is this supplier ISO registered?
  • Or, has a site evaluation been performed? Or, has a self-assessment been performed?
  • Have you assessed the supplier's process capability?
  • Have raw material - process interactions been modeled with this new supplier?
  • How many distinct lots of raw material / components have been evaluated?
  • What types of product testing have been completed:
  •       Standard battery of manufacturing tests only?
  •       Plus, product development tests (e.g. Consumer-use tests)?
  •       Plus, any stress testing or accelerated life testing?
  • When did we last we validate our customers' requirements?
Other thoughts?

What does it mean to apply statistical thinking and engineering? I don't think it has a lot to do with tools. We have the tools; and there are consultants who can teach us to use new tools. It comes down to leadership. Leadership and execution that integrates strategic quality plan deployment with effective and efficient systems and processes. So, how are you helping your organization to become more customer focused, apply statistical thinking for better decision making, and drive the right behaviors for sustainable operational excellence, growth, and customer satisfaction?

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