A Glimpse At the New Environment in Business and Industry

1. A Glimpse At the New Environment in Business and Industry Roger W. Hoerl Quality Leader - Corporate Audit Staff General Electric Company Fairfield, CT ASA Joint Annual Meetings August 1999

2. OUTLINE • Overview • A Case Study • Changing the Statistics Paradigm • Implications For The Future of Statistics • Summary

3. OVERVIEW • “The times - they are a changin” • Example - Blurring of the distinction between “Industrial” versus “Business” statistics • Example - Wide availability of statistical software for the “masses” • These changes are occurring whether we like it or not • The Statistical Profession must either lead, follow, or get out of the way! • Obviously, we should lead, but how?

4. CASE STUDY • A case study I worked on previously may shed some light on this question. • The statistical work done is not necessarily profound or noteworthy, this is not the point. • The point is HOW the work was done, and particularly as it relates to the emerging role of the statistician. • This is a real case study, and the data are real, but to protect confidentiality, some details have been modified.

5. CASE STUDY • I was called to attend an emergency meeting of a “swat team” of technical experts, to resolve a problem with flushable baby wipes. • Customers had been complaining that the wipes were not properly flushing, and some customers with septic tanks were threatening to sue to recover the cost of cleaning out their septic tanks. Senior management was adamant that the problem must be resolved immediately. • Just prior to our first meeting, the plant manager told us he would be willing to switch to more expensive fibers, at a cost of $40,000 per day, if we thought this would solve the problem.

6. Figure A Calculation of Net Realized Revenue (NRR) Distributor Subtracts Rebate Vouchers From Invoice NRR = (Gross Sales At List) - Rebates - (Miscellaneous Promotions & Discounts) Order Booked With Distributor List Price Invoice Issued Distributor Sells to Hospital (Time Lag) Distributor Sends Copy of Sales Contract To Rebate Center, With Paperwork Rebate Center Sends Voucher To Distributor

7. CASE STUDY • When the meeting began, each technical expert told the “team” what the cause of the problem was, and what must be done to solve it. These “solutions” were all different, and ranged from chemical changes, to new synthetic or natural fibers used, to problems with new, low volume toilets. • After much debate, I convinced the team that we should first start with a clear definition of the problem, evaluate existing data, and then agree on a joint path forward to resolve it. • A critical evaluation of customer complaint data revealed that the problem actually began almost two years ago.

9. CASE STUDY • The first step was to verify that there was a real problem. • A team visited a complaining employee’s home, and opened their septic tank (I had a previous commitment that day!). • The problem was real - the wipes were not breaking down properly, and strangely, some natural (cellulose) fibers were floating in the tank. • The floating fibers were thought to be impossible, since cellulose is denser than water. • We could not blame new, low volume toilets!

10. CASE STUDY • Upon obtaining this data, the team met again, and as a “neutral party” (no pre-conceived solution), I facilitated the team in a “brainstorming” session to identify potential root causes of the problem. • Numerous ideas were presented and documented, followed by an open discussion. • The open discussion produced more “heat” than “light”, so we used “multi-voting” to narrow the scope to the most likely causes. • These were new synthetic fibers, a surfactant (soap) used in the process, addition of chemical “X” in the wet end, and chemicals in the local water supply.

11. CASE STUDY • The “swat team” split up into 5 teams, one each to focus on the 4 potential root causes, and one to work on developing methods to actually measure “flushability” and also “floating”, since there was disagreement as to whether one or both were the real root cause. • The fiber team ran a DOE, and found that while fibers made a difference, they could not explain the significant difference between this product and competition. • The surfactant and water chemicals teams ran controlled experiments, and found no evidence of a problem.

12. Competition Us

13. CASE STUDY • Attention now focused on Chemical X, by process of elimination. • This team had planned a plant experiment to change the addition point of Chemical X, but this had been vetoed by plant management. • Addition point, as opposed to the presence of Chemical X was the real variable, and could not be adequately addressed in a laboratory experiment. • One team member did some laboratory “tinkering”, however, producing the following data, and suggested that Chemical X, and fibers, with a possible interaction, were root causes. Others vehemently disagreed.

15. CASE STUDY • While the debate was raging, a plant engineer reported that after a shutdown, the flushability and floating tests preformed on the product were now at normal levels - the same as competition. • Upon investigation of this improvement, it was discovered that Chemical X had accidentally been left in “water flush” mode, i.e., while the instrumentation showed Chemical X being added, it was really pumping water into the process, not Chemical X! • Everyone, including plant management now accepted Chemical X as the root cause of the problem, and new equipment was added to change the addition point. • Once this equipment was installed, the flushability and floating problems went away immediately. Preventive testing and procedures were put in place to prevent reoccurrence. The “floating” fibers phenomenon was never explained.

16. Key Take-Aways • The statistician (me) was a full member of the team - accountable for results, not a “consultant”. • The statistician did none of the statistical analysis, this was done by the team (with input from the statistician). • The statistician took a “leadership” role, in taking charge of the “problem solving process”. • The most valuable contribution of the statistician in this case was leading the team through the problem solving process - not statistical methods consulting.

17. Hypothesis: This type of role for the statistician is consistent with general trends in business and industry. These changes have also been accelerated in companies implementing Six Sigma, or other statistically based improvement initiatives. In other words, we don’t have the option of choosing to accept the new paradigm or keep the old one!Corollary: These changes provide a glimpse of the future of statistics.

18. The New Statistics Paradigm • Everyone uses statistical tools; these tools are not “owned” by statisticians. • Financial/service applications are becoming more important than manufacturing and R&D applications. • Statistical Thinking is becoming more important than statistical methods (“Big picture” view versus micro view). • Statisticians are still needed and valued, but not to analyze data - people do that for themselves. The role is now significantly different!

19. Analyze data and design experiments Teach statistical tools Work with technical people Consult on other people’s projects Narrow expertise and accountability “Benign neglect” Determine the appropriate tool set Design training systems Work with managers Lead cross-functional projects Broad expertise and accountability “In the firing line” The New Versus Old Role OLD - Operational NEW - Tactical

20. Related Business/Industry Trends • Wide availability of easy to use statistical software (“democratization of statistics”). • Organizational delayering - less room for “consultants” or “specialists”, and no place to hide. • Shift from a manufacturing to “service” economy (even in manufacturing industries). This trend is being accelerated due to the Asian financial crisis, and subsequent high worldwide inventory levels, not to mention the explosion in e-commerce. • Emphasis on broad application of basic tools versus narrow application of advanced tools.

21. A Glimpse At The Future of Statistics in Business and Industry • Statistical thinking and methods are routinely applied by practitioners as “part of the job”. • Professional statisticians are “leaders”, not just “doers”; similar to the current role of computer scientists. The people who do well in this role are very different than the people who did well in the old role; e.g., broad, “strategic thinkers”, OE skills. • Financial and service applications are growing more rapidly than those in manufacturing and R&D. • Broad application of statistical thinking (the “forest) is valued more than the tools (the “trees”).

22. One Data Point on Statistical Thinking • “I am greatly encouraged by the attention currently being paid to the issue of teaching statistical thinking, as opposed to statistical methods.” • Colin Mallows - “The Zeroth Problem”, February 1998 American Statistician

23. Summary • The world around us is changing very rapidly. • A significant change in the roles of professional statisticians is required to keep pace. • While much attention has been focused on being better statistical consultants, traditional statistical consulting is a declining market! • Key aspects of the needed future role involve giving up “ownership” of routine use of the methods to assume a leadership role, and greater emphasis on broad application of statistical thinking versus narrow expertise in the tools.