Here is another look at the “lean obstacles” survey questions, again breaking it down by some key demographic factors (more details here).
Looking first at the split between Private and Public companies, there don't appear to be any major disparities in the results. The largest gaps are in “lack of implementation know-how” (a bigger problem at the Public companies) and “lack of crisis” (a bigger problem at the Private companies). The table below shows the full results, broken down by full survey population, Public, and Private.
There are somewhat similar patterns when looking at Larger (>$250M) and Smaller companies. Smaller companies have a higher percentage of responses where “lack of top management support” was the top obstacle, but the finger of blame pointed at top management was the highest vote getter in both populations. The full results are shown below.
Now, we look at the final breakdown, the three “tiers” of the organization chart. The Middle tier (managers, technical, and support roles) and the Lower tier (supervisors and front-line employees) listed “lack of top management support” as the #1 obstacle (22.6% and 27.8%). The blaming of top management increases as you move further from the executive suite.
When you look at the “people blaming” obstacles, all four of them (top management, middle management, supervisors, and employees), the Lower tier placed more blame (66.7% of respondents said one group of people was the top obstacle) than the Middle tier (51.6% blamed) and the Top tier (41.2% blamed).
The Top tier placed more blame on middle management (23.5% listed this as their top obstacle) than on top management themselves (17.7%). Interestingly, ZERO percent of the Top tier listed supervisors or employees as the top obstacle to Lean implementation. I wonder if this is a case of top management taking responsibility for their Lean efforts (as they should) or if it's a function of distance from the shopfloor?
The final table shows the full breakdown by organizational tier.
What other things stand out to you from this data breakdown? What other hypotheses or generalizations would you try to make from this?
Next, we'll put the numbers and the simple blaming aside and we'll start looking at the real meat of the survey — the “5 Whys” exercises and the root causes that survey respondents got to.
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