Productivity: locate improvement with those closest to the process!

Productivity and how to improve it has been very much in the news this week. A Financial Times lunch briefing ‘Below potential, but how far?’ contained the following wonderful sentence:
“Productivity gains may rely on protecting or putting in place conditions where workers themselves can and want to figure out how to do things better.”

The same briefing references the recent paper ‘Small steps for workers, a giant leap for productivity’ by Igal Hendel and Yossi Spiegel (published in the American Economic Journal: Applied Economics 2014, 6(1): 73–90 http://dx.doi.org/10.1257/app.6.1.73).
The authors write-up their study of performance at a steel mini mill over a 12 year period. The pair had access to detailed output records for the production of an unchanged product.

Their findings and to what they attribute them to, are both heartening and quite amazing.

Daily production of the product doubled in the study period.

15% of this increase can be attributed to capital investment at the mill
18% can be attributed to the use of an incentive scheme for workers at the mill
67% cannot be explained by the use of other external influences. Hendel and Spiegel suggest that “Learning by experimentation, or ‘tweaking’, seems to be behind the continual and gradual process of productive growth”.

Output growth was continuous, suggesting that a flow of small improvements to the production process took place.
These small improvements (or ‘microinnovations’) took the form of experiments with the process; trying new ways to better execute each step of the production process. These experiments can expand capacity substantially.

The authors suggest that these ‘microinnovations’ are necessary to fully exploit physical changes such as improvements to equipment.

“Findings imply that learning by doing is not simply a function of cumulative output and is not guaranteed automatically. Rather it is the result of an active experimentation process”.

The authors’ suggestion is that regular, small experiments with the production process (importantly, not to fix but to get better) were made by the workers involved which led to incremental improvements in output.

In ‘Design education and innovation ecotones’,

Ann Pendleton-Jullian, states that “Experimentation is explicitly about the framing of questions through which we learn about the things we are experimenting with and on. Experimentation also implies that it is not merely a process of providing questions and answers, but a recursive process of repeated questioning in which partial, possible, or probable ‘answers’ are tested and then subjected to new questions with new responses leading to new propositions, more questions, and so on. Because experimentation is recursive and because it is ongoing (fueled by curiosity), this process of knowledge building has the potential to keep pace with its environment while simultaneously affecting this environment.”

“Experimentation is the conducting of specific pieces of work (acts or opera- tions) for the purposes of discovering something unknown, or for testing an idea, a principle, a proposition. It is the means through which creativity is linked to innovation.”

“Innovation requires deeply contextualized knowledge; knowledge that comes from engagement of the context, not before engage- ment of the context.” (my italics)

This reinforces one of the central messages of Kaizen; that the responsibility and the expectation of process improvement should be located with those who are actually involved with the process. With those that have and understand the context in which they are working.

My key question on reading the findings from the steel mill is how did the management create the conditions for success here. Possible answers come from the ideas in ‘Building a Learning Organization’ by David A. Garvin,https://hbr.org/1993/07/building-a-learning-organization here experimentation is defined as an activity which involves the systematic searching for and testing of new knowledge. Using the scientific method is essential, and unlike problem solving, experimentation is usually motivated by opportunity and expanding horizons, not by current difficulties.

Ongoing programmes normally involve a continuing series of small experiments, designed to produce incremental gains in knowledge.

Successful ongoing programmes share several characteristics.
1. They work hard to ensure a steady flow of new ideas, even if they must be imported from outside the organisation. (Go and see)

2. Require an incentive system that favours risk taking. Employees must feel that the benefits of experimentation exceed the costs; otherwise, they will not participate. This creates a difficult challenge for managers, who are trapped between two perilous extremes. They must maintain accountability and control over experiments without stifling creativity by unduly penalizing employees for failures. (The incentive scheme at the steel mill was not individualised but a group one for the whole production team on a daily basis).

3. Need managers and employees who are trained in the skills required to perform and evaluate experiments. These skills are seldom intuitive and must usually be learned. They cover a broad sweep: statistical methods, like design of experiments, that efficiently compare a large number of alternatives; graphical techniques, like process analysis, that are essential for redesigning work flows; and creativity techniques, like storyboarding and role-playing, that keep novel ideas flowing. (Ongoing developmental activity both of skills and behaviours).

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