“Scanlon Principles Lay the Groundwork for Lean”
Target
2007 Volume 23, Number 5 (Available at www.ame.org)
Though many people think of the Scanlon Plan as merely a financial formula for gain sharing, this interesting article describes the history of Joe Scanlon and how he developed his plan based primarily on equitably sharing the financial benefits of employee involvement, leadership engagement, continuous improvement, focus on the customer, integrated strategic and tactical planning, and innovation.
After Scanlon passed away in 1955, a young psychologist at MIT named Carl Frost carried on his work and distilled his principles. The combined Frost-Scanlon principles are:
- Identity—This principle refers to employees understanding the realities of their organization, including:
- Who the customer is
- The finances of the company
- What is the most important thing to work on
- How do you know if you are doing things right
- Participation—This is defined as “an opportunity management provides to employees, to influence decisions in their area of competence, that they can accept or not.” The more people know, the more they should be able to influence decisions. Suggestion systems have been a key part of Scanlon plans.
- Equity—This principle is “about balancing the needs of the key stakeholders: the employees, the customers, and the investors. In many companies, it’s also the community and suppliers.”
- Competency—“Competency means continuous improvement personally, professionally, and organizationally.”
The article includes a discussion of Donnelly, the auto mirror maker that has had a Scanlon Plan for over 50 years. The discussion links Donnelly’s usage of the Scanlon plan to its early implementation of Lean and its usage of Hoshin Planning.
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“The Four Things a Service Business Must Get Right”
Harvard Business Review
April 2008, pp. 70-80
The author presents a “service model” that posits the significance of integrating four different elements—“it is their effective integration of the elements that stands out more than the cleverness of any element in isolation”.
The four elements are:
- The Offering—“Whereas product designers focus on the characteristics buyers will value, service designers do better to focus on the experiences customers want to have…To create a successful service offering, managers need to determine which attributes to target for excellence and which to target for inferior performance. These choices should be heavily informed by the needs of customers. Managers should discover the relative importance customers place on attributes and then match the investment in excellence with those priorities.”
- The Funding Mechanism—This can take four basic forms:
- Charge the customer in a palatable way
- Create a win-win between operational savings and value-added services
- Spend now to save later
- Have the customer do the work
- The Employee Management System—The successful service company needs to explicitly connect customers’ service preferences with their employee management approaches. The author recommends that designing a well-integrated employee management system starts with asking two questions: What makes our employees reasonably able to achieve excellence? And what makes our employees reasonably motivated to achieve excellence? A service business that wants to maintain a competitive cost structure will probably need to compromise on either excellence in employee aptitude or in employee attitude.
- The Customer Management System—Again, the important thing is to manage customers in a manner that is consistent with the service attributes the company has chosen to emphasize. The key questions to ask are:
- Which customers are you focusing on?
- Which customer behaviors do you want?
- Which techniques will most effectively influence customer behavior?
The final part of this article emphasizes the author’s perspective on sustaining growth in service companies. The common thread in continuing success is the capacity to become “multi-focused”. This means pursuing “multiple service niches with optimized service models—each designed to achieve excellence on some dimensions at the expense of inferior performance on others.” Shared services often provide the economies of scale to allow the company to succeed with various service models in different niches.
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“Engaging the Disengaged”
HR Magazine
April, 2008, pp. 109-112
Studies indicate that only 20-30% of employees in a typical organization are actively engaged and willing to give their best efforts. The author of this article discuses five basic forces that affect this in times of change.
- Connecting—“Where there is no [feeling of organizational] connection, people disengage and withhold discretionary effort. Creating experiences that allow employees to build relationships is mostly about the two-way sharing of ideas, facts, and feelings…During change initiatives, communicate face to face with your people at least twice as much as you do when you are managing the status quo.
- Learning—“A culture of learning needs to permeate formal and informal learning systems. This happens most effectively when you embed learning into the daily work flow.”
- Envisioning—“The most highly engaged employees have two visions: a personal vision that creates a portrait of who and what they will become, and an organizational vision that outlines a compelling picture of where the organization tries to go.”
- Earning—“Organizations with high employee engagement levels normally provide competitive compensation packages and opportunities for top performers to accelerate earnings.”
- Contributing—“To build engagement through contribution, give your people specific and important work assignments that can be accomplished in a reasonable time frame.”
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“Leadership is Critical to Lean”
Manufacturing Engineering
March 2008, pp. 145-151
Norm Bodek was one of the early popularizers of Lean manufacturing through his translation and publication of books by Japanese proponents of Lean manufacturing. Arguing in this article that Lean requires leaders instead of just managers, Bodek displays a list of 54 differences he has noted between a manager and a leader. He selects several of these 54 to focus upon, and he uses examples from Toyota to illustrate these points:
- Leaders exhibit independent thinking—Taiichi Ohno of Toyota “would encourage all of his managers to only ask workers what to do, not tell them.
- Leaders eliminate waste and show respect—“You show people your respect by continually developing them, continually challenging them to be better on the job, and allowing them to fully participate in identifying and solving problems.”
- Leaders praise others.
- Leaders use checklists—“if we want to be perfect in what we and others do in our organizations, then it is a must to properly use checklists.”
- Leaders overcome resistance—“A leader recognizes that there will always be resistance to change, but knows how to overcome that resistance and move on, while a manager just finds excuses not to change.”
- Leaders encourage ideas form workers—“It is a leader’s job to get as many creative ideas as possible from all workers.”
- Leaders encourage personal growth—“People at Toyota submit their personal growth plans for the year, and then meet with their supervisor every three months to review their needs and progress.”
- Leaders don’t fear mistakes—“A leader is aware that everyone makes mistakes, and that people really learn from their mistakes.”
- Leaders use sayings to encourage—“These are words that inspire people to rise to their greatness.”
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“Are You a Vigilant Leader?”
MIT Sloan Management Review
Spring 2008, pp. 43-51
This article is based on survey data that was collected from 119 global companies in order to examine their “need and capacity for peripheral vision.” Vigilance by leaders can avoid disastrous results that can come from being overly-focused internally on operational aspects. The three most important qualities of vigilance identified in the article are:
- External Focus: Openness to Diverse Perspectives—Curiosity and focus beyond the immediate are key aspects of this quality of vigilant leaders. It is important to foster networks and create systematic methods (such as formal “paranoia detectors” and “search parties”) to detect significant threats and “faint stirrings.”
- Strategic Foresight: Probing for Second-Order Effects—“Vigilant leaders are imaginative in recognizing the implications of new signals from the periphery.” Leaders should also create initiatives that foster deeper thinking and challenge managers to generate new opportunities and explore their implications.
- Enabling Exploration: Creating a Culture of Discovery—Vigilant leaders need to create enough slack that employees can explore areas outside of their main focus. Leaders can hire and promote people that are naturally more vigilant and broadly focused. Leaders can educate employees in critical and innovative thinking skills. Leaders can also ask deeper and broader questions to stimulate the curiosity and vigilance of others.
The article also describes a systematic program at General Electric that is very similar to the purpose of creating vigilant leaders. This program is called the Leadership Innovation and Growth Program.
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Who's Afraid of a D.O.E.?
Just the thought of undertaking a designed experiment strikes fear in the heart of many of our clients’ novice green belts and black belts. But conducting a designed experiment can be quite a lot of fun. Dr. Douglas Montgomery of Arizona State University strongly recommends a seven step process to conduct a designed experiment:
- Complete a problem statement – clearly define the problem that you seek to solve.
- Choose the response variable (Y) – determine the outcome that you will measure.
- Choose the factors (Xs), levels and ranges. – identify and set your input variables.
- Choose the experimental design – determine which design best suits the nature of your experiment.
- Conduct the experiment – the fun part, execute your design!
- Perform a statistical analysis of your experimental results – generally an ANOVA an analysis of residuals.
- State your conclusions and make recommendations – tell us what you learned.
The experiment will answer the question, “I wonder what happens to Y if I systematically vary X1, X2, X3, etc”. The problem statement indicates why you are interested in knowing the effects of the Xs on the Y. The response variable must be something that you can measure effectively. It is important to get a handle on knowing how you will measure your response variable before you proceed with the experiment. Determine which factors will have a measurable effect on your response variable and select the levels to set the response variables. Generally a high level and a low level will be selected for each factor.
Deciding on the number of factors to experiment on will help determine the experimental design. If you are not sure of the effect that your input variables will have on your response variables, or if you have a large number of factors to consider, then you will most likely want to run a factorial or fractional factorial screening experiment. If you have previously determined the characteristics of your system and want to optimize your response variable then you should consider a response surface or mixture design. Statistical software packages such as Minitab, JMP, SAS, or Design Expert, greatly simplify the process of running a D.O.E. Once you determine your experimental design you enter the input and response variable information and the computer program will generate your experimental design matrix which then runs in random order.
It is best to personally monitor the experiment as it is run to ensure that it is run properly. Once you have gathered the response data, it’s time to analyze the experiment. Once again, statistical software packages greatly simplify this step. Most software packages allow you to select effects by viewing a normal plot and highlighting the points furthest away from normal – this will select the terms in your model. The main tool of the analysis will be an ANOVA of the experimental results. A low p value is the indicator of a significant response variable. You further refine your model by eliminating non-significant effects from the model. At any rate you will know what happens to Y when you systematically vary your X’s.
Next, you check residuals for any patterns that might indicate the presence of any effects that you have not included in your model. Once you are sure that there are no residual effects to be concerned about, use graphical analysis to see the effects of the changes made to the input variables on the response variable. Finally, state the conclusions of your experiment and make recommendations either on which input variables or interactions of input variables have the biggest effect on your response variable, or the best settings for the input variables to optimize the response variable.
Still afraid? Prepare yourself by lining up a software package or black belt expert and stand by for the next Quick when we will give some great D.O.E. examples. Too impatient? Email us and we will send our white paper of D.O.E.’s free of charge.
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