CASE STUDY
No Silver Bullet
HOW A FOOD PROCESSING PLANT SUSTAINED RESULTS BY BLENDING IMPROVEMENT METHODS
By Francisco A. Hernandez Jr., Booz Allen Hamilton
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side from the organizational improvement trends often written about, I’ve been discovering an underworld of clients whose interests go beyond the trendy, fixed methods. The basis of their request is simple: “Fix the problem, use any approach you’ve got, but only use the tools we have. And most important, make it stick.” This is a rather common request from clients. But when we find ourselves in lean economic times, we find clients with a sense of urgency to minimize additional expenditures (“use only the tools we have”) and to go beyond the savings target (“make it stick”). I often joke that cutting costs for an organization is a lot like losing weight. Many can take the pounds off, but keeping them off is a whole different story. It is a dilemma that is seen far too often in cost reduction initiatives. Changes are made, savings targets are met, and after some time, an organization reverts back to old, costly behaviors. In our current economic environment, there is the pressure to take off the pounds, but there is even more pressure to keep them off. So how do we do it? We start by going beyond our usual approaches and methods. After all, there is no silver bullet for improvement. I often refer to an example of a project in a food processing plant in which a group of practitioners went beyond the traditional tr aditional lean approach and a good training program to minimize waste, cut costs and sustain results. A plant in need of help
The client asked us to help the plant get ge t the most out of its raw product. The Th e plant needed to minimize waste and squeeze out as much finished product as possible within its production cycle to meet demand. In addition, the organization’s capital expenditure plan already had been set. In short, all recommended changes had to be made within the confines of its current productive capability. The layout of the plant consisted of three processing lines. Lines 1 and 2 were always cycled to make the same product product type, while line 3 used the raw material scrap from lines 1 and 2 to make a different variety of its product offering. The plant was highly automated and fairly lean with respect to headcount and overhead. Total production of the processing lines was about 2 million pounds of finished product per shift. The theoretical production maximum was about 3 million pounds. The project goal was to minimize waste and increase production by 25%, or 2.5 million pounds a shift. The project team was made up of several consultants from various backgrounds, each with their own style and approach. When embarking on their operational assessment, the team analyzed the plant’s operational
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No Silver Bullet
processes, various waste points, the plant’s management operating system (MOS) and the behaviors of the staff responsible for the production. The current state
The current state analysis consisted of the development of various process maps and the identification of improvement opportunities. We used cause and effect diagrams to better understand problems and their causes, and we implemented the five whys technique to get to the root cause. In addition to our standard tools, there were two assessment components that were particularly different about this analysis. The first was the holistic analysis of the plant’s MOS. The second was the assessment of personnel behaviors from the frontline management and staff. MOS assessment
A MOS can be defined as, “a compilation of activity, communication, controls and tools used to achieve organizational goals and objectives.” 1 Figure 1 shows the information and workflow that comprises a MOS. The five key functions of a MOS are forecasting, plan-
ning, scheduling, monitoring and reporting. The MOS assessment consisted of a gap analysis of: • The availability of tools that fall into the key functions. • The use of these tools. • The effectiveness of the tools. To illustrate the MOS analysis, let’s look at the assessment of the monitoring functions at the plant. In assessing the monitoring function, the project team evaluated the plant production monitoring tool. The project team found that the tool provided hourly productivity in pounds with a lag of 15 minutes. This means that at 9:15 a.m., a production lead would know how much was produced between 8 and 9 a.m. The monitoring tool was far from real time, but useful in tracking production volume. Naturally, the recommendations were made to consider future enhancements to the tool, but the client had asked to use the tools already in place. The second component of the monitoring function assessment was use of the tool. The project team found that production leads were actively using the tool to monitor their production volumes. As far as the assessment was concerned, it was determined that monitoring tools did exist and managers were using it.
Figure 1. Components of a management operating system Forecasting
Scheduling
Assigning and executing
Monitoring
Annual sales forecast
Operating reports
Annual production forecast
Problem resolution process
12-week production forecast
4-week production schedule
Weekly, daily production schedule
Knowledge repository
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Reporting
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Hourly production plan and monitoring
Production dashboard
No Silver Bullet
The open question was, “Is the tool effective?” The answer was no. The tool did not provide the production leads with insight into hourly targets. So, as a manager having to produce 2 million pounds by the end of a shift, you may not realize that production was behind schedule until halfway through the shift. By that time, catching up would be impossible due to capacity constraints. Seasoned production managers will argue this is Production 101. However, in an environment in which the production floor is the picking field for talent and the starting grounds for new hires, the plant is left with junior production leads running the show. Therefore, it is important to lend more of the right tools to junior associates so they can quickly close the learning curve gap and meet production targets. The MOS assessment went beyond controls. The goal of the assessment was to effectively track a number from a sales forecast to the number of units produced by hour, and back out to quarterly reports and onward—a true analysis tool for sales and operations planning. The assessment also measured the capability of each tool to track performance to plan. To be qualified as an effective tool, the tool must provide guidance on a target, actual production and a variance if applicable. This provides the production leads with the capability to employ real-time corrective action when needed. Finally, the assessment measured the effective use of the tool by measuring behavior. It questioned how effectively the production leads and operators used the tool. Behavioral assessment
The project team conducted a separate assessment of personnel behaviors. On one end, the project team observed frontline operator behavior. The operators were observed to determine the effectiveness of their job performance and training. Key questions asked were: • How effective are operators with the tools pro vided? • How well are the operators employing problem resolution skills? • How much time are operators spending on nonvalue-added work, and what are the causes? The project team was not looking for scapegoats. It was seeking to understand the frontline operator work behaviors to help get them better engaged in
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Figure 2. The missing element Full savings potential is achieved when process improvements, behaviors, and systems and tools align. Process improvements
Behaviors
Systems and tools
productive, value-added work and help facilitate their job function. For example, the project team would analyze the amount of time a worker idly waited for work. If a boxing operator was idle waiting for product, the project team captured the time lost and identified potential solutions to maximize production during similar gaps. An example of a downtime solution included the stocking of packaging material to prep the work area and avoid line stoppages due to shortages of the staged material. In addition, the project team studied the worker time in motion to determine lost time in work areas. The project team helped determine whether operators had all the necessary tools and job aids to effectively complete their tasks. Lastly, the team would also determine the need for training based on the workers’ problem-resolution capability. For example, machinists were often found fixing machine jams. They would clear the jam—until it would jam again. Problem solving and root cause training could have prepared the machinists to fix the issue versus addressing the symptoms. With respect to the management behaviors, team leads were assessed on their ability to manage and direct their teams. The project team observed the production leads on their ability to provide clear directions and follow-up on assignments—key management traits that often are taken for granted. Production leads also were assessed on their problemsolving skills.
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No Silver Bullet
packaging could not keep up with the production flow, spillages could occur, resulting in finished product waste. The assessment was comprehensive and detailed, Another common failure was a shortage of staged and it helped identify a number of opportunities for packing material. Both scenarios could cause line improvements: stoppages and the boxing of finished product in large Opportunity one: Production leads had real-time containers due to overflow. This was referred to as monitoring tools (the team was able to monitor “catching totes.” By implementing similar MOS trackpounds per hour); however, production scheduling ing tools, the packaging lines were able to maintain tools failed to provide clear hourly targets needed to a performance and pace that was balanced with the meet demand. The assessment of the MOS allowed finished product feed. The tools facilitated communithe project team to improve on the organization’s cation between the upstream and downstream groups, scheduling approach. Schedulers were given planning and also allowed for quick decisions and direction on tools that match and balance production capacity. managing variances in the hourly plans. Further, the tools developed for the production leads Opportunity three: As previously mentioned, probroke down the production run needs to hourly tarduction overflows often resulted in spillage or catchgets that were easy to follow and track. This allowed ing totes. Monitoring and inventory management for corrective action earlier in the production cycle tools that were installed allowed production leads to versus finding out at the end of the day that the prodecide how to manage the production variance. They duction was short or overrun. also allowed management to plan and stage totes Opportunity two: Production shortages and overfor blending back. Blending back was the process of ages also affected downstream packaging lines. If taking totes from production overflows and using them to Figure 3. Waterfall vs. agile project schedules supplement production feeds whe never necessary. It was Waterfall project schedule found that the overflow invenWeek 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 tory often would go to waste because of expiration. Poor Define project requirements planning on blending back finished product for packaging caused much of the inventory Design project solution to expire. Monitoring tools, the Develop project solution implementation of problemresolution processes and the elimination of waste were Test project solution ◆ among the key improvements sought by the project team to meet business objectives. Agile project schedule Responsible, accountable, Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 consulted, informed (RACI) matrixes also were developed Sprint to ensure that all players knew ◆ their role in the new way of Sprint doing business. ◆ Based on baseline performances (2 million pounds per Sprint shift), the expected projected ◆ gain in productivity was about Sprint 25% (2.5 million pounds per shift). The production leads ◆ Findings and solutions
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No Silver Bullet
AFTER
THE FIRST COUPLE OF WEEKS, WE NOTED THE PRODUCTION PERFORMANCE
WAS INCONSISTENT ACROSS THE LINES, AND ALTHOUGH OVERALL PRODUCTIVITY WAS UP, WE WERE FALLING SHORT OF TARGET GOALS.
and operating team members were trained throughout the project on the process improvements made, the tools developed and the pending changes to be installed. Production leads and operators were all part of the change journey and were key developers of the tools designed.
together a team of what we referred to as installation specialists (IS). The goal was to leverage the ISs to support, educate and instill in the production team the behaviors and best practices needed to achieve the targets. The ISs were primarily selected due to their ability to influence. We initially sought the support from various plant leaders, but found that regardless of their title, they may not have been the right people for the job. We needed people who understood the importance of change, but more importantly, we needed people who treated employees as people. We selected folks that were respected and well liked across the production lines, and frankly, had a natural ability to sell. The role of an IS was to help coach the production leads and frontline associates to adopt and model the behaviors needed to support the improvement changes. This included gemba walks, which is “an activity that takes management to the front lines to look for waste and opportunities,”2 as well as active production monitoring and asking the five whys where variance existed. The approach taken by the ISs was borrowed from the world of software development, a variant of agile known as scrum. Scrum is a software development
The future state falls short
The installation was celebrated, and after just a few days many production gains were made. But we were falling short. After the first couple of weeks, we noted the production performance was inconsistent across the lines, and although overall productivity was up, we were falling short of target goals. The project team concluded we were falling short in creating the habit of success. Due to the client demand that we use only the resources it had, we had to rely on manual and visual tools to monitor production. As it turns out, the excitement of the “new thing” wore off, resulting in inconsistent performance. We had the processes and the tools, but we were missing the right behaviors. Figure 2 (p. 19) illustrates the missing element we identified that was preventing us from achieving full savings potential. In response, our project team decided to pull Figure 4.
Gemba dashboard Quality daily schedule control board
Shift:
Line:
Date:
Unit of measure
Shift hour 1
Shift hour 2
Shift hour 3
Shift hour 4
Shift hour 5
Shift hour 6
Shift hour 7
Shift hour 8
Shift summary
Plan Line 4
Actual Variance Plan
Lineflow
Number
Actual Variance Plan
Line 4
Actual Variance
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No Silver Bullet
TOOLS
SUCH AS GEMBA DASHBOARDS WERE CREATED TO KEEP PRODUCTION
TEAMS MINDFUL OF THEIR PERFORMANCE TO PLAN.
approach based on iterative and incremental development. Scrum is different than a typical waterfall development approach because it is focused on an iterative approach to development as opposed to a phased approach. See Figure 3 (p. 20) to compare a waterfall project schedule and an agile project schedule. A typical waterfall schedule requires the completion of one phase before moving on to the next. The disadvantage is that after a phase is complete, you can’t go back to it. In scrum testing and feedback, it is iterative on the development of features. It allows for coursecorrection. Ultimately, the intent of the implemented MOS and required behaviors is to course-correct production before falling behind in achieving production targets. Using the scrum tool of iterative meetings and adapting it to the production environment, the ISs met hourly with the production leads on the shop floor to discuss production targets. The ISs coached the leads on identifying the root cause of any variance in their hourly production plans. Each production lead was assigned an IS, and for several weeks, the ISs met with the leads to review dashboards on the work floor and discuss performance against hourly plans. The purpose of the reviews was to go over the production and identify corrective action needed on target variances. The r epetitive coaching created a habit of the practice and instilled in the leads a practical understanding of the tools implemented that lent to a more effective adoption of change. Figure 4 (p. 21) shows an example of a gemba dashboard. Tools such as this were created to keep production teams mindful of their performance to plan. Production leads and frontline associates had a role in monitoring production and in asking the question, “Why?” when a variance presented itself.
to scale back the hourly reviews to once a day. The production leads had established the practice of the short-interval reviews and production was consistently hitting 2.5 million pounds. After the success in our first plant, the IS team and our project team were given approval to expand the project efforts across the client’s other plants. Later, some of our consultants were hired into the organization, and the ISs were given permanent roles to repeat the successes internally across the client’s various plants and operations. The team eventually became its own arm in the process improvement division of the company. Some team members were actually moving to implement the practices in the administrative areas of the organization. The team and I have debated what truly drove the savings. Whether the key was the changes to the MOS, modified behaviors or process improvements, one thing is certain: Without the blending of methods, the right tools and the right people, we would have never been able to deploy a genuinely holistic solution. More importantly, we would have never lived up to our promise of 25% gains. REFERENCES
1. Dennis Stevenson, “Management Operating System,” Toolbox.com, June 12, 2008, http://it.toolbox.com/wiki/index.php/Management_ Operating_System (case sensitive). 2. Wikipedia, “Gemba ,” http://en.wikipedia.org/wiki/Gemba (case sensitive).
EDITOR’S NOTE
The work discussed in this article was completed while the author was employed at a different organization before joining Booz Allen Hamilton.
Sustaining results
During the period of about four weeks, we started noticing a behavioral shift on the production floor. The teams started taking full ownership of the tools and processes implemented, and the IS team was able
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