Understanding Control in Business: Going Beyond Rules and Punishments

Introduction:

[Reading Time: 6 minutes. Difficulty: Intermediate].

In business, control is often seen as a way to ensure that results align with our expectations. Many businesses rely on a combination of rules, targets, rewards, punishments, and other motivational techniques to try to maintain control over their results.

There is a different kind of control. However, this approach is frequently misunderstood due to its name: Statistical Process Control.  Dr. Walter A. Shewhart introduced it in the 1930s, and it has made the great advances in the mass production of high-quality consumer technology possible.

One is based on the false idea that we can control results. The other, Statistical Process Control, stands on the surprising assertion that results are the “result” of something, and cannot be controlled directly. The process controls the result. To paraphrase Dune, “who controls the process, controls the spice!” 

Recognizing Our Limits

Control doesn't mean we have complete power over everything. Sometimes, factors beyond our control can affect the outcomes. When tackling complex, real-world issues, it's advisable to approach them with humility. We need to find ways to improve what we can control while being mindful of the things we can't.

In this article, we will explore CONTROL in everyday language.  We will explain why statistical thinking is a valuable tool for small non-technical businesses, and we will avoid using words like statistical thinking as much as possible.

An Example

A small factory was having trouble sending copies of the current invoices to the main office. Management blamed the employees, set a clear deadline for when they were to be completed and sent. In addition, they threatened the job of the office manager. This led to increased pressure on everyone and increased infighting between those who had to use the combination fax/scanner/printer they shared.

I suggested to the owner that before blaming the people, let's look at the process. A manager and some workers drew a layout of the office on paper, then traced where people went, for 20 minutes. A big black blotch appeared on everyone’s drawings, in front of the combination scanner and printer. All of these black lines converged where people stood waiting their turn to use the scanner/copier/ printer. 

They analyzed and added up that four hours per week of paid time was spent for each office worker using the scanner in waiting, accomplishing nothing. Collectively, it added up, and clearly explained the delay in sending the invoices. Hours per Week  

• 4 hours waiting         
• 6 employees
• 24 Total H per Week wasted   
• 1248 Hours Total per Year

More than the cost of a half-time employee, year-round, was wasted on waiting, (Real: How a small Company quadrupled profits during a recession Simply Looking, Dan Strongin, 2012. Page 103.)

Setting a deadline, blaming, and scaring had not worked for more than a year since the general manager, under pressure to cut costs, had bought the all-in-one printer to save money. Did it? 

The misunderstanding comes from the word “Control.” Can we control the natural world? Shewhart’s approach is about being aware of how a process should normally behave and acting when it goes off track by finding and addressing the cause. Trying to improve unpredictable results is like whistling into the wind. How will you know if it is an improvement?

Management “designs and implements” the process. The process behavior, in turn, delivers the result. Control that is one or two stages removed from the result. It is a serious misunderstanding that holds a significant number of people, businesses, and industries back from reaping the benefits of what was discovered in 1930. Not to mention an army of consultants competing to make it look more statistical than it needs to be for most businesses. (And using all kinds of jargon)

The “control” in statistical control means predictable. The catch is that a process can be IN control, predictable, but the results may not be what is needed.  Like I mentioned, a manager has only second or third hand control. It is a bit like navigating a boat in a fast-moving river.

Rather than make rules, motivate and dole out punishment, wasting energy and other more tangible resources, the way to get the results required is to innovate and improve the process.

Real Control means Predictable Results

Statistical control, as introduced by Dr. Shewhart, is the idea that processes' behavior can be understood by observing results over time. When results fall within a predictable range for a particular process, we can make more informed decisions, based on those dependable results. On the other hand, when results become chaotic and unpredictable, it indicates that the process is out of ¨control¨. In such cases, it is crucial to stop the process, identify the cause, and take steps to restore the process to its predictable behavior. 

How can you know if you have improved when all you have is unpredictable results?

Understanding Statistical Thinking

Statistical thinking, despite its name, does not require an in-depth understanding of statistical mathematics. Instead, it recognizes that it is the process itself that controls the results, and that:

1. All work happens in a system of interconnected processes: In any business, different processes are interconnected, and they affect one another.
2. Variation exists in all processes: No process is perfect, and there will always be some natural variation in the results.
3. Understanding and reducing variation are crucial for improvement: To get better results, we need to understand why there's variation and work on reducing it. (The Certified Manager of Quality/Organizational Excellence Handbook, Third Edition. 2012, ASQ press. Page 626)

Roles and Responsibilities

When management does not interact directly with the work floor, they need a sense of control. The larger the organization, the more layers there are between top management and the work floor, the greater the insecurity and the perceived need for control.

In the context of statistical thinking, control is not about micromanaging or imposing rules on workers. Instead, it involves recognizing that different stakeholders have distinct roles and responsibilities. What is the role of management in a healthy organization, if it is not to police the workers? 

The Role of Management:

Management plays a vital role in the pursuit of predictability within a business. Their responsibilities include:

• Designing and Innovating Processes: Management is responsible for creating efficient and effective processes that lead to predictable results. They need to analyze and understand the intricacies of the business operations to design systems that work smoothly.
• Implementing Improvements: Managers need to take the initiative to implement changes and improvements to the processes. They should identify areas of potential variation and work towards minimizing them, thus enhancing predictability.
• Providing Resources and Support: Management is responsible for providing the necessary resources, such as equipment, technology, and training to support the implementation of improved processes. They should ensure that workers have the tools they must have to carry out their tasks effectively.
• Monitoring and Feedback: Managers should keep an eye on the overall performance of the company.

The Role of Workers:

Workers also play a crucial role in achieving predictability within a business. Their responsibilities include:

• Monitoring Process Performance: Workers are responsible for carefully watching the process results. If the outcomes are expected and predictable, they should just let the process continue, while staying alert for any results that go beyond what was expected.
• Problem Identification and Resolution: Workers should actively participate in problem-solving efforts. When a process deviates from the predictable range, workers should contribute by investigating and identifying the root causes of the unpredictability. Perhaps it is an issue that needs correcting, or a trend signaling fundamental change, like a new supplier or product, or seasonal changes. 
• Continuous Innovation and Improvement: Worker insights and experience are invaluable for finding more effective solutions. They should actively seek ways to be more effective, and suggest process enhancements. But, as everything in a company touches everything else, changes to the process itself can only be addressed together with management, innovating and improving it. Only management has the control of the resources necessary, like changing machines, or workflow, and are better positioned to understand how a change may affect other people and processes in the organization.

In summary, management focuses on designing, improving, and providing resources, while workers play a crucial role in monitoring, reporting, problem-solving, and contributing to continuous improvement efforts. Both management and workers need to collaborate and work together to achieve and maintain predictability within the business.

Real Control: Shifting the Focus

The concept of real control, as advocated by Dr. Shewhart, lies in making processes deliver predictable results that meet customer needs and legal requirements. Instead of trying to control results directly or setting arbitrary targets, businesses should concentrate on innovating and improving for dependable results. 

Conclusion:

In the pursuit of control within a business, understand process behavior, and what your processes can and cannot deliver by observing results over time. Adopting this mindset, businesses can make real economic progress, rather than rely on targets, rules, and punishments that do not work for long and waste precious resources.  In this way, control becomes a collaborative effort between management and workers, with each playing a crucial role in maintaining dependable results, improving the quality of those results, and lowering costs through innovation and improvement. That is why Dr. Shewhart called his groundbreaking book The Economic Control of Quality of Manufactured Product.