The value-added fantasy: A strict focus on eliminating waste is not the best way to improve performance

The value-added fantasy is the perception that eliminating nonvalue-added activities will enable the most profitable performance for a supply chain. The reality is if companies truly want consistent performance improvement, they should focus on a practical, scientific approach for quantifying and controlling the elements of cycle times that drive performance.
By Edward S. Pound, Mark L. Spearman, Factory Physics November 17, 2007

Performance improvement strategies that revolve around the notion of reducing nonvalue-added activities are quite popular these days. Unfortunately for the multitude of manufacturers relying on them, these strategies are flawed.
The “value-added” focus is one of legions of corporate slogans and consulting initiatives—e.g., “one piece flow,” “eliminate waste,” “zero variability,” and “pull to demand.”
Why do these initiatives seldom live up to
In particular, the value-added fantasy is the perception that eliminating nonvalue-added activities will provide the most profitable performance for a supply chain.
The reality is if companiesd, objective, and predictive approach to improving profitability.
A value-added strategy may or may not lead to improved profitability. So why bet your career on something so risky?
You may be asking: If value-added strategies don’t really work, why are they so popular? To answer that, let’s first look at some typical definitions of value-added:


Some good things can result from value-added analysis. For instance, it typically shows that most of the time that
However, there are other problems with the value-added fantasy—particularly the notion that it addresses things customers care about.
In the vast majority of cases, assuming a company is not using slave labor or other unethical practices, the customer does not care what a company does in its processes. The customer makes a value statement with an exchange of money for goods or services at the time of purchase of a product or service. When buying gas for our cars, not once have we considered the value-added
How do you think the majority of your customers would respond to following multiple-choice
A. Customers prefer companies that have long set-up times.
B. Customers prefer companies that have short set-up times
C. Customers are not concerned about set-up times.
We believe the answer “C” would win hands down.
Since the vast majority of customers are not concerned about the activities that go on within a company’s production or service processes, having internal decisions about what customers consider to be value-added or nonvalue-added is an extremely subjective and often dysfunctional exercise.
Actually, since “value-added” is typically defined as a process step that changes form, fit, or function, the value-added steps are the ones that a company would need to do most effectively whether a customer knows about them or not. Calling these steps value-added is just a confounding classification and frequently leads to nonproductive discussions. For instance, try telling a highly skilled quality inspector that his job is nonvalue-added. The use of vague terms such as nonvalue-added leads to the creation of more vague terms—particularly the invention of the uninspirational necessary nonvalue-added .
We have suggested focusing on a practical, scientific approach to cycle time rather than using the value-added approach as a more reliable means of achieving consistent performance improvement. In some cases, value-added activities have been used as component of cycle time. But we would argue that even using value-added activities in this context is a flawed exercise.
For example, the statement, “Cycle Time = Value-added time + Nonvalue-added time + Necessary nonvalue added time,” does not provide useful information about where to address the most profitable efforts for improving performance. The statement
Cycle time here is used to mean the time a product takes to get through the manufacturing supply chain from raw materials to completed product. Other names for this term include throughput time, flow days, and dock to stock time. The division of cycle time into elements related to value-added steps provides no predictive control about what will happen to an organization’s financial performance if the various elements are addressed.
It is advisale to eliminate unproductive efforts fueled by subjective definitions, and control your operations’ performance using the practical science that describes the natural behavior of your operations.
A fundamental, comprehensive framework of the practical science governing manufacturing supply chains reveals that cycle time is composed of the following components:

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Now this is not as simple a list as value-added, nonvalue-added, and necessary nonvalue-added, but it is a much more powerful classification of the elements of cycle time.
Why? First, every item in the list can be described quantitatively and objectively, and the list completely describes the elements of cycle time. Second, because the description is quantitative and objective, its use provides predictive control over performance.
For example:
•ycle-time reduction without major capital expenditures.

Do not depend on the subjective “value-added” description of performance to drive performance of your organization. You might get good results, but then again, you might not. Drive your career progression and your company’s financial health through a solid understanding of the practical science governing your manufacturing supply chain logistics.
To get the best possible performance from your organization, understand and apply both the mechanics of cycle-time control and the scientific principles that provide predictive descriptions of the interactions between work-in-process, throughput, cycle time, and variability.
Edward S. Pound is COO of Factory Physics . Mark L. Spearman is the company’s president and CEO. Factory Physics is a management consulting company that provides a scientific framework, software support tools, and training to optimize performance of manufacturing supply chains.