Why are productivity gains shrinking?

by: Taylor Milner

Does being more productive seem harder to you too?

If being more productive, or getting your team, group, company, or organization to be more productive seems harder these days, you are not alone.  Annual productivity improvement has slowed to about 1% from its most recent peak of almost 6% in the early 2000’s. 

Minus a spike in 2010, the last decade’s improvement has been pretty dismal at well less than 2%.This is particularly evident in the manufacturing sector summarized in the graph below

Labor Productivity Graph.png

In the next few pages, we are going to explore two questions:

  • Why should you care about productivity growth?
  • What are the causes for the slow down?

In a subsequent article, we will explore what you can do to increase the rate of productivity growth within your organization.

 

Why should you care?

At the most macro level, productivity improvement drives better quality of life for all of us.  It makes products less expensive and more accessible for more people.  It also eliminates the need for resources to do certain work and frees them to do other, often more valuable and fulfilling tasks.

One of the great examples of productivity improvement has come from agriculture.  Agriculture in the early 1800’s required about 80% of the entire US workforce.  Today it is well less than 10%.  At times, this has caused dislocations in the agricultural workforce, yet it has also freed 70% of the entire US workforce to focus on other endeavors that improve the overall quality of life of the broader society.  We would not have seen the recent advances in healthcare, technology, or education if 80% of us were still toiling in the fields every day.

Likewise, if it takes less labor to produce something, more of that product or service can be created at a lower cost making in more accessible to more people.  Continuing our agricultural example from above, the labor cost component of agricultural products has come down drastically, making food on average less expensive and therefore more available to more people.

Televisions are another great example.  How many televisions did you have in your house growing up?  Odds are it is less than you have today.  In the late 70’s and early 80’s, the average US household owned about 1.5 televisions.  In 2010 it was almost 3 televisions per household.  Much of this was driven by affordability.  As a note, the number of televisions per household is now declining as other devices are being used as “televisions.”

From a business perspective, productivity improvements allow us to do more with less.  In much of manufacturing, productivity improvements are expected to cover general inflation.  As a leader, you are expected to drive 2-3% productivity improvement each year to cover the increasing costs.  They also allow us to free up capital that can be used in other ways, investing in new equipment that will further improve productivity for example.

Compound the above example, and you can see how productivity plays a role in company earnings, the broader stock market, and the overall growth of the economy.

In short, improving productivity has significant and broad impact on the overall quality of life of our society.  It is so important that when it slows, as it has over the last two decades, many people try to answer “why?”

 

What is causing the slowdown?

Even with many people looking into why productivity has slowed, no one has a clear answer.  There is lots of speculation, hypothesizing, guessing, and blaming.  Here is a quick summary of some of the common themes:

  • The technological advances and improvement strategies that drove the last big gains have run their course and are no longer generating the returns they did when first implemented.  Nothing new has replaced them.  I have seen this first hand where the popular improvement methodologies of Six Sigma and Lean are now pushing 20 years old in most organizations.  Improvement is still important, but the urgency to find the next big improvements seems to be much less.
  • Capital investment slowed significantly with the financial crisis and access to capital.  There is a natural lag between capital investment and productivity improvements, which we are seeing today.  This theory is augmented with one that capital investment is now picking up and productivity will bounce back.
  • We are not measuring productivity correctly.  This argument shows up in a number of places, so as easy as it is to dismiss it with, “if you don’t like the answer, discount the methodology,” there may be more to it.  This argument is also known to statisticians and economists as “measurement error.” Counting the output per hour worked for something like manufacturing is one thing, however, measuring the output of the services sector is another thing entirely. With the increase in technology and the service sector in recent years, this seems like a plausible explanation.
  • Finally there has been plenty of blame placed on excessive regulation, bail-outs, and accommodative monetary policy.  Workers have also been blamed with the theory that low unemployment has reduced the motivation to work hard.

 

My two cents

Given all of the speculation, I figure it does not hurt to add my own thoughts.  As I shared in the first bullet point above, there is not much new in the world of productivity improvement.  We hear a lot about AI, machine learning, and automation, but this is not yet mature enough to accelerate productivity.  There are more robots in manufacturing, but they are doing a lot of the same things they were doing 10 years ago.

I also do not see operations taking full advantage of their automation by designing their systems, lines, and plants around it rather than fitting automation into more traditional layouts.  As an example, even with automation, most “automated” operations still require human operators, whether to load raw materials, check for quality output, or fix the occasional equipment fault.  With a more thoughtful layout, a single operator can cover several pieces of automation if they are located in close proximity. But if automation is added to a more traditional “spread” layout, one operator may be required for each piece of automation.  The more operators we have, the lower the productivity gains we get from automation.

Finally, improvement methodologies such as Lean and Six Sigma were designed to mobilize the individuals within an organization to generate small improvements.  Leveraged over hundreds and thousands of employees, this would add up to a large improvement across the organization.  Over the course of these methodologies’ lifespans, two things have happened that have driven the slowing of productivity growth. 

First, fewer and fewer employees have been available to leverage as improvements in productivity have shrunk workforces.  This means there are fewer and fewer people driving improvement.  With fewer employees, each one needs to drive greater productivity improvement to keep pace.

Second, employees have run out of ideas, incentive, and energy to generate new ideas.  These methodologies have done a good job encouraging employees to submit productivity improving ideas.  After 20 years or so, these methodologies have just run their course as new ideas are fewer and harder to generate.  Companies either need to create a new incentive for productivity idea generation or adopt a new methodology for finding opportunities.

 

Conclusion

In short, productivity gains are likely shrinking because we are between macro phases of significant productivity gains.  The current technology we have to employ is not that much more advanced than what was employed to drive the last wave of improvements.  The next wave of technology is still a ways out from being broadly adopted.  Likewise, the productivity programs that harnessed broad organizational resources to drive improvements have run their course and the next programs have not yet taken shape.  All of this does not mean that you should resign yourself to waiting for the next wave of productivity improvements to come.  Instead, you will need to look at your operations differently than you have before.  I will tackle this in the next article; stay tuned.

 

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