In the United States, the US Bureau of Labor Statistics is the most important source of productivity statistics, at least those that pertain to specific industries. If you take even a quick look at the Bureau’s website, you’ll probably notice two things:
If you dig a bit deeper through BLS’s tables, you’ll notice another important thing:
When you start unpacking these three insights, you’ll get to the major issues you can come across when measuring productivity in your business.
Labor productivity is the ratio between the products or services made and the labor hours that go into making them. It’s a fairly straightforward metric that’s widely used, but it has one significant and obvious drawback — it relies on labor for input.
Labor productivity might work well for businesses where labor is the most important item on the list of inputs. For a business where labor isn’t the major component of input, labor productivity doesn’t make much sense, as it tracks only one factor, and not the most important one at that.
The other problem with industry-wide labor productivity is that work processes can vary significantly from one business to another. While labor productivity in itself isn’t always the most reliable measurement, using the industry-wide labor productivity measurement to compare your business can be even more unreliable, although not completely useless.
Measuring the change of productivity is very useful when businesses want to track and gauge new practices or work processes they’ve established, or when they want to see how external circumstances influenced them. But in order to know how much productivity has changed, businesses need to have something to perform the “before and after” comparison, and that for those reasons indexes as used.
But to establish an index, a business would need to set a reference value, a baseline or a benchmark of a sort that will be used in further calculations. The US Bureau of Labor Statistics, for example, uses the labor productivity as it was in 2007 as their benchmark.
They pretty much declared that the ratio between output and input in 2007 will be awarded the number 100, and based on that you can see, for example, that in nine years since then the productivity of the electronic instruments industry rose by almost 10%.
And even when businesses manage to establish a good baseline, there’s still a lingering question about the efficiency of using quantifiable productivity measurements without accounting for quality.
Not all processes can be best described using numbers, and not all productivity measurement methods rely on them.
No matter how difficult and complicated it might get, measuring and comparing productivity is still too valuable to business to be disregarded.
A better approach to measuring productivity would have to deal with the single-factor productivity problem, the baseline/benchmark problem, and the problem with measuring things that aren’t easily quantifiable.
But it’s even more important for businesses to acknowledge that the best productivity measurements are those that give valuable insights that can be applied to specific businesses. Industry-wide measurements can serve a purpose, but they can skew a business’ view of its own work processes.
There are two different ways you can tackle the shortcomings of single-factor productivity measurements:
The problem with multi-factor productivity measurements is that they can be complicated to develop. A multi-factor measurement basically tries to include all the relevant inputs into the classic productivity formula. This can be difficult enough without the possibility that multiple outputs can also exist, especially in a large business which has many different departments.
Compartmentalization can be helpful here. Instead of creating a master productivity measurement which would take into account all of the activities that occur in a business, productivity can instead be measured for each sector or team.
So, for example, the marketing team would have its own productivity measurements, the sales team its own, the customer support team own, and so on.
Further segmentation can also lead to using multiple single-factor measurements to get a multi-factor impression of productivity.
So instead one, big, complicated formula, businesses would employ several smaller formulas and then combine those results to get an accurate depiction of a team’s productivity from several different standpoints.
Depending on the business’ proclivity towards monitoring and storing performance data, setting up baselines can be more or less difficult. A baseline should be the productivity measurement of an average team during a set period of time, using the average amount of resources to produce average results.
With more data, it would be easier to accurately calculate an average. If the data is lacking, the business is pretty much left to the data they have or can capture in the near future. Having a baseline is always better than not having one.
Benchmarks are productivity measurements which are used to compare a business’ productivity. There are several measurements that can be used as a benchmark:
While industry-wide productivity measurements might be the easiest to find, for the reasons already explained businesses should be careful when using them.
There are two types of tasks in any work environment — tangible and intangible. The former has a clear product of performing the task, such as products created by a single machine on a factory floor.
Intangible tasks don’t have a clear and material output. Service industries are especially susceptible to the lack of tangible tasks, making it hard to measure the output as well as determine how actions relate to it.
While it might be more difficult to identify how the output of a graphic designer, for example, relates to its productivity, business should still find a way to do it.
Instead of focusing on the number of ideas a designed can produce in a workday, which would be treating the designer’s products as tangible when they are essentially not, combining client satisfaction and the amount of time it takes to create the final product would paint a clearer picture of the designer’s productivity.
This type of measurements which include opinions of relevant parties is very useful when gauging not only client satisfaction but also the productivity levels within teams.
Ideally, business would track and measure productivity for the whole business as well as for specific tasks, for the whole organization as well as separate team members.
Taking into account the human factor, the fact that productivity measurements can be confusing, and that some things can’t be efficiently measured can help with moving towards making productivity measurements into truly actionable metrics.