Don’t hire brilliant people and tell them what to do; Measure what matters
Last week we discussed the problem of measuring productivity in general and arrived at a conclusion that some of the problem is the measurement frameworks themselves. What can you do about those? How do you measure measurement? Let’s find out!
Let’s start by exploring these measurements by industry sectors and we will explicitly not focus on technology companies.
Given that the service industry employs about 80 percent of the U.S. workforce, many organizations are focused on measuring employee productivity and improving it. Unlike the manufacturing sector, in which employee productivity can be measured by the number of items produced, in the service industry you need to know how the service was delivered, as well as the degree to which the service impacted the customer experience. The good news is that there are many ways to measure the productivity of employees in the service sector, and you can improve employee productivity with training and development activities.
The traditional employee productivity calculation equals total output divided by total input, for example, the number of cars (output) produced during a 12-hour shift (input) in a manufacturing plant. But for organizations in the service industry, a purely quantitative method of measuring employee productivity doesn’t work quite as well. In the service sector, the input (for example, decision-making, judgment) and output (customer experience, achievement of performance objectives, and so forth) may be harder to measure and are subject to variation from employee to employee.
Instead of focusing on the number of customers served or hours worked, an effective strategy for measuring employee productivity in the service industry takes into account a range of factors that will vary depending on the sector, company, or employee role.
Customer Satisfaction: A focus on quality outcomes rather than number of transactions often makes sense for service sector employees, because the service industry provides customer experiences rather than products. For example, a customer service representative’s patience, professionalism, and friendliness matters as much as the number of calls taken in the space of an hour.
Employee Engagement: According to research conducted by Gallup, teams with high employee engagement are 21 percent more productive than teams with lower engagement rates. While engagement is no guarantee of employee productivity, when employees are engaged and have the desire to perform at their best, they may be better positioned to do so than those who lack engagement.
Performance Against Goals: Productivity can be measured according to how successfully employees meet their performance goals. As an example, a salesperson has a goal to increase business from new clients by 10 percent. Business development productivity requires that salespeople deliver a high level of service to potential clients. The degree to which the employee meets the goal shows his or her level of business development productivity.
The following examples illustrate how the factors described above help with measuring employee productivity in different service sectors.
Transportation: Instead of focusing on the number of routes a train conductor completes each year, it would be more effective to measure the conductor’s productivity by the number of on-time arrivals or the length of time gone without a safety violation or accident. Strong marks in these areas also help build customer satisfaction and loyalty.
Food Service: The fast pace of many food service establishments requires engaged employees who want to provide excellent customer experiences. The productivity of waiters, chefs, and hostesses is not measured only by the number of customers served, but also the degree to which their engagement enables them to provide great food, courtesy, and a swift resolution to any customer complaints.
Merchandise Retailing: It’s true that dollars per sale and sales per employee matter when looking at the productivity of retail employees. However, as one study found, high engagement among retail employees not only increases their productivity, but also results in significant reductions in inventory shrinkage, waste, cash loss, and lost sales.
Healthcare: A quantitative measure of employee productivity for a hospital might be the number of patients seen by a nurse in the course of a workday. However, that might not adequately measure the nurse’s productivity if each patient didn’t receive proper care and attention. In an age when the patient experience is a critical component of a hospital’s competitive advantage, a more important measure of the nurse’s productivity would be the number of satisfied patients, which can be quantified with patient experience surveys.
Unfortunately, measuring a measurement problem is almost impossible. We do have some experience in adjusting for quality in both goods and services. If, for example, a new car is more reliable than the previous model, though otherwise indistinguishable, you can adjust for that. On paper the cost of roadside repairs would appear as a rise in GDP, whereas in reality our living standards do not increase at all when we are stranded by a broken-down car.
You can make similar adjustments for improvements in quality of services, though this is tricky too. For example, if thanks to advances in treatment you can cure an illness with medication rather than an operation, the lower cost appears as a decline in GDP but, of course, it is a much better outcome not to have to go through the trauma of the op. One of the oddities in UK productivity statistics is that when banks sprayed loans around that never got repaid, that appeared as bankers having high productivity. If, on the other hand, they make fewer loans but ones that are repaid, then their productivity goes down. One of the UK productivity problems results from having a relatively smaller financial services sector, even if the sector is qualitatively better.
The trouble is that in the past there has at least been something going through the national accounts – some goods or some services are duly recorded – but now many activities are not recorded at all. For example, when we use Google Maps to navigate round an unfamiliar city, nothing appears in GDP. Google knows where we are to within a few yards, which feels slightly spooky, but the fact that we have not had to buy a map, or even subscribe to satnav, does not appear in GDP.
This affects government revenue. It does not get the VAT on the service we use because that service is not paid for and not officially recorded. Google makes a tiny amount of revenue, and may make more as location-based services develop further, but even then, if the service we “buy” is simply time saved, that will not appear in the statistics either.
That surely is the key to what is happening. We may not be getting increases in our living standards as measured by GDP per head or per hour worked. But we are getting increased living standards in time saved and hence more effective use of time both at work and at leisure.
Now you could argue that we don’t use this extra time very well. Are we really better off by sending YouTube videos to each other of cute dogs pretending to play the piano, or people falling off swings and landing on their backsides? It is true, too, that a vast amount of time at work is lost by people obsessively checking their personal emails or scanning the internet for some new celeb scandal. But how people use their time is up to them. We reveal what we want by what we do; it is called “revealed preference” and a jolly useful economic concept it is.
What I suggest will happen is that we will get better at measuring non-paid for services and finding some way of allowing for these in calculating genuine economic activity. When we do that we will, I suspect, find out that far from stagnating, productivity is rising as
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