Productivity Indicators: Use Patterns for Effectiveness

This article is an excerpt from the Shortform book guide to "High Output Management" by Andrew S. Grove. Shortform has the world's best summaries and analyses of books you should be reading.

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What are productivity indicators? How can you use them to be a more effective manager and increase output?

Using productivity indicators is an important strategy for management. Indicators can help you see patterns, and leading indicators can help you predict productivity and make changes.

Read more about productivity indicators and how they work.

Other Productivity-Increasing Strategies: Productivity Indicators

In the previous chapter, you learned how to increase your productivity by taking inspiration from manufacturing’s production process. In this chapter, we’ll look at some other manufacturing strategies that can aid productivity, as well as strategies for efficient and productive meetings.

Productivity Indicators

Productivity indicators, or measurements, tell manufacturers (or managers) about what’s going in the production process (or administrative process) and provide information about output.

There is a myriad of possible productivity indicators ranging from equipment downtime to profit to customer satisfaction. To determine what your indicators should be, ask yourself what information you want to know first-thing every day to head off potential problems. Effective indicators must:

Measure output rather than activity. For example, it’s more important to know how many orders a salesperson received than how many calls she made.
Be physical and countable. For example, a janitorial indicator might be the number of square feet cleaned.
Tell you if you’re going to meet your operational goals. (Shortform example: The number of pages of a novel you write today will tell you if you’re going to finish your book by your deadline at the end of the month.)

For example, here are the five most important pieces of information to a factory manager:

Sales forecast, which is how many sales you expect to make in a given time period. To inform your forecast, compare yesterday’s forecast to yesterday’s real numbers (the difference between them is called variance). This will show you if your forecasting is generally accurate or if you need to reconsider your approach.
Raw material inventory, which is how much of the materials manufacturers need to make the product on hand. If you check this first thing in the morning, you have time to either order more or cancel a delivery, whichever is needed.
Equipment condition. If something has broken down, manufacturers will need to get it fixed or adjust the process to work around it.
Human resources. If some staff are sick, manufacturers have to call in extra help or take people off the less important jobs to cover the most important ones.
Product or service quality. Manufacturers use a variety of measures for this indicator, such as customer satisfaction.

Indicators are very helpful in types of work besides manufacturing because they:

Provide clarity about individual and team goals
Make abstract tasks more objective
Allow for comparisons between different groups
Help solve problems. When something goes wrong, you can look at your existing data to see where and how the problem might have started. If you don’t have data, you can’t do anything until you collect it, and in the meantime, the problem will likely worsen.

People tend to overreact to what they’re paying attention to. (Shortform example: If you’re trying to avoid overstaffing, you might inadvertently reduce your staff so much you don’t have enough people to manage the workload.) To avoid overreacting to an indicator, pay attention to all areas of your business.

Leading Indicators

There’s a special type of indicator, called a leading indicator, that tells you what might happen in the future. These productivity indicators are useful because they predict problems before they happen, so you can take preemptive action to avoid them. (However, this is harder than it sounds, because you don’t have an existing problem to justify the expense or anxiety of reacting.) Leading indicators must be accurate and believable (or else you’ll be reluctant to act on them).

There are a few leading indicators that are appropriate for most cases. All of them are only visible once you’ve plotted the data on a graph:

Linearity indicator. This indicator is the slope of the line of output over time. Ideally, the line should be straight and ascending (which indicates a consistent output) and hit the desired point of a particular output at a particular time.

If the graph is a saggy line or not a line at all, then output isn’t constant and you’ll have to adjust production in the remaining time to meet the goal. If you continually have concentrated output right before the deadline, you’re probably not using equipment and manpower efficiently and run the risk of having a problem that derails the goal right before the deadline.

Trend indicators. Like the linearity indicator, this indicator shows output over time but also takes quality into account: Output must meet a certain standard. This helps you extrapolate both future output and quality.

Stagger chart. A stagger chart estimates future output numbers a few months in advance and is updated as the real numbers come in. This allows you to see how close the forecasting was to reality, which informs your future predictions (Shortform example: If you consistently predict selling more than you actually sell, start predicting lower). Stagger charts are particularly useful for forecasting economic trends.

For example, in the chart below, in March, the forecaster predicted that March would see 20 units, April 26 units, and May 32 units. In April, she had the real number for March—21 units, indicated with an asterisk—and predicted a new forecast for the next three months.