6 Ways To Jump-Start Productivity Using Data

Employers have always put a premium on productivity. New ideas and methodologies are constantly being developed to boost the output of workers without putting too much strain on them. From open floor plans to four-day work weeks, companies have tried a lot of different strategies—with varying levels of success.

The better strategy? Start with data. Metrics matter not just for sales, marketing, and operations, but for how you optimize your team’s output. Consider these six ways you can use data to increase productivity in your office:

1. Put it all in the same place.

Cross-referencing metrics is tough when they’re scattered all over the place. How are you going to check hours worked against projects completed if your timeclock tool doesn’t integrate with your project management platform?

Getting data all in one place requires a process known as ETL, short for “Extract, Transform, Load.” The best ETL tools extract and compile disparate metrics, helping leaders get a holistic view of their operations.

Think of ETL like an X-ray of your business, giving you an inside look at exactly where bottlenecks are. Examining deep relationships between metrics makes it possible to find ways to increase overall productivity. Otherwise, you’re just making changes blindly.

2. Stop worrying about hours—focus on output figures.

Businesses have long measured their employees’ productivity according to the number of hours they put in each week. Team members get compensated for the amount of time they’re on the clock, and they’re expected to work nonstop during those hours. 

But counting hours is, in many cases, an inefficient and outdated way to measure productivity. Let’s face it: People waste a lot of time when they’re on the clock. Metrics based on output are a more effective way to judge whether an employee is actually being productive.

For example, two employees could be completing the same number of tasks each day. If one takes eight hours and the other only needs six, the second is more productive. If their output is right where it should be, there’s no need to worry about the number of hours they’re logging. 

3. Let data point you to productivity-enhancing tools.

Productivity isn’t solely dependent on the individual. The tools people have at their disposal play a huge role as well. For example, construction workers will be able to demolish old pavement and build a new highway a lot faster with heavy-duty equipment than with pickaxes and shovels.

Unfortunately, the solution isn’t always so clear at knowledge-based businesses. Instead, use data to point you in the right direction. If customers complain about long hold times but your customer service reps are already working at full tilt, perhaps it’s time to invest in a better CRM. 

Take a “slowest hiker” approach. You can spend a lot of money trying to improve…

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