3 Big Ways Data Analytics Can Boost Employee Productivity

Gathering hard data on your employees, practices, and customers is now easier than ever—and it’s easier than you might think to pull actionable insights out of the data you gather.

The phrase, “data analytics,” gets thrown around a lot in business contexts these days, but the people who use it aren’t always clear about what you’re supposed to be analyzing—or how that analysis can translate into improvements in your business processes. The truth is, though, that gathering hard data on your employees, practices, and customers is now easier than ever—and it’s easier than you might think to pull actionable insights out of the data you gather.

Here are three concrete ways in which data analytics can make your employees more productive, and raise the return your business gets out of every hour they put in.

1. Streamlining Processes

Whether you’re operating a warehouse, making on-site customer visits, or organizing large creative projects, you almost certainly have some lag creeping in somewhere in your business processes. While this lag sometimes results from employees who don’t do their part, that’s not necessarily the case—in fact, lag often arises because you’ve provided employees with guidelines that don’t address the challenges that arise in the course of normal day-to-day work. Every time your employees have to take time out of their days to find solutions to those challenges, you’re losing money.

That said, analyzing your processes and providing pre-packaged solutions doesn’t have to mean intruding on your employees’ privacy. Some warehousing chains now require all employees to wear armbands that measure how much time they spend walking from product to product, and even the amount of time they spend in the restroom—exactly the kind of Big Brother spying that makes some companies think twice about tracking employees on the job.

UPS, on the other hand, took a more respectful route. By tracking the fuel consumption of delivery vehicles, the company’s data analysts realized they could save more than a million gallons of fuel every year simply be implementing a “right turn only rule.” Without spying on its employees, UPS leveraged data analytics to streamline the delivery process, and made life easier for delivery drivers, accountants, and customers alike.

2. Catching Wasteful Mistakes

How many times have you caught a tiny but costly numerical error too late to correct it? Simply disciplining the employee who made the error may not have much of an effect—after all, that person didn’t make the mistake deliberately. The only real way to prevent an error like that from creeping in again is to improve your optics on the process that generated it, so you can see where and why it occurred in the first place—and act to prevent it in the future.

This kind of error catching is one of the most powerful applications of business data analytics. By tracking every step of processes such as sales pitches, spreadsheet creation, and document collaboration, you’ll be able to see which errors are made most frequently, where in these processes employees make those errors, and which specific employees (or types of employees) are most likely to make which types of mistakes.

What’s more, by using this data to build profiles of each workflow in your business, you’ll actually be able to generate predictive models of workflows for future projects—complete with predictions on the types of errors that are likely to creep in at each stage of the process. This can empower you to train your employees to watch for those specific errors, while also giving you a clearly defined set of processes and documents to monitor extra closely for mistakes.

3. Improving understanding of customers

No matter what kind of product or service your organization provides, customer conversion and retention are both crucial to your success. And while you may have well-trained sales staff who bring years of experience to the table, it can be hard to know exactly where in the sales process they’re losing qualified leads, or failing to turn one-time customers into consistently loyal ones.

You’ve probably been gathering your own data on customers for a long time—and the latest analytics tools can turn that data into robust customer profiles, which often provide insights about who’s buying your products and services, who’s not, and why. That means you’ll gain an understanding of exactly where in the sales process your salespeople are losing leads—and what you need to do differently in order to hold on to them.

Customer data analytics also can generate actionable predictions about who is likely to buy your products next, and at which touch points (sales calls, the Web, in-store displays, etc.) they’re most likely to meet your brand. These insights can help you allocate marketing spend in ways that maximize ROI—and to design personalized customer journeys that lead the way to a purchase.

With streamlined processes, precise optics on errors, and a personal understanding of how your customers think, you’ll be well equipped to raise your organization’s efficiency even as you continue to bring in new business. But perhaps the most important reason to start leveraging data analytics in your business isn’t listed above, because it’s self-explanatory: Your competitors are already taking advantage of data analytics, and they’re already starting to reap the benefits. Will you?

Jason Stephen Ali is Marketing director of BroadConnect, a VoIP service provider in Canada. Offering telecom and networking solutions for business of all sizes, the company specializes in providing reliable, scalable, and secure services for voice, video, and data. Learn more at www.BroadConnect.ca.