How Automation Streamlines Data Management

Managing data is a challenge. It’s not hard to collect data, but most companies collect data in disparate locations and across multiple applications that don’t talk to each other. With this model, multiple reports are required to crunch data from multiple sources. That requires manually entering data into yet another application to generate a final report.

While manual methods worked in the past, it’s no longer sufficient. Today’s businesses rely on automated processes to stay competitive and for good reason – automation is a game-changer for data management.

How does automation improve business processes?

Automation uses technology to perform a variety of tasks that would be slow to perform manually by humans. In general, automated processes save time and money, and even increase the accuracy of whatever is being automated. For example, Resolve Systems, an intelligent IT automation provider,  describes several instances where network automation saved companies millions of dollars, thousands of work hours, and produced faster incident resolution.

One area where a large number of organizations have embraced automation is cybersecurity. Automatic threat detection and isolation are necessary to combat today’s sophisticated cyberattacks. However, automation can help organizations consolidate, manage, and analyze data everywhere.

Application integration supports deeper insight

By integrating multiple applications, you can automate many processes that would normally require manual work. Integrating applications from multiple departments is an opportunity to consolidate data, allowing for more complex reporting that provides deeper insights.

For example, say you have the following departments: Human Resources, Marketing, Sales, Shipping, and Accounting. Normally, each department will generate their own reports and come together where necessary to analyze and collaborate.

However, when all department data is housed in one central repository, you can run a report that will tell you everything you’d normally need to figure out manually. You can know how fast your orders are being shipped, how many customers contact customer service after a purchase, and how many customers unsubscribe from your email list after making a purchase.

Automated data management simplifies operations

Powered by machine learning and artificial intelligence, automated data management tools simplify a business’ operations by handling processes that would take humans hours – or even days or weeks – to complete. For example, automating processes can help evaluate  data and address errors, like merging duplicate entries.

One real-world example most people can relate to is having multiple entries for the same contacts in your email list. Sometimes people sign up for free downloads twice and spell their name differently. Other times, they get added to the list automatically after a purchase as a duplicate contact.

Automation strengthens simple and complex data-driven decisions

Successful companies make decisions based on hard data. Their focus is to gather and process data as accurately as possible to generate insights that can be used to take effective action.

Automation can be used to strengthen both simple and complex data-driven decisions. For example, you can automate operational decisions and eliminate the need to make decisions in the first place by automating entire processes (like ordering supplies).

Automation can run reports that crunch data from multiple departments. For example, automated processes can notify the shipping department of an uptick in sales, so they can stock up on supplies and get ready to handle more orders.

Automation can also eliminate the need for any human action when orders are pouring in. When sales data gets crunched with shipping data, your shipping department will instantly know when there’s an increase in sales. Nobody will have to wait for someone to run a report and call a meeting.

With automation, the shipping team can also set parameters that trigger automatic supply reorders. For example, the system will know how many boxes are on hand by subtracting sales from the master inventory count. The application will automatically reorder boxes when the supply drops below 500 boxes. Once the inventory (or expected inventory based on new sales) drops to 499 boxes, an order will be placed.

Cloud data management is essential for automation

If you’re going to use automation to grow your business, you really need cloud-based data management. It doesn’t matter if you’re using a multi-cloud or hybrid cloud strategy – automation is smoother when the cloud is involved.

You can still manage on-premises servers and take full advantage of automation, provided you’re integrating with a cloud environment.

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