What Is Operational Analytics? In this practical introductory guide we will give a definition to the term but not without explanations about why you need to practice operational analytics and how.
We will review some alarming statistics and will show you how you can remove yourself from being included on the wrong side of the diagram.
We will finish the article with a real-life example and show you how XpoLog can help in turning your corporate data into actionable insights (and thus enabling operational analytics strategies).
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Let’s begin
Cloud computing, mobile devices, and IoT technologies continue to evolve and proliferate. As a result, businesses are generating and collecting more data than ever before.
Data is generated and stored every time a customer interacts with a website or device. Savvy companies understand the importance of capitalizing on that data. It enables them to enhance customer experiences and increase profitability, among other countless benefits.
At the same time, every day an employee uses a company-issued tablet or device to do their jobs, they generate data. And every purchase—whether that’s coming from customers or the procurement department—leaves a trail of data, too.
Suffice it to say that in the age of big data, leading companies need to analyze this data—rapidly and easily. That’s the ticket to increasing workplace efficiency, driving competitive advantage, and delighting customers.
Struggling to Make Sense of It All
As it turns out, however, many companies are having a difficult time harnessing all of the data they generate. That’s due to a confluence of factors. For example, data often lives in several different repositories. And many workers need to get IT’s help to run analytics.
Believe it or not, a recent study found that 55% of the average business’s data is unused. This means that it has no practical value. Since the data is unused, it’s impossible to know what trends and insights are hiding in it.
While lots of businesses have a hard time using their data to begin with, many other organizations struggle with data integrity. In fact, one recent study found that the financial impact of poor quality data is expected to exceed $3.1 trillion annually in the U.S. This makes perfect sense: When you’re making decisions based on inaccurate data, how can you expect to make the best ones?
Still, the writing is on the wall; 81% of technology professionals agree that data is very valuable to their organization’s success.
A Better Way Forward
The good news is that—with the right tools in place—it’s possible to tap into all this data. And leverage it rapidly to make better business decisions.
For example, companies can use a process known as operational analytics to analyze large swaths of data and figure out the best path forward.
If you’d like to learn more about operational analytics, you’ve come to the right place. Keep reading to learn more about what operational analytics is, how it can be used, the benefits of operational analytics, and more.
What Is Operational Analytics?
Operational analytics is the process of using data analysis and business intelligence to improve efficiency and streamline everyday operations in real time.
A subset of business analytics, operational analytics is supported by data mining, artificial intelligence, and machine learning. It requires a robust team of business and data analysts. And it also requires the right tools (think Tableau and Looker).
As such, operational analytics is much better suited to large organizations than small businesses—at least for now.
Now that we’ve got our definitions out of the way, let’s take a look at some of the transformative benefits operational analytics delivers.
What Are the Benefits of Operational Analytics?
There’s a reason leading organizations are increasingly investing in operational analytics. It can have a profoundly positive impact on the entire enterprise.
Here are three of the reasons why businesses that prioritize operational analytics don’t look back.
1.Faster Decision-Making
Quite simply, businesses that can analyze and react to customer data in real time are able to make much faster decisions.
Traditionally, businesses would make adjustments to their operations based on a quarterly or annual data review. In this reactive manner, they might miss out on serious revenue or glaring issues. They’d only become aware after the fact.
On the other hand, companies that embrace an operational analytics platform can make adjustments to processes and workflows in real time. Or at least close to it. As such, they are in a better position to increase profitability and reduce waste. They can also detect problems and inefficiencies quickly and respond to them rapidly.
In fact, one recent study found that improving operations can result in a $117 billion increase in profitability for global organizations.
2. Enhanced Customer Experiences
Businesses that react to situations in real time are able to provide better customer experiences. It’s that simple.
For example, imagine an e-commerce company runs operational analytics. After that, they find that a significant percentage of its users are adding items to their carts but not completing transactions. Armed with that information, they then investigate the issue. It quickly becomes apparent that their website is buggy and checking out is a nuisance.
After identifying what’s wrong and fixing it, the company improves the customer experience and drives more online sales.
3. Increased Productivity
Thanks to operational analytics, businesses can see the inefficiencies that exist in their workflows. Accordingly, they can then change their processes to streamline operations.
For example, a company might run analytics and realize that the process for approving a purchase order is too cumbersome. In this case, it requires too many signatures from too many people who are moving around constantly.
This data might encourage them to rethink the process entirely. They may either decide to reduce the number of signatures required to approve a PO. Or they could opt to move to an online system that eliminates the need for having to track anyone down in person.
Now that you understand some of the benefits of operational analytics, let’s take a brief look at a real-world example.
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A Real-Life Example of Operational Analytics in Action
Let’s say you want to install an in-home, cloud-based smart security system. You order the product online and it arrives a few days later. After you pop open the box and glance over the instructions, you plug in the device.
But, for some unknown reason, you’re unable to connect it to your local WiFi network. The device is trying to connect. But the signal keeps cutting out.
An enterprise with a robust operational analytics platform might be able to detect that you’re trying to connect for the first time. Then an alert would appear in central management’s operational analytics platform indicating a new device is being activated. The platform would also indicate that the device connection isn’t steady. Instead, it’s turning on and off.
As a customer, you’re becoming increasingly frustrated. The cool new device you just paid a pretty penny for isn’t connecting—despite following all the instructions. Further, you only have a few minutes left before you need to head to an appointment.
Under the old way of doing things, companies would expect customers to call a support line. At this point, the already frustrated customer would then have to wait on the phone. Finally, if and when a live agent picked up, they would troubleshoot the issue over the phone. Or, if that didn’t work, they’d schedule an in-person technician appointment.
Customers tend not to like either of these approaches. What’s more, they’re wasteful to businesses, too.
Operational Analytics Saves the Day
Now, here’s how operational analytics can truly enhance customer experiences. Rather than taking this reactive legacy approach, the security company could proactively reach out to the customer. They could provide personalized customer service by sending a text message to the customer asking if they need help. Or, better yet, a real person could call the customer and walk them through the setup process.
This is a big deal. A recent study indicated that 83% of U.S. consumers prefer working with a real customer service person to resolve issues. At the same time, another study showed that customers who experience personalized customer service are 44% more likely to return.
Think of the transformative change this proactive customer service approach can have on customer experiences—and on profits.
Is Your Business Ready to Use Operational Analytics?
By now, you probably know how important it is for your business to embrace operational analytics. If you’re looking for a turnkey platform that can help your business be more proactive and more efficient, check out XpoLog’s Application Monitoring Platform.
With features such as AI-powered log analytics and real-time monitoring of performance issues and cyber threats, you can rest easy knowing that your business is running smoothly at all times.
That’s the ticket a stronger business, happier customers, and a healthier bottom line.
