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Everything You Need to Know About Operational Analytics in 2022

Data and Analytics

Brian Wallace, Founder & President, NowSourcing

One of the many challenges that face modern industry is affected by the acquisition and aggregation of data. Data is constantly being developed and stored for companies that deal in the digital sphere. In many ways data is king, however, while it is a powerful tool, it can also be elusive and hard to cultivate. For instance, the idea of making high-profile decisions that can deeply impact a company’s trajectory and position pulled from data is a great challenge. 

In fact, getting the data that a company complies over time to be understandable, and usable for analytics to base high-level decisions on is not an easy task. That being said, there are certain modern developments that have helped to make this easier. 

For instance, improvements to data stacks have taken data from silos and transferred it to warehouses and data lakes. Not only that, but well-written business intelligence (BI) tools have used data enrichment and automation to help make this data more available and valuable. 

That being said, the bottom line is that most companies want to see decisions from the massive amounts of data they have to improve customer satisfaction through increased analytics. While their data lives in warehouses, companies struggle to use this data in powerful, impactful ways. 

This is where the field of operational analytics comes into play. In the face of warehouses full of data that is hard to utilize, operational analytics seeks to find the solution to this pressing problem. How do we take the data that is living in a data stack, and make it available to a company in a way that helps clarify, and direct decision making?

So what is operational analytics and how can it help your business in 2022? Here is everything you need to know about operational analytics, and how it’s different from traditional analytics. 

What Is the Bottom Line With Operational Analytics?

Before taking a look at how operational analytics can help to transform your company in 2022 and improve your data analytics, first it’s good to know exactly what operational analytics is. Operational analytics has a very simple concept and is very straightforward. This field of analytics focuses on gathering and interpreting data, however, it also largely emphasizes the implementation of that analysis for practical decision making. 

This means that in a nutshell, operational analytics seeks to give a company not just a breakdown of what their data means, but how it can be used in real-time. This information is meant to be understood clearly, and serve as data that can help to make informed, high-level decisions with deep impacts to improve customer satisfaction. 

What's the Difference Between Traditional Analytics and Operational Analytics?

Traditional analytics and operational analytics have several differences, even though they both rely on gathering and interpreting data. Analytics as a whole focuses on taking in data from a multitude of sources and trying to figure out key benchmarks and characteristics that are of interest. This data helps to bring a full 360-degree view to a company. 

While traditional analytics is focused on helping to better understand events as they have happened, operational analytics focus on analytics that are active. This could look like active enrichment of data as certain aspects of interaction are taking place. 

The difference here is that traditional analytics can be gathered to make important decisions, while operational analytics are leveraged in real-time and actively work. This essentially makes one of the most unique aspects of operational analytics the accessibility that it brings to data. 

Operational analytics has implications for improving several different fields of business from sales and marketing to automation and product analysis. 

How Do You Bring All of This Together?

One of the greatest challenges of operational analytics is that it is hard to have all of the sources of data communicating and working together well. This is probably the number one problem that many businesses run into as operational analytics must have clear, concise flows of information that work together to make these insights possible. 

Finding an effective, reliable way to streamline your operational analytics is something that any company that wants to implement operations analytics will have to do. While this may be challenging, it’s not impossible and can be done in a way that improves your entire company’s ability to gather operational analytics. 

Conclusion 

Taking the data that lives in your warehouse and democratizing it to a single source of truth is a valuable, real-time tool that can improve your company’s BI and drive analytics forward. This can have an incredibly powerful impact on your company’s ability to drive customer satisfaction forward and improve your brand. 

The good news is that if you know that your company is lacking a concise way to grow your operational analytics, there's no need to wait to improve this. 


Brian WallaceAbout the Author: Brian Wallace is the Founder and President of  NowSourcing, an industry leading infographic design agency in Louisville, KY and Cincinnati, OH which works with companies ranging from startups to Fortune 500s. Brian runs #LinkedInLocal events, hosts the Next Action Podcast, and has been named a Google Small Business Adviser for 2016-present. Follow Brian Wallace on LinkedIn as well as Twitter.