With artificial intelligence, data mining, and machine learning, operational analytics is able to use data analysis to help companies stay on top of their business operations. These monitorable activities can already exist and can be taking place in real-time. 

In today’s business context, it is imperative that businesses access real-time data with total transparency into customer behavior and business processes so that the business owners can monitor their day-to-day operations basis and take the necessary actions to improve customer satisfaction and benefit their bottom line.

When it comes to use cases for operational analytics, there are countless situations when it can be used to identify and solve problematic occurrences. 

The most practical use cases tend to reside within the areas of sales and marketing, where employees on those teams rely on current and exact data to inform their daily decision-making. 

Discover the most critical reasons why your business needs to be using operational analytics to streamline company activities and improve productivity.   

1. Automation with operational analytics 

Contemporary times call for automation in order for organizations to maintain efficiency. Once operational analytics are put into motion, companies have the power to increase the speed of their processes, eliminate human error from redundant tasks, and broaden the scope of data that team members have the ability to see with automation. 

The pluses associated with using operational analytics don’t stop there. Transactions and leads can be sent to the sales team, message notifications can be pushed through to alert the appropriate department when accounts go dormant, product usage characteristics can head over to the product team, and campaign-related information can make its way to the marketing department.  

2. Sales with operational analytics 

Operational analytics can amplify sales in ways that include leveraging free customer accounts that can pay a monthly fee to be upgraded to have access to advanced features. Analytics can identify how many signups have taken place, the percentage of free users who became paying customers, and how successful sales representatives have been in customer conversations. Now the sales team can focus on helping customers. 

3. Marketing with operational analytics

Marketing managers with an understanding of data systems can use operational analytics to experiment and gather results regarding data, eliminate marketing elements that are failing, and elevate the ones that are substantial to keep their products and services properly promoted. 

4. Product analytics with operational analytics 

Companies are leveraging operational analytics in product analytics platforms to derive a better understanding of how customers are using their products. Getting user id, service area, and product usage information in these product analytic tools are additional use cases that enable more complex analysis on a granular level, giving team members from all sides of a business the identical vision of customers to ensure that everyone is working towards arriving at the same definition of success. 

5. Making decisions with operational analytics

When you are part of an organization that is analyzing and responding to customer data in real-time, the speed at which decisions can be made becomes faster than ever. 

You don’t feel like you were left back during the ancient industrialization times when strategies revolved around only becoming aware of data regarding fundamental problems on a quarterly or annual basis. The decision-making process affects not just the staff and the productivity but also the customers that depend on what a company may provide. 

Making necessary adjustments to entire workflows and processes and workflows doesn’t have to feel so frightening when it is able to occur in real-time, which makes everyone involved better positioned to reduce the amount of waste that is taking place, increasing the profitability, making troubleshooting more accurate by turning up the response time. 

6. Productivity with operational analytics 

Operational analytics is able to help businesses remain streamlined in their operation capacities by enabling them to focus on and identify inefficiencies in order to make the proper adjustments. For instance, businesses with access to operational analytics data can realize whether or not the way that they process and approve invoices for payment is taking up too much time and lagging behind a long series of approvals.

The way in which this valuable data could prompt the business to take a whole new look at their procedures could involve establishing a much more acceptable number of approvals so that they can streamline the process and yank down the turnaround time.    

Data enrichment gets accelerated with operational analytics at the helm, pushing clean data back into operational systems so that non-technical users can leverage it to generate value for the organization.