Operational analytics is an analytical approach meant for improving the operational processes of a business. A combination of data analysis and Business Intelligence to make everyday operations efficient in real-time.
In the world of data, much of the attention is focused on analysis. There’s a huge set of tools out there for moving, storing, transforming, and analyzing the data companies collect. This makes sense—after all, it’s hard to operate anything, particularly a company, without clear visibility.
While visibility is great and required, inside many organizations, there’s a disconnect between the data that’s collected and what to do with it. Much of what’s important to executives and managers are backward-looking performance indicators that likely have little immediate bearing on how a salesperson or junior marketer behaves. What’s more, much of the data that a company collects gets stored in such a way that it’s separated from the day-to-day tools that most employees rely on to get their work done.
Broadly, operational analytics is an attempt to solve this problem: moving data out of the realm of pure analysis and into the on-the-ground operations of a business. To make things simpler here’s a set of objectives for any operational analytics tool:
A good operational analytics tool should work at multiple levels: allowing users to operate at the level of data fidelity with which they feel most comfortable. This is because the needs of on-the-ground users can vary a great deal, with some wanting access to raw, or near-raw data, while others prefer digests and scores.
It’s an exciting moment for operational analytics thanks to the explosion in the modern data stack over the last decade. The opportunity now is to get all this amazing data into the hands of more customer-facing employees in a format they can use to drive meaningful growth-generating actions.
Here are some amazing companies in the Operational Analytics .