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How Does Insights Delivery Differ from Embedded Analytics?

Written by Roman Stanek  | 

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How Does Insights Delivery Differ from Embedded Analytics?

Part Two

In my last blog post, we touched on the difference between traditional BI and embedded analytics. We also explored some of the challenges that embedded analytics is currently facing, such as the market becoming flooded with embedded analytics offerings that aren’t truly “embedded.” So what’s next? What can we expect to see as we advance to the next stage of analytics? For me, it’s clear that the next big technology that we’ll see—and that we’re already seeing—is insights delivery.

What is insights delivery?

What I mean by insights delivery is what embedded analytics should have evolved to mean: highly personalized insights that are contextualized to the individual user’s business decisions within a single pane of glass. Essentially, it goes a step further than embedded analytics. Instead of embedding dashboards in your workflow, insights delivery collects and analyzes all the relevant data, then delivers a recommendation or insight to you at the exact point at which you’d need it in your daily workflow. As a result, employees can do their jobs faster and easier than before to deliver a specific measurable business outcome.

Insights delivery also solves another common problem with embedded analytics: that, in an effort to be useful to everyone, embedded analytics has actually been useful to no one. It presents too much information that’s far too broad, and users are forced to sift through the noise to find what they need. With insights delivery, there’s no data overload or additional work required to glean value from the information you’re given. Instead, each insight is relevant to the individual user and their needs—and delivered in a format that’s easy to understand with much of the legwork already done, letting the user quickly review the recommendation and take action.

Insights delivery shows you the exact information you need when and where you need it

As an example, let’s say I’m a call center agent and I’m talking to a client on the phone. During our call, I’ll see everything that I need to know about that client and recommended actions to take, or next steps, so I’m capable of confidently responding to an event in the best way possible. What I won’t see? The overall performance of the call center or any data that is relevant to other employees—but not to me.

The big difference here is that the data is personalized and contextual, and it helps spur the user to the next step in the workflow—with “workflow” being the operative word here. The insights provided need to pertain to a particular decision during that decision-making workflow. This way, insights are treated as an integral part of the work process, and as a result employees can do their jobs better and companies can realize more value. In this particular example, that would mean knowing immediately what offer to give to the client on the phone based on the information presented to the agent.

This is still a fairly new concept for many companies. Principal Forrester Analyst Michele Goetz shared that just 51 percent of organizations are investing in distributed, real-time insight delivery technology. But with companies like Gartner talking about the importance of moving from data to action to impact and bridging the gap between insight and action, it’s clear that insights delivery is a viable route to help us close the loop and deliver value that is much more tangible. So how can you take the first steps to begin introducing insights delivery to your company? I’ll explain in my next post.

Written by Roman Stanek  | 

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