Organizations in Healthcare and Manufacturing Prefer Embedded Analytics
Watch this video to dive deeper into embedded analytics use cases for the healthcare and manufacturing industries.
Many application providers and users can show strong results from the use of embedded analytics across various functional areas. But the embedded story also includes industries. Two of the many that have found the potential of embedded analytics promising are healthcare and manufacturing.
From bringing actionable data closer to the point of patient interaction in healthcare to using more kinds of data for predictive and search-based analytics in manufacturing, analytics baked into everyday tools produce a higher level of satisfaction than standalone applications. And research from both industries points to improved decision support -- faster and more efficient -- as the reason.
Given the breadth of software applications in frequent use today, the potential for embedded analytics is seemingly limitless. From CRM and ERP to financial forecasting and human capital management, applications for embedded analytics abound, but let’s make it a little bit more real here.
Welcome back, I’m Mike Locke. I’m Vice President and Principal Analyst here at the Aberdeen Group and I’m delighted to share with you the fifth and final video in this series exploring embedded analytics. So, we’ve discussed this concept from the perspective of those providing applications embedded with analytics and we’ve discussed it from the perspective of the end-users interacting with software embedded with analytics. Let’s get a little bit more specific from an industry perspective here.
Recap: Embedded Results
Before we do that, though, I just want to add a quick reminder of the context here. If you saw either of the previous two videos, you may recall how companies embedding analytics were seeing some pretty strong results. The way we defined those leaders was by looking at their ability to expand their business, both through the addition of new customers as well as new revenue streams. Leading companies, in this context the top 40% of respondents, saw more than twice the year-over-year increase in total customers as well as organic revenue growth.
Healthcare: Embedded Analytics Provide Insight at the Point of Care
So, with that in mind, let’s jump into our industry snapshots here starting with the healthcare industry, something that’s near and dear to my heart personally.
I recently launched a survey to the healthcare provider community, mostly hospitals, asking about their experiences with technology. Obviously, my own interests were more on the analytics and big data side, but we started off asking the simple question of what drives most of their technology investment decisions.
At the top of the list, from both clinical staff as well as operational and IT employees, is the need to bring actionable data closer to the point of care or the point of interaction with a patient. The value of having that data at their fingertips in that moment of interaction is something that a lot of care providers are striving towards today.
As we got deeper into the survey I started asking more pointed questions about their experiences with technology and analytics in particular. And another question that I asked was how they prefer to use analytics. As it turns out, over half of these provider respondents said that they would actually prefer to have analytics baked within other everyday tools that they interact with, such as electronic medical records, EMR, system or some other application, as opposed to using it as a standalone application. Essentially, as they look to get insight closer to that point of care, that point of interaction with a patient, many are seeing the value of having a single tool to help with this decision process and having analytics embedded within it.
Manufacturing: Embedded Analytics Reduce Costs and Improve Decision-Making
Then, from yet another perspective, here we look at the manufacturing industry. So, taking a slice of data from my most recent survey looking at manufacturing organizations using analytics primarily as embedded functionality, say within their MES, MOM, or ERP systems, versus those using it as primarily standalone functionality, we start to see some important differences.
First off--and this is from data actually not pictured here--the research shows that manufacturers that are taking an embedded approach are able to use more kinds of data on a regular basis, whether it’s structured data, unstructured data, machine-generated IoT data. But they also reported a greater level of analytical activity in some key areas like data discovery and visualization, predictive analytics and search-based analytics as well.
But like in other industries, for manufacturers it all comes back to familiarity and decision efficiency. These companies taking an embedded approach reported a higher level of satisfaction with the job role relevance of their analytics capabilities. They were more likely to report an increase in their speed of decision making and then they were ultimately able to deliver a larger reduction in operating costs as compared to those taking a standalone approach.
So, these are just a few examples here. But, as I alluded to before, the industry and the job role use cases for embedded analytics are seemingly limitless.
So, that about does it for the fifth and final video in this series. I hope you’ve enjoyed some of this content and I want to thank you again for joining us for this series. Thanks very much and have a great day.