Software companies don’t want to admit they developed their BI tool for internal use and only later did they try to make it work for customers outside of the organization. They can’t call their BI platform purpose-built embedded analytics for OEM use.
So it’s unlikely that you’ll ever hear a vendor tout how they developed a software platform specifically to serve their own users, and not yours. But that’s what many analytics vendors have done by building their solutions for internal use cases. The internal use case tools were initially built as desktop tools to answer the organization’s internal needs. This framework causes struggles with embedding analytics. They didn’t consider requirements for external use. The workflow imposed upon analytics users comes from their needs, as do the methods for handling data. Tech requirements, both hardware and software, match what their company needed and not the needs of their customers. Only lately have they added their limited versions of embedded analytics.
Despite making claims as self-service solutions, these inward-facing platforms often require tech staff to design and create reports and dashboards. End users still depend on IT to create these tools. As business users try to drill down and through the data, they’re limited if they must wait on IT staff to create new reports. Each report and data visualization may add more insight and raise more questions, but these pauses and “holds” put an end to making the business decisions at the point of context and in real time.
Choosing an analytics solution that’s purpose built for embedding enables you to establish efficient workflows that keep your customer’s end users decision-making in context. You won’t sacrifice your core business or core application to stick a business intelligence platform alongside of your application’s workflow. You don’t have to change the well-established business processes upon which you built your application.
This isn’t a new problem. Dan Woods addressed this in an article published in Forbes five years ago. “Application development may be needed, but finding an app or choosing an application platform that is tailored to a specific business problem should be the first choice.”
When will businesses get to the “Analyst 2.0” as described in Woods’ article? Samsung Vice President Mok Oh said that’s when business users can conduct analysis themselves, which we’d say is realizing the potential of self-service analytics. The process for most vendors appears fragmented, with obstacles in the way of reaching that goal.
End users need self-service analytics, including the ability to create reports and dashboards that utilize data visualizations. The labels and categories used within the analytics platform should be written using terms that the end users recognize and understand, rather than arcane terms or naming conventions that only make sense to IT or DBAs. Tailor the analytics tools for the organization and its end users to improve user adoption and business insight. As Woods wrote, putting these tools in the hands of users and in a highly visual way assists them, rewards their curiosity and efforts at analysis.
Izenda: Only Purpose-Built Solution for Embedding Analytics
Our purpose-built software lets your team focus on developing and customizing your application for your customers, delivering a competitive advantage in your dealings with clients and potential customers. It frees up your software product team to do the work they do best in developing additional value for your products.
“Our platform is purpose-built for OEM use and embedding in business applications. Our unique approach is the only solution in the industry that meets the needs of end users, business analysts, and software development teams.” – Bill Curran, President and CEO, Izenda
Get your application and its updates to market quicker with an analytics solution that’s purpose-built for OEM use.
Benefits to purpose-built embedded analytics
- 3-tier modern architecture built to be future-proof
- Faster time-to-market (with benefits such as improved ROI)
- Analytics solution tuned to unique needs of the software company
- Focus on core competency with internal resources
- Scalability
- Lifecycle productivity for analytics solution
- Satisfied customers
- Increased revenue
- Best practices expertise
- Lower risk
