This is the first installment of a series posts on the state of application analytics and modern application development patterns and practices.
In a recent survey that includes responses from 100’s of development organizations, two thirds identified application analytics as either essential or important in one or more of the following categories: Product planning, Development prioritization, Test plan definition, Customer support, and/or Development ROI calculation.
Among this group where application analytics has the greatest impact, the following were identified as the most serious obstacles to implementation. (click to enlarge graphic)
Obstacles preventing the use of application analytics in my organization
Half of all respondents identified security and privacy - a 20% higher response rate than the next two closest obstacles e.g. lack of expertise and general quality concerns).
The emphasis on security and privacy is even more pronounced inside larger development teams. Nearly 3 out of every 4 development organizations with greater than 50 people identified privacy and security as an impediment – 50% more likely than development teams of between 5 and 15.
Correlating perceived obstacles to implementing analytics with development organization size
In fact, an organization’s size appears to have a significant influence on virtually every perceived obstacle; larger organizations appear to be more concerned with performance, quality and connectivity while smaller organizations struggle with awareness of analytics solutions, development best practices, and the required integration of their development and operations processes.
One might make the generalization that, due to the complexities that come with size, larger organizations have had to move to more tightly integrated platforms and practices – putting them in a better position to implement application analytics (and so they focus on potential risks stemming from an implementation) whereas smaller teams may not have as an entrenched “feedback-driven” integrated approach to development. As such, they are more likely to struggle with how to move forward (keep in mind that all respondents identified application analytics as either essential or important).
Privacy and Security and PreEmptive Analytics
Regardless of development team size, privacy and security is the number one perceived obstacle – and PreEmptive Analytics is unique in its approach to this critical requirement. PreEmptive Analytics includes the following:
- Development teams own their own data. PreEmptive asks for no rights to aggregate, inspect or resell your data.
- A two-level opt-in switch is included ensuring user opt-in to transmit runtime data from both regular usage AND application exceptions. The logic itself can be injected post-build for .Net and Java and can always be defined by the development organization.
- All data is, by default, encrypted on the wire.
- Device ID's (if they are collected at all) are hashed before they are transmitted.
- Tamper-detection and defense can be used to detect and defend against any attempt to alter or redirect runtime data transmission.
- Obfuscation can be used to obscure inspection by third parties of what is being collected and transmitted.
- Unique keys identify both the organization and the application source for data.