Mobile continues to be an important point on the agenda of most CIOs. While some trends like mobile device management (MDM) have seen mainstream adoption within business applications, the adoption of mobile technology platforms have been considerably slower in the enterprise than in the consumer market. However, innovation in the mobile space hasn’t stopped. In recent months, the industry has produced a series of technologies that will play an important role in the next successful generation of mobile enterprise solutions.
The list of emerging mobile technologies that may become relevant in the enterprise is incredibly large to cover in a single article and, many times, requires making assumptions about a market that has more than once proven to be unpredictable. For the purpose of this article, we have focused on technologies that, although new, are already enjoying a significant level of adoption within mobile applications in the consumer market and that are immediately applicable to enterprise scenarios. Specifically, we think the following mobile technologies can have an impact in the enterprise in the near future.
1. Machine learning for mobile analytics
The evolution of machine learning, stream and predictive analytic technologies is starting to power the next generation of mobile analytic solutions. The first wave of mobile analytic platforms focused on basic business metrics such as user sessions, retention or engagement, as well as operational metrics such as app crashes, API calls, etc. The emergence of machine learning, stream data processing, and predictive analytics allows businesses to gain insights about mobile data that weren’t possible before.
Modern stream analytic technologies allow the executing real time queries over mobile data streams containing hundreds of thousands, or even millions of events. Machine learning technologies enable the prediction of real time actions in a mobile application, or accurately selecting the content to display on a specific section of a mobile application. Even though applying machine learning to mobile analytics is a relatively new concept, mobile advertising platforms seem to have taken the lead in the space. Platforms like Mixpanel and Yahoo’s Flurry are also in a great position to expand their mobile analytic platform with machine learning and predictive models.
2. Mobile application streaming
Application streaming created a multibillion-dollar market for desktop application and its potential is even higher for mobile apps. The ability to stream data, content or entire apps on demand from secured and centralized locations could be a catalyst for the adoption of mobile apps in the enterprise on a larger scale.
In recent months, we’ve started seeing breakthroughs in app streaming technologies from companies like Google that are providing the first signs of the applicability of these technologies to mainstream scenarios. While users are already benefiting from mobile app streaming technologies in the consumer market, the implications in the enterprise can be significant and address many of the challenges in areas such as security and distribution which are common in enterprise mobile solutions.
3. Deep linking
Deep linking is becoming one of the most popular trends in modern mobile computing. Conceptually, mobile deep linking specifies a format to launch a mobile application with specific configurations, such as home screen, images, user profile, etc. Deep linking has become the foundation of relevant mobile capabilities, such as app discovery or search.
In the context of mobile enterprise solutions, deep linking will allow organizations to deliver a group of specific mobile applications interconnected using deep links. Using this model, enterprise mobile apps can focus on specific tasks and evolve independently while communicating with other mobile apps via deep links. Platforms like Deeplink.me and Branch already represent viable options to enable deep linking in the context of enterprise mobile apps.
4. Self-service, data-Driven mobile apps
Most mobile enterprise applications focus on accessing and displaying business data from enterprise systems. From that perspective, the number of business scenarios from accessing corporate data from a mobile app is vastly larger than the number of apps that can be effectively produced by mobile development teams in an enterprise. To address those challenges, enterprises can benefit from platforms and tools that enable the self-service creation of mobile apps.
To be effective in the enterprise, self-service mobile application platforms need to combine the seamless authoring of mobile front-end with sophisticated back-end capabilities to access data from corporate systems in a secure way. After a few years of struggle, platforms like Microsoft’s PowerApps, Capriza and AppGyver’s Supersonic seem to have found the right formula to enable self-service, data-driven mobile applications.
5. New cross platform app development stacks
Native and cross platform mobile app development has a special place in any enterprise mobile strategy. For the last few years, solutions like Xamarin or Appcelerator, have been the main choices for enterprises developing mobile apps. Despite the great value proposition provided by those technology stacks, many developers prefer to rely on native stacks such as Android and IOS to implement enterprise mobile applications.
After a few years of evolution in cross platform mobile application technologies, the enterprise space might be ready for a new mobile technology stack. To be successful in the enterprise, a cross platform mobile app technology doesn’t only need to provide a simple experience for authoring mobile apps, but also robust infrastructure capabilities in areas such as testing, distribution, security, as well as a sizable developer community. Recent efforts like Facebook’s React Native seem to have the right combination of simplicity, robustness, and developer traction to become relevant in the enterprise.
This article was written by Jesus Rodriguez from CIO and was legally licensed through the NewsCred publisher network.