Future of Enterprise Mobile Applications
Mobile has evolved as the primary interface to interact with Business Systems, transforming the experience of work and driving the productivity and efficiency of employees. Gartner Top 10 Strategic Technology Trends for 2018 clearly identifies Augmented Reality, Chatbots, Artificial Intelligence and Machine Learning, and IoT. These technologies are now starting to be used in enterprise mobile applications delivering unique user experience and increased workplace engagement.
In this blog, we will look at a few examples of how these technologies have been used in enterprise mobile applications and their impact on workforce engagement.
Case 1 – Augmented Reality to guide end-users
Augmented Reality (AR) is becoming a mainstream technology in mobile games applications. Mobile App stores are full of AR established mobile games and we are starting to witness the adoption of AR technology in Enterprise Mobility. For instance, SAP has developed an Augmented Reality based smart glass application warehouse picker app that enables stock handling and transfer, stock check serial number handling without the use of the number of devices as required in a typical set-up. As the technology matures, we will see increased usage of AR in mobile apps that will deliver a guiding experience to end-users. For example, Plant Maintenance applications capable of scanning camera images, recognizing the area of machinery and its various components. The application will also be effective in mapping those components with stock-keeping unit (SKU) number in enterprise resource planning (ERP) records and guiding a supervisor to the location of components in the warehouse for replacement or maintenance.
Case 2 – Chatbots
Conversational Applications are the new User Experience and are completely re-imagining user interface. As per Gartner, by 2019, natural-language generation will be a standard feature of 90% of modern Business Intelligence platforms. Today, four use-cases of Chatbot integration in Enterprise Apps exist:
1. Call center help desk:Specialized Chatbots can potentially reduce the number of help desk workers needing to handle routine requests by automating responses. 2. ChatOpsapprovals: A change in a back-end record will trigger an event, which can cause a message to be delivered to an enterprise messaging or workflow environment requesting an employee responds to “approve”, “deny” or “defer” in the app. 3. Equipment diagnostic inventory management: When implemented in conjunction with the Internet of Things (IoT) technologies, warehouse workers can be notified when a product is out of stock, or if a shipment has arrived at the loading dock that contains out-of-stock items. 4. Chatbot scheduling agent: Requires both the use of AI and bot-to-bot communication. The Chatbot will likely call another bot that uses AI to initiate a messaging stream combined with calendar access, in an effort to find open time on multiple calendars. As the technology matures and more Chatbot platforms are available, we will see increasing use-cases of Chatbot integration into Enterprise Apps. This theme was picked up by Atos for the 2018 edition of its IT Challenge where students are being asked to devise an innovative use case and build a prototype leveraging Artificial Intelligence and conversational interfaces.
Case 3 – Artificial Intelligence / Machine Learning
Machine Learning and AI has taken the world by storm and are being widely used in various automation processes. Machine Learning technology instructs computers how to execute tasks by learning from data – instead of being explicitly programmed.
But can it be used to revolutionize and improve the experience of enterprise mobile apps? Well, the possibilities are enormous – recommendation engine, predictive apps, diagnosis and treatment, motion detection and many more. Enterprise approval applications can be enriched and made intelligent with AI by applying trend and pattern analysis on various elements of an approval workflow to make a recommendation for approver. For example, analysing pattern of an individual’s expenses, leaves, travel to identify anomalies and deviations and recommend to approve or reject the request with due comments. Even the experience of conversational apps discussed above can be enriched and made intelligent with Machine Learning to provide a better recommendation to the end-users over time.
Case 4 - IoT integration
Thanks to Industry4.0 (I4.0) evolution, enterprise mobile applications are now getting hooked up with the Internet of Things (IoT) technology. Mobile devices are not only remaining an endpoint but can also serve as a gateway. They are used to gather and analyze data from IoT devices and send the information block into the cloud for storage and future use.
The application Eco-dashboard is a concrete example in the manufacturing sector of leveraging the value of SAP Cloud Platform, IoT and mobile services to provide real-time information about order status and production status to the end-users. Manufacturers benefits from reduced machine downtime, predictive maintenance and can optimize capacity planning. As the application is fully customizable and configurable, advanced services of SAP Leonardo can be designed and added.
IoT integration is opening new opportunities for all sectors.
To discover more about this solution, read the full features here.
As these new technologies evolve and are used in enterprise mobile apps, we will see more use-cases and gather more information on user experience at workplaces. It will be interesting to see how it impacts workplace engagement, and what values it brings to businesses, their IT departments and of course their employees. For the moment, they have a lot of expectations and promises for the future of enterprise mobile apps.