It is impossible to recover lost time. Once a moment passes, it’s gone. Time is especially at a premium in the business world, so end users can’t waste it sorting through a sea of mobile data to find the information they need.
Mobile data analytics grants IT the power to deliver the right data to the right users at the right time. A salesman, for example, might need to know what will happen if he changes the price of a product. If he can access those results in real time, he can quickly communicate the effect to a potential customer.
With a mobile data analytics strategy, IT can send users role-specific data so they can quickly see the information they need to get their work done anywhere. Keeping the data specific is even more important on mobile devices than traditional desktops because the smaller screens can only display so much information at once.
To deliver role-specific data to mobile users, IT needs real-time data stream processing, which requires big data products. Even with the right product in place, however, IT needs to know what data is most important to process. To achieve that, admins should shadow users to see how they work over the course of a normal day. How do they use apps? What type of data do they access most? What devices do they use, and what tasks do they do with them? Then they can start to deliver business insights to streamline users’ workflows.
Companies can also use mobile data analytics to drive customer-facing business value. Contextual data, such as a customer’s location and previous transaction history, for example, can help organizations predict how that customer will behave in the future. If a customer enters a certain location, the company can push a message to them about a sale in the area.
Mobile data analytics is no time machine, but it can help IT and end users be more productive with their time, which can pay off with major dividends.