Mobile Business Intelligence (BI) extends the decision-making and analytics capabilities of conventional BI beyond the office. The ubiquity of smartphones and tablet devices (such as iPads), in addition to a growing number of vendors, mobile platforms, and applications, has rendered this form of BI one of the most viable means of accessing and extracting value from data today. Depending on which app is selected and integrated with which particular device, Mobile BI offers all of the capabilities and features of traditional BI, plus additional benefits such as displaying analytics on other portable and desktop devices in any location.
However, the nature of Mobile BI presents a set of considerations that are distinct from enterprise versions. The principle concern is to select an appropriate app and mobile device that best integrates with existing BI software. All of the traditional concerns for mobile BI, such as issues of security and platform extensions with current BI tools, have largely been addressed. Users are still responsible for determining what sorts of data will be analyzed most frequently via Mobile BI, while evaluating platforms and devices to determine which is most compatible. Although all forms of BI are accessible via mobile devices, some data is better visualized than others, depending on the portable device and app selection.
Modernizing Mobile BI
Around the turn of the millennium, Mobile BI was severely limited in its utility. It required a dedicated server and was difficult to integrate with existing tools. With the development of tablet devices and smart phones in more recent years however, BI vendors began supporting mobile devices so that they served as extensions of conventional tools on the same server. Querying, reporting, visualizations, and animations are shared between conventional and Mobile BI.
Other than the proliferation of mobile devices in recent years, the most significant factor to influence the rapid rate of adoption of Mobile BI is the virtual elimination of security concerns for it. Most forms of Mobile BI offer security at three respective levels: the device, the network, and at the point of transmission. Handsets have security features such as firewall and antivirus software, full disk encryption and passcodes. Secure socket layers and virtual private networks help fortify security at the network level, while the same security clearances required for BI tools in the office are required for mobile devices as well.
Operational and Business Value
Aside from the convenience of accessing BI as needed in any location mobile devices are supported, Mobile BI can assist real-time decision-making for those who need it most in the field – such as as sales representatives. Access to information from remote locations helps to complete transactions more expediently, increase productivity, and decrease administrative and material costs. Mobile BI is ideally suited for informing short-term decisions, which makes it valuable for analyzing operational data and flexible metrics related to pricing.
Although Mobile BI analyzes the same data that traditional BI does, it comes with a variety of features that significantly enhances its use. In addition to providing filters and alerts, Mobile BI has become increasingly characterized by intuitive graphical user interfaces that can accommodate sophisticated levels of visualization. Whereas early Mobile BI apps could only access previously canned reports, current tools can generate new queries. Particularly competitive apps like those from Logi Analytics (LogiXML, Logi Info, Logi Ad Hoc) enable users to do so without code, simplifying the querying process, and eliminating input from IT. Apps integrate with all of the conventional sources of data such as relational databases, warehouses, CRM and ERP, and provide a bevy of dashboards, reports, graphs and grids which can be rapidly deployed many times.
Other features found in products like MicroStrategy Mobile and others specifically pertain to mobile devices, such as integration possibilities with email, calendars, phone lists, and other apps on the mobile unit itself. Those that incorporate HTML 5 have a plethora of offline capabilities, which may be enhanced by IT personnel. The sensor-based querying feature is a distinct advantage over traditional BI, with which users can scan barcodes to generate and change queries. Queries can also be facilitated via convenient voice to text and voice recognition functions. Several solutions accommodate ad hoc querying and reporting, which can be updated via GPS. Mobile platforms can support a variety of Mobile BI apps, while key stroke shortcuts and multi-touch gestures facilitate ease of use.
Mobile BI utilizes web browsers on portable devices to access conventional BI tools. Costs typically revolve around purchasing devices, a BI solution, mobile apps, and whatever training and design assistance is required. Most BI vendors have their own mobile apps that extend enterprise service remotely via interfaces that are similar to the desktop version. There may be additional licensing fees for desktop users to access Mobile BI. Other apps have been designed to integrate with a variety of BI platforms. Although not all apps can integrate with existing BI tools, popular BI vendors are supported by a number of different apps. There are more limitations on the type of mobile device that a particular app can work with, as some are designed only for particular manufacturers or for certain smartphone operating systems.
Other selectivity concerns relate to the design of Mobile BI, which is considerably different than that for the desktop version. Limitations related to screen size, memory capacity, and processing speed/capacity of mobile devices influence the way reports will look – which affects their overall utility. Too much information may appear clustered on smaller devices. Mobile BI design should ideally limit the number of objects on the screen or dashboard to increase usability. A chief determinant in achieving this objective is the process of data categorization, in which organizations specify which types of data will be accessible to which individuals and design tools for apps accordingly.
Although Mobile BI can handle all of the functions of desktop versions, the presentation of data on individual handsets factors heavily into what data is most advantageous to base designs around. There is a direct correlation between the type of mobile device an app supports and the type of data that it works best with. The primary goal in selecting Mobile BI solutions is to standardize data, yet the particular form of data analysis most frequently used factors into what sort of device is desirable. Lengthier data mining processes tend to work better on bigger tablets, while smartphones are ideal for scanning data and making quick decisions relating to real-time information for pricing and operations.
Adoption rates of Mobile BI are projected to increase in the very near future. How rapidly they do so largely depends on the effectiveness of implementing these platforms with current BI solutions. Vendor support on both ends (from the mobile and enterprise community) is already there. Most tablet devices present functionality and usability similar to desktops, while certain uses of smartphones (including scanning and GPS incorporation) make them viable options as well.
In that respect, the trend towards Mobile BI merely reflects the larger movement towards the simplification of BI. Cloud-based Data-as-a-Service options are another integral component in moving BI out of the realm of IT and into the daily world of operations and business professionals. Many of the features of Mobile BI – alerts, ad hoc tools, trends related to key performance indicators – increase usability, particularly in products in which code is not required for design.
Although such platforms and applications are increasing, the primary challenge in utilizing Mobile BI today lies in facilitating a design that optimizes visualization, reporting, and other key tools on the mobile device a particular solution supports. As more solutions allow such tools to be manipulated without the need of an IT team, the variety of data types which can be presented optimally (per device) should only increase, further spurring adoption rates. The potential for enhancing decision-making and incorporating data to generate business value will become significantly more accessible.