Posted by Karen
August 25, 2014
The ability to mobilize BI data – to deliver real-time information via smart phones and tablets – will likely be the most significant contributor to improved BI adoption in 2014. Although the adoption rate for mobile BI is still relatively low, the rate is growing faster for mobile than for other technologies and has not nearly reached full potential. Gartner predicts that by 2015 mobile devices will be exclusively relied upon for insight delivery by over 50 percent of mobile BI users and will grow overall BI users by 20 percent.1 This is not really surprising considering that mobile BI provides significant benefits including:
Employing a BI tool that offers a mobile solution with the most advantageous features for your business will result in more users and help promote a culture of data driven decisions. Some mobile capabilities to look for in a BI vendor include:
Access and Authoring: users want an “author once, consume anywhere” experience as well as interactive consumption of BI with view, refresh, sort, filter, and drill capabilities.
Consistent experience across devices: mobile apps should provide familiar content interface, so users can quickly find the information they need.
Touch-optimized controls and views: look for touch optimized views and controls with dynamic scrolling to give users the ability to quickly and easily access data.
Security: mobile device management (MDM) systems let customers grant authentication at the device level in addition to supporting user names and passwords. MDM also supports remote wipe and lockout in the event a device is lost or stolen.
As the market expands, cloud support in BI solutions becomes a more popular feature. A cloud infrastructure offers beneficial features for many businesses: easy scalability; lower start-up cost due to the reduction or elimination of expensive hardware; faster implementation; and reduced administrative overhead. Cloud based BI also provides access to analysis within minutes, rather than the weeks it takes IT departments or power users to set up inquiries and reports. Collaboration is an associated benefit to the cloud as it facilitates sharing with people both inside and outside of your organization. Although these features can benefit all types of organizations, cloud BI is particularly applicable to smaller businesses with more limited resources in terms of budget and staff.2
However, be aware that BI in the cloud is not the best solution for every organization. For instance, it would not be recommended for businesses with extensive legal requirements with respect to data auditing.3 Secondly, BI in the cloud is not necessarily the least expensive option in every circumstance. After a certain point, cloud hosting can be less cost effective than on-premise. Therefore, organizations should be sure to evaluate all related costs including vendor licensing, people costs, scope of project and overall cost of ownership. Finally, ideally everything should be browser based in a cloud solution, so watch out for cloud based BI services that require client side software to connect to their data in the cloud.
After Mobile BI, embedded BI in conjunction with cloud BI solutions will likely have the most significant influence on the BI market in 2014. Together these two features open up the market to a previously unattainable audience.
The ability to integrate BI capabilities into software allows business applications to transform transactional data into highly interactive dashboards and analytics that help people make faster more informed decisions… on their own. Demand for embedded BI continues to grow as dashboards, reports, and interactive visualizations become market requirements in most software segments.
Customer relationship management solutions have led the way in the utilization of embedded analytics. It is anticipated that departments that have typically lagged such as retail environments will begin to employ embedded BI in the not too distant future.
Benefits of using an embeddable option include:
Data Scientists may have been sexy in 2013, but they’re losing their appeal as data science in 2014 is trending from the “specialists” to the “masses”. Business users are becoming more familiar with data and are increasingly required to have BI tools to make data based decisions. With the primary use of BI shifting to business users, vendors are specifically targeting the business users for new products. Today it’s possible to find many tools that can help the most inexperienced user quickly begin doing sophisticated analysis and produce great visualizations from many different types of data. The “masses” now have access to easy- to-use data visualization tools such as Tableau.
IT’s role in BI is changing from that of traditional gatekeeper, which has often impeded the process of delivering much needed information, to facilitator, which will provide business users with the means to consume data at the rapid pace they require. Forbes contributor Ben Kepes emphasized the transformation of IT’s role in 2014 in regards to emerging BI applications:
“Applications that were hardwired with IT and Data Sources were designed for the few, rather than for the needs of the broad employee base. Applications that will deliver value into the future are those that bring context, processes and people together often to make data-driven decisions.”4
An Economist Intelligence Unit survey revealed that the use of data is gaining a foothold within all departments in organizations. A strong link was established between the successful exploitation of data and financial performance – evidence that focus on data can transform businesses.5
This means businesses will be seeking BI solutions that not only capture and manage data but are also able to exploit data for business benefit without needing an army of coders. End users rather than IT will largely dictate the pace and the specific BI tools that are most relevant to the enterprise, with applications created with an ease of use that seemingly belies the IT department.
The trend to self-serve business intelligence technology continues to transform the landscape from a sluggish, onerous process used primarily by large enterprises to a more flexible, agile process that can be used to great advantage by both SMBs (small – midsize companies) and individuals. The evolution towards self-service is evidenced by the multitude of dashboards, interactive visualizations, search, and other discovery tools specifically designed for business users. Because there are so many options, the 2014 Gartner Magic Quadrant for Business Intelligence and Analytics Platforms is extremely helpful for companies seeking the best BI solution for their business. Ubiquitous access to data is becoming a key business priority and certain to increase in importance. Businesses are demanding the ability to support a multitude of data sources, integrate them with minimal effort and access analysis results via a multitude of channels.
In today’s era of “big data” and fierce competition, organizations need to go beyond the analysis of historical data to compete and thrive. The organizations that use predictive analytics technologies to look forward and be proactive will be the ones to sustain a competitive advantage.
How does Predictive modeling work? It identifies and mathematically represents underlying relationships in historical and current data in order to better understand the data and make predictions, forecasts or classifications about future events. Predictive models are used to better understand customers, products and partners and to identify potential risks and opportunities for a company.
Predictive analytics allows executives to anticipate what is about to take place and, thereby, make better decisions, with greater consistency and lower costs. Top areas in which predictive models are generating significant value for organizations include marketing, customer retention, pricing optimization and fraud prevention. The list continues to grow as the number of successful applications continues to increase.6
Driven by the “Big Data” phenomenon, more advanced data analysis technologies and the increased number of effective applications, Predictive analytics is experiencing a surge in adoption and has not yet come close to being fully exploited.
BI vendors have incorporated storytelling capability in their products to provide a better way to communicate ideas and insights using data. The use of data stories is growing in popularity as organizations realize that data analyses and dashboards invariably require context to reveal the valuable insight. Barraged with dashboards teeming with analytics, executives often struggle with data-driven decision making because they don’t know the story behind the data. Data stories help people gain meaning from vast amounts of disparate data to facilitate a decision making process. Data is powerful; data with a good story is unforgettable.
The dynamic arena of business intelligence continues to advance and improve. The vendors that adapt better and faster to this evolving business intelligence environment will flourish. Similarly, the businesses that make the best choice of BI technology – the best fit to benefit their operation – will succeed.
1. Daniel Yuen, Gartner Group. Mobility and Real Time Dashboards will Make Business Intelligence more Pervasive in 2013. Forbes.com. https://www.forbes.com/sites/gartnergroup/2013/02/26/mobility-and-real-time-dashboards-will-make-business-intelligence-more-pervasive-in-2013/
2. Joe McKendrick. Business Intelligence advances into the clouds but with Some Caveats. Forbes.com https://www.forbes.com/sites/joemckendrick/2013/08/11/business-intelligence-advances-into-the-cloud-but-with-some-caveats/
3. Ellie Fields, Tableau. Why Business Analytics in the Cloud. Tableausoftware.com. https://www.tableausoftware.com/sites/default/files/media/whitepaper_why-the-cloud.pdf
4. Ben Kepes. What Analytics Looks Like in the Modern World. Forbes.com. https://www.forbes.com/sites/benkepes/2013/11/26/what-analytics-looks-like-in-the-modern-world/
5. Fostering a Data Driven Culture, A Report from the Economist Intelligence Unit, The Economist.
6. CGI. Predictive Analytics White Paper. https://www.cgi.com/sites/default/files/white-papers/Predictive-analytics-white-paper.pdf