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Gartner: 3 Actionable Analytics Trends Driven by Big Data, Mobile, Social

As a precursor to its upcoming conferences in the US and Australia on actionable analytics, Gartner has just published a new research report that identifies three trends that will push users towards analytics adoption in the medium term.

Analytics Adoption Drive

The report, "Actionable Analytics Will Be Driven by Mobile, Social and Big Data Forces in 2013 and Beyond," predicts major changes in the workplace that will see more and more users taking to analytics over the medium term.

It also identifies the three emerging technology spaces of social, mobile and big data as the big drivers for analytics adoption in the enterprise over the coming years, as more enterprises struggle to manage the data created by this terrible threesome.

It seems that despite all the talk around the use of analytics and all the good things vendors are promising, only 30 percent of the potential users in enterprises are using analytics tools, despite the fact that those tools are largely being sponsored by CIOs.

However, the report also notes an interesting trend that should be of considerable interest to vendors — as enterprises invest in software that make analytics tools invisible, more and more users are turning to them. In fact, there is a lot to be said for this theory surrounding many other technologies we talk about on a daily basis. If users don’t have to think about using the tools themselves, they are more likely to use them.

Analytics, Business Users

In this respect, we are talking about business users rather than IT users.

In the face of accelerating business processes and a myriad of distractions, real-time operational intelligence systems are moving from "nice to have" to "must have for survival." The more pervasively analytics can be deployed to business users, customers and consumers, the greater the impact will be in real time on business activities, competitiveness, innovation and productivity,” said Rita Sallam, research VP and report author at Gartner.

The challenge then — or at least another challenge on top of all the other challenges facing business intelligence and analytics professionals — is to encourage adoption by users. There are three ways of doing this:

1. BI transparency

To make analytics more transparent, business intelligence and analytics professionals should develop easy-to-use, natural language interfaces, enabling easy exploration of data through embedded analytic applications.

There is an interesting development here in the shift from systems that primarily pull together content and structured data, towards systems that can relate structured and unstructured data, reason, learn and offer findings and advice.

As big data becomes the rule rather than the exception, more and more systems are offering enterprises the ability to take in information from more natural mediums like written notes, or spoken questions. And Gartner has found that the more these tools are hidden from the end user, the more they are used and the more actionable information will be made available to enterprises.

To cover-up the existence of analytics tools, enterprises will have to use a great deal of computing power, and increasingly complex information management systems.

The growing volume of real-time data, and the reduced time for decision making, are driving companies to implement real-time operational intelligence systems that make supervisors and operations staff more effective.

2. Data volumes, real-time analysis

As more and more data arrives in real-time from news feeds, email, tweets and other unstructured data sources, the time that is available to users to make decisions based on data is decreasing.

While that may be daunting, all this information is in digital format so can be machine read, offering enterprises that realize this is happening the possibility to implement systems that can offload even data capture, filtering, mathematical calculations and pattern detection enabling users predict events.

Where the cause and sequence of events are understood, leading indicators can be used to predict situations of threat or opportunity before they occur. Where this is not possible, they can be used to reduce the lag time between events and responses.

3. Competition, cost and regulatory pressures

As competition for markets gets fiercer and the pressure to reduce costs increases, with more and more regulatory regimes, businesses are looking for better ways to help them make smarter, repeatable decisions that will also reduce personnel costs. The result is a move towards the deployment of decision management software in more areas and to use ever increasingly sophisticated forms of these technologies.

Decision management software is software that is on-demand when humans or computers need computational support to make decisions, with some vendors now even providing intelligent decision automation.

Solutions architects should work with business analysts, subject matter experts and business managers to indentify what kinds of decisions need to be made and which are repeatable. This will not only save money, but also conserve time and energy for the kinds of decisions that computers cannot do.

There is a lot more in this report that would be useful for analytics and business intelligence experts, as well as those enterprises that are looking at their options in this space.

 
 
 
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