CSG Blog

Top 8 Changes Shaping the Future of Business Intelligence

Written by Mark Peterman | Jan 12, 2017 11:10:07 PM

BI is one of the most rapidly evolving technologies on the planet. With a highly competitive market, companies look for any means possible to gain competitive advantage. The number of professionals using descriptive and predictive analytics grew by 20% in one year alone
(
Forbes, 2019).

This arms race drives BI consultants to push the boundaries of their technologies – boundaries that are ever-expanding thanks to both improvements in computing power and clever lateral thinking.

With 79% of enterprise executives agreeing that companies that do not embrace Big Data will lose their competitive position and could face extinction (Forbes, 2018), what can we expect from the game-changing BI solutions of tomorrow?

 

1. Predictive analytics with ai and machine learning

As both artificial intelligence (AI) and BI solutions become more advanced, AI and predictive analytics will become more prevalent. Machine learning will more quickly be able to understand a company’s habits and patterns and wil be entrusted with making an increasing amount of increasingly difficult decisions. Machine learning will be able to help create forecasts, predict customer turnover, identify new customers, and more.

Despite its ever-increasing capabilities, Harvard Business Review reports that only 8% of firms have core practices that support the adoption of AI throughout the organization (2019). AI is a clear area
of opportunity for gaining a competitive edge.


2. Centralized to localized: separating reporting and IT

Historically, BI has been centralized to an IT department. An end user requests a data report and waits for an answer. The timeframe to get the answer is a function of where this request fits on the IT priority list, not so much based on the needs of the requestor. In recent years more companies have moved away from a centralized system for reporting, with more self-service systems favored. These systems are localized to the end user with the help of desktop, mobile and cloud applications. Company IT departments will continue to morph from a provider of data to a facilitator of localized BI use.


3. Accessible to everyone

Following on from the localization of a company’s BI solution, the focus on self-service BI operation will mean that anyone, regardless of technical ability, will be able to comfortably utilize BI. This is crucial considering that 70% of users in organizations lack a statistical background and, in spite of this, do not use BI tools that could help them process data (BARC, 2017).

In order to maintain competitive advantage, companies need to be able to equip employees to act as quickly as possible on real-time data. Self-service BI applications make it easier for every user to make those important data-informed decisions. The use of self-service BI applications and analytics will only continue to grow.


4. Going mobile

The perfect BI solution is one that provides answers to your queries anywhere, at any time. Offering a BI solution that is able to be utilized on-the-go will become ever-more important, as digital technologies continue to move from the desktop to the phone and tablet. The upsurge in businesses adopting "Bring Your Own Device (BYOD)" policies will require any solution be universally compatible with all devices.


5. Data discovery and visualization

The days of painstakingly searching mountains of data for important information may soon be over. In the future, relevant data will find you, not the other way around. Conventional BI will fade away, replaced by a service that offers up relevant and interesting data on demand, or at regular intervals. This data will be offered in easily consumable visuals, ready to be digested and acted upon in an instant.


6. Taking advantage of the cloud

The low cost storage, scalability, and expansion that the Cloud provides is perfectly suited to the data volume challenges posed by BI solutions. Moving the data off-site can also lead to better access, including mobile.


7. Personal analytics for self improvement

Just as personal fitness trackers aim to improve a wearer’s understanding of their performance, so too will BI data be used for self-improvement of a user’s professional performance. The once-a-year, KPI-driven performance review may become a thing of the past, with real-time information guiding users to achieve the greatest productivity possible. Putting their work into the context of the overall value of the company improves motivation. Employees can identify with particular KPIs, track them over time, and gain an understanding of how their contribution impacts the company as a whole.


8. More business decision reviews

Perhaps the core aim of BI is to gain a deeper understanding of a company’s situation in order to improve its decision making. According to data from Qlik, only 23% of organizations check the outcomes of their business decisions routinely. In order to increase this number, future BI solutions will offer ‘decisions’ as a metadata type, making them incredibly simple to analyze.

 

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