The Big Data Analytics Decision Making Process by Chief Intelligence Officers

“To increase competitiveness (and improved the decision making process), 83% of CIOs have visionary plans that include business intelligence and analytics.” – The Essential CIO (IBM Chief Intelligence Officer study)

big data analyticsDetailed business intelligence required for the decision making process was once collected with pen and paper. Now, however the large amounts of data can be automatically uploaded and analyzed in real time with big data software. This allows for saved time as well as increased decision-making accuracy.

This article provides 5 ways to develop and implement big data analytics into your business intelligence infrastructure. Collecting surveys while out in the field is much more efficient with the use of mobile data collection software and devices. As the saying goes, “knowledge is power.” With big data analytics, more data does not mean just a jumble of numbers anymore. Increased data leads to a better decision making process. Mobile data collection software enables a real-time data upload into the infrastructure as well as real-time data analytics. Continue reading to learn more about the 5 different methods to revamping your system to optimize big data usage and propel your organization into the technology world.

According to a recent IBM-sponsored study, “Using Big Data for Smarter Decision Making”, becoming an analytics-driven organization creates numerous benefits such as the following:

  • Reduce costs
  • Increase revenues
  • Improve competitiveness

BI-Research’s conclusion from the study: “(Those factors are) why business intelligence and analytics continue to be a top priority for Chief Intelligence Officers. Many business decisions, however, are still not based on analytics, and Chief Intelligence Officers are looking for ways to reduce time to value for deploying business intelligence solutions so that they can expand the use of analytics to a larger audience of users.”

The IBM-sponsored study identified 5 major pathways to optimize your data with big data analytics. The methods are as follows:

  • Update systems
  • Improve analytical capabilities
  • Sharpen operational business intelligence
  • Obtain faster hardware
  • Acquire cloud computing (specifically packages that are optimized for large amount of data transfer and storage.)

In addition to revamping your organization’s hardware and software, check out the chain of information throughout your organization to see if there are any holes in the decision making process. Big data analytics and mobile data collection can only help so much because the structure of the organization plays a vital role in information transfer. As the Chief Intelligence Officer, understanding the flow of information throughout the organization is critical. The following is an information supply chain diagram from the above-mentioned BI Research study.

“ Big data used to be a technical problem. Now it’s a business opportunity.” – Big Data Analytics by TDWI (The Data Warehouse Institute) Research

According to a 2009 TDWI survey, the following statistics are provided. These states demonstrate the growing investment into big data by Chief Intelligence Officers.

  • 38% of surveyed organizations use advanced analytics
  • 85% of surveyed organizations said they would be practicing it within three years

TDWI provides several of the innumerable reasons why Chief Intelligence Officers are utilizing big data analytics:

  • Better-targeted social-influencer marketing (61%)
  • Customer-base segmentation (41%)
  • Recognition of sales and market opportunities (38%)
  • Develop definitions of churn and other customer behaviors (35%)
  • Understanding of consumer behavior from clickstreams (27%)
  • Accurate business insights (45%)
  • Understanding of business change (30%)
  • Better planning and forecasting (29%)
  • Identification of root causes of cost (29%)
  • Detection of fraud (33%)
  • Quantification of risks (30%)
  • Market sentiment trending (30%)
  • Automate decisions for real-time business processes such as loan approvals or fraud detection (37%)

Obstacles that Chief Intelligence Officers face when implementing big data analytics:

  • Staffing issues (46%)
  • Skill-related barriers include the difficulty of architecting a big data analytic system (33%)
  • Problems with making big data usable for end users (22%)
  • Issues arise when the current database software lacks in-database analytics (32%)
  • Scalability problems with big data (23%)
  • Cannot process analytic queries fast enough (22%)
  • Cannot load data fast enough (21%)

Check out COMMAND Mobile to learn more about how you can adequately equip your organization for big data analytics through mobile data collection. Use field surveys and mobile data collection devices to gather the data and then utilize big data analytics for increased business intelligence information analysis and increased decision-making tools. Mobile data collection software truly has he potential to transform your organization.

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About DeAnna Davidson

DeAnna Davidson is a proven technologist and business leader who is passionate about the power of mobile computing to revolutionize a business or industry, and dedicated to helping organizations use mobile, wireless, and web technologies to their advantage.

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