There are three major truths about analysis in the world today.

  • We live in a global environment on a vastly connected planet. There is more data in the world than we likely realize. According to a Frost & Sullivan 2015 study, “The Global Big Data Market will generate a revenue of over $122 billion by 2025”.

  • Data and information that supports extensive analysis is accessible, automated and comprehensive. F&S states, “90 percent of the world’s data has been created in the last two years alone.”

  • Like it or not, “garbage in is still garbage out” no matter how much data, information and analysis you have at your fingertips.

The right stuff

Author Ron Freidman says, “When data is missing, we overestimate its value. Our mind assumes that since we are expending resources locating information, it must be useful.” Ensure that recommendations and supporting intelligence is based on foundational data that is synthesized accurately, but not endlessly. The lure of colorful visualizations and quick turn analysis is useless if not underpinned with solid basic mechanics for uncovering specific and necessary critical insights.

What decisions keep us competitive? What future trends, drivers and risks underpin market dynamics to give us insight into competitiveness and early warning visibility into probable scenarios and emerging shifts? Regardless of the use of automated analytics in the decision process, a few rules apply.

  • Understand customers: Decisions should be customer-centric whether they are current or future targets.

  • Understand preferences: A number of forces guide customer needs and choices in the business environment.

  • Understand how to fill business environment gaps: Competitive advantage is attained by understanding internal and external forces driving preference now and in the future and filling those gaps better than anyone else.

These are the basic mechanics. Still, applied automated collection of data has had a major, positive effect on managing the insurmountable manual task of market understanding, as long as we apply the foundational rules.

Why cloud-up?

Cloud-based big data methods improve decision capabilities via:

  • Speed because of the ability to collect and synthesize large data sets in real time and create powerful visuals.

  • Efficiency by reducing manual efforts.

  • Effectiveness via decision outcomes that are integrated into business processes.

  • Comprehensiveness in that the variety of tools choices provide tailored, targeted regional analysis.

Analytics promise the possibility that we will soon be able to measure things like disease prevalence, probability of war and other catastrophes, measure emotions and even understand the language of animals.

That said, none of this precludes that accurate outcomes are based on the correctly sourced intelligence targeted at answering the right questions based on the right factors. The real treasure trove lies in your ability keep sound decision methodologies in tack while accelerating the development of insights. Analytics is a powerful engine but the car still needs a driver.