Proceedings

Traditional analytical tools claim to have a total integrated view of the enterprise or
business, but they analyze only historical data—data about what has already
happened. Traditional analytics help gain insight for what was right and what went
wrong in decision-making. Today’s tools merely provide rear view analysis.
However, one cannot change the past, but can prepare better for the future and
decision makers want to see the predictable future, control it, and take actions today to
attain tomorrow’s goals.
Predictive analytics employs both a microscopic and telescopic view of data allowing
organizations to see and analyze the minute details of a business, and to peer into the
future. Traditional BI tools cannot accomplish this functionality. Traditional BI tools
work with the assumptions one creates, and then will find if the statistical patterns
match those assumptions. Predictive analytics go beyond those assumptions to
discover previously unknown data; it then looks for patterns and associations
anywhere and everywhere between seemingly disparate information.
1.2 The business value of predictive analytics
Predictive analytics can help companies optimize existing processes, better
understand customer behavior, identify unexpected opportunities and anticipate
problems before they appear. There is no doubt that predictive analytics can yield a
substantial ROI. Nevertheless, there are many organizations that have yet to employ it
- according to a survey conducted in august 2010 by TDWI (The Data Warehousing
Institute) only 30% of organizations have fully or partially implemented predictive
analytics, while more than 50% were still exploring or have no plans about it.
We can list a lot of reasons to justify that a company needs predictive analytics; these
are only some of them:
• Get a higher return on data investment
• Find hidden meaning in data
• Look forward, not backward
• Deliver intelligence in real time
• Discover unexpected opportunities
• See assumptions in action
• Empower data-driven decision making
If that’s so, why we don’t find predictive analytics wide spread in most of the
organizations? Many IT managers and some business managers understand the value
that predictive analytics can bring, but most are still wondering where to begin.
Analyzing data is not easy. Finding people who have sufficient knowledge of the
business processes, underlying data structures, and data access and analysis tools is
challenging. Also, preparing organizational data so that business people can access
and trust it is difficult, time-consuming and expensive. The analytical tools – like
spreadsheets, desktop databases, reporting tools – are not so evolved and haven’t
changed much in the past years. But there are many new analytical tools (like visual
discovery and workgroup BI tools) and technologies designed to improve the
productivity of business analysts and preserve information consistency throughout an
organization.
~ 1117 ~