With the current financial crisis showing no signs of abatement, economists agree that "We are not going to have an economic recovery, but an economic ‘reset.’"

Extraordinary times call for extraordinary measures, and increasing market pressures, tightening budgets, and economic uncertainty dictate that organizations re-examine everything — their strategies, operations, budget allocations, and internal IT processes.

"Cutbacks" is the new word resounding across boardrooms. New pressures are forcing companies to cutback on spending in every sphere from R&D to sales and maximize the utilization of available resources. And, this trend, which is fast catching up across industry sectors, does not appear to be a reactive short-term strategy but rather a permanent change for the better. In their quest to streamline processes and focus on critical business drivers, organizations are increasingly turning to consolidation and integration of available resources and heightened use of analytics and forecasting.

Most organizations have vast reams of historic data and critical information scattered over different silos, systems, and formats at any given time. The advancement in technology and data collection methods has led to a further surge in information, leading to more and more fragmentation of data. Poor integration of such valuable information only invites costly errors, redundancies and overlaps, and exposes businesses to greater risks and losses. Having a limited view of the market trends and consumer behavior data makes the execution of marketing decisions a high-risk proposition. So, you could say that most organizations, with the exception of a few, had up to quite recently been making important business decisions with blinders on.

A new way of working demands a new way of organizing. The need of the hour is data integration or consolidating and managing, as part of one large repository, pre-existing as well as current information from multiple sources — across domains, functions/silos, and industries. Having a robust up-to-date data integration platform that houses all relevant studies and data — from market sales, equity studies, to consumer data on preferences and needs — will enable decision makers to quickly access information on a key variable as well as query against existing data from past studies to gain meaningful insights.

Let’s take one sector, say R&D that deals with new product development, to assess the benefits of data integration. New product development is often a laborious time-consuming and expensive process involving product engineering and reengineering that can take weeks to months, and sometimes, years. Be that as it may, new product development, which accounts for approx. 15% to 30% of annual sales of some organizations, is the lifeblood of any organization wanting to remain competitive. And for organizations to maintain their market shares, it is necessary that new product development be in sync with customers’ changing needs and tastes. To this end, organizations devote huge chunks of time and budgets to new product development.

Effective data integration could mean the difference between commissioning a year-long study versus a month-long study. Data integration would help better monitor key variables such as trending patterns and consumer behavior across geographies, which would alleviate the need to conduct more studies and surveys, bringing about reduced spending on R&D and minimization of redundancy. What’s more, retrospective analysis of qualitative studies will help draw actionable insights, enabling organizations to react more fluidly to changing market trends.

To sum it all, data integration or creating a consolidated repository or data warehouse spells — more for less.

By Brian Welsh