In the new business world, smart data analysis can be the smart executive’s crystal ball.
By Rob Ashe, general manager, business analytics and performance management, IBM
What if the financial industry could capture enough foresight on the right trends and indicators to pinpoint the next potential Ponzi scheme before it unravels? What if scientists could better predict infectious disease outbreaks such as H1N1? What if a brand manager could easily determine his most profitable customers or better detect fraud to help his business save operational costs?
It might seem like guesswork best left to the realm of industry pundits and scientists in lab coats. But gaining real foresight about trends, sentiment and customer churn — the kind of insight that can help modern businesses cope with tough economic times and simultaneously deal with the deluge of data they face — is achievable today.
The problem is most companies are drowning in data and information: Each day more than 8 times the information in all U.S. libraries is being generated. By next year, the amount of digital information will be equivalent to a stack of books from the sun to Pluto and back.
Each week businesses waste 5.3 hours per employee due to inefficient processes. An average company with 1,000 employees spends $5.3 million a year simply to find information stored on its servers. The consumer products and retail industries lose about $40 billion annually, or 3.5 percent of their sales, due to supply chain inefficiencies. Similarly, the world’s ports are cluttered by empty containers. In North America alone, it is estimated that between 20 and 22 percent of the total port volume is containers with nothing in them. 59% of businesses do not have access to information across the value chain that would be most useful to them for decision-making.
Business as usual isn’t working.
But some leading organizations are already exploiting new predictive analytics technology that instantly parses diverse, unstructured and disconnected pieces of data – whether the data comes from blogs, email, podcasts, customer comments or videos – for very fast, accurate and insightful decisions based on relevant and timely information.
Real-time business smarts
They are gaining new intelligence into how best to manage spending that is for the benefit of periods beyond short-term horizons, how to improve profits by understanding which customers are most profitable and retaining them and how to reduce risk by limiting exposure to chronically late suppliers or the impact of fluctuating market prices for supplies. They are quickly able to capture insights from time-sensitive information such as the health of business supply chains, marine ecosystems, business operations, customer sentiment or financial trades.
For example, DHL Worldwide, a global air and ground express industry leader, is now able to analyze more than 30 million customer records in just seconds vs. hours while reducing system maintenance costs and improving operations and customer profitability.
The Marine Institute of Ireland is now able to better understand fragile marine ecosystems. Developing large volumes of acoustic signal data from hydrophones mounted on buoys in the ocean, the platform is analyzing echolocation sounds of sea life, which can be used for location, range and object identification. This data is then correlated into useful information such as species identification, population count and location.
Using streaming analytics and the latest supercomputer, scientists at IBM ibm Research collaborated on a project with TD Securities to achieve a 21 times performance improvement on the volume of data consumed by financial trading systems.
With modern technology these organizations are using information in entirely new ways to improve performance and gain new insight about their business and the world around them.
By turning ‘what-if’s’ into “what we know,” and “what will be” smart companies are gaining the insight required to improve productivity and properly fuel innovative 21st century growth.
Ashe, former CEO of Cognos, is currently the general manager of business analytics and performance management for IBM’s Information Management group, which develops software that enables organizations understand their performance and make informed decisions.