Understanding the data mountain means getting smarter

Understanding the data mountain means getting smarter
By Stephen Leonard, IBM’s chief executive in the UK and Ireland

Published: May 10 2010 17:28 | Last updated: May 10 2010 17:28

Modern information is unlike any that has gone before – it is voluminous, extremely fast and widely varied in format.

It comes structured and unstructured; from within a company and without; it arrives on a daily, hourly and real-time basis.

At the same time, powerful tools using advanced mathematics combined with vast computing power can start to integrate financial data with information about customers, supply chain, and workforce capabilities.

And in a world of intelligent objects, greater granularity is making information even harder to fathom. Containers and pallets are tagged for traceability – as well as medicine bottles, poultry and fruit, adding more detail to the information ecosystem.

This makes using information a daunting task. But it means the business of making decisions is shifting from intuitive and experiential to fact-based, which should lead to better decision-making.

To make progress, however, each enterprise needs to look at how prepared it is to help integrate, standardise and analyse the information flooding in – a real potential problem.

Working harder and longer is not the answer. The key is working smarter, and that means having the right information and insight to drive smarter business outcomes.

Working smarter means front line business leaders know where to find the new revenue opportunities and which product or service offerings are most likely to address each market requirement.

It means business analysts can quickly access the right data points to evaluate key performance and revenue indicators in building successful corporate growth strategies. And, it means corporate risk and compliance units can recognise regulatory, reputational and operational risks before they become a problem.

Until now, acquiring, configuring and fine-tuning a system to analyse information to solve problems and uncover breakthrough insights has required technical skills out of reach for many companies.

Now, many organisations are embracing analytics technology to gain business advantage and better serve their clients. Our research shows that one in three business leaders frequently makes critical decisions without the information they need; 53 per cent don’t have access to information across the organisation needed to do their jobs.

There are, of course, challenges in undertaking analytics-driven transformations. First, and most critical, is data quality.

While 100 per cent accurate data is impossible in enterprises, it should be remembered that analytics is a journey, with successive iterations of the analytical cycle providing the gradual improvements required.

Enterprises too often assume analytics is a highly technical or a quantitative subject that should be left entirely to technology teams.

In fact, successful analytical transformations are driven by the core business leadership. The chief executive or chief operating officer should be driving analytics initiatives across the enterprise. They should ensure that every tool, technology or statistical technique becomes part of achieving the larger business goal.

A further challenge comes from trying to meet every business challenge using analytics. It is important to ensure the business does not lose confidence in the initiative by keeping the rewards incremental and demonstrating the impact of analytics at every stage. Once the basic framework is in place, value can be delivered incrementally and periodically.

For the intelligent enterprise, the future means knowing, not guessing. It means taking information and turning it into insight that can enable business leaders to make real decisions, rather than simply hope for the best.

Analytics has applications that range from helping financial markets to perform better and recognise fraudulent behaviour, to helping doctors make better diagnosis and treatment decisions.

It can also help police in crime reduction, by aggregating street level information across myriad sources. Wherever there are huge amounts of data, analytics can determine the best course of action.

Forward thinkers have, for some time, been drawing on the potential of the technology that is proliferating in the physical world and being embedded in all kinds of systems, interconnected and infused with intelligence.

In the coming decade, these ”smart” pioneers will have at their disposal new analytics technology that will become an increasingly vital source of intelligence, influence planning and take informed decision-making to new levels of sophistication.

Leaders are also beginning to acknowledge that smarter systems sometimes require change in economic and social mindsets. For example, societies may need to shift long-held views on citizen privacy, as systems generate (and share) far more personal data than before.

Societies need to ask themselves whether the benefits of smarter systems outweigh perceived civil infringements, changes in lifestyle or even up-front investment. Welcome to the “decade of smart”.

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