C-level Execs: Big Data Means Big Value

Big data and analytics are top corporate, top-three corporate or top-10 corporate priorities in their organizations’ strategic agendas, according to 65% of 1,469 C-level executives taking part in a recent

Forty-four percent of the respondents say that they’re generating more value from big data and analytics than their competitors, while only 28% say the same for social tools or technologies.

An even larger share of executives in healthcare and pharma (56%) and business-to-consumer companies (50%) say the same about big data and analytics.

Companies are focusing on using big data and analytics to improve their overall performances in a number of functional areas including:

49% for customer insights, segmentation or targeting
39% for budgeting, forecasting or planning
37% for operations, service delivery or supply chain management
33% for customer service and support
30% for performance management and transparency in internal operations
28% for new product strategies
21% for pricing

The executives say their companies should focus their efforts on using data and analytics to generate these insights. Still, the executives report several challenges to taking advantage of the potential payoff from big data and analytics including organizational structures and shortcomings in their infrastructures and systems, which can be too inflexible to take advantage of the large volume of data flowing into their companies.

For the companies that can overcome these challenges, the returns could be immense, with companies gaining or losing market share based on their capacities to exploit big data, according to Michael Chui, a senior fellow at the McKinsey Global Institute, the research arm of McKinsey & Co. McKinsey has projected that the healthcare sector alone could reap as much as $300 billion in value from the effective use of big data, including $200 billion in reduced spending.

McKinsey suggests that companies take these steps to overcome the barriers to using big data and analytics effectively to drive business value:

Study possible organizational hurdles like silos of marketing, product development and IT functions before launching new analytics projects. Consider creating flexible team structures and engaging outside resources for collaboration;
Focus on building and acquiring the skills necessary to carry out an analytics agenda. Develop homegrown skills wherever possible and be creative in finding other talent to fill in those gaps;
Seek to foster active participation from IT leadership for big data and analytics projects.

Next steps:

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