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Data – the “new oil”

Data – the “new oil” 02/09/2019

Data is not called the “new oil” for nothing.

Adopting a data-centric approach enables organisations to better understand their markets, products and customers. It is the key to turning previously uninformed “hunches” into highly qualified, evidence-based, precise, data-informed decisions.

Yet it’s not easy to turn raw data into something useable. Analysis by NewVantage Partners Big Data Executive Survey shows enhancing data maturity is painfully slow, with most failing in their efforts to become data-driven:

  • 72% of survey participants state they have yet to forge a data culture
  • 69% state they have not created a data-driven organisation
  • 53% report they are not treating data as a business asset
  • 52% admit they are not yet competing on data and analytics

These results come in spite of increasing investment in big data and AI initiatives:

  • 92% report that the pace of their big data and AI investments is accelerating
  • 88% report a greater urgency to invest in big data and AI
  • 75% cite a fear of disruption as a motivating factor for big data/AI investment

Data security and compliance is critical. Regulators are ‘catching up’ with the market and a breach not only means potential financial penalties but may significantly impact brand confidence.

Data complexity is growing faster than uptake. According to McKinsey only a fraction of the potential of data envisaged in 2011 is being realised – healthcare 10-20%, manufacturing 20-30%, and retail 30-40%.

Data is complex and siloed. It is often unstructured and cannot be managed using traditional business intelligence tools. Real expertise is needed to monetise it, and typically it’s not something the average IT team can simply “turn their hand to”.

Data is a specialist field. Organisations make the mistake in assuming that driving value from their data is simply an extension of their existing IT systems – it most definitely is not! Specific technologies are required, based both on need and data types to extract value are required alongside the specialist knowledge of data methods, analysis and science.

Your competitors are using data to gain an advantage – are you?

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