8 ways big data analytics can be applied by any CEO

8 ways big data analytics can be applied by any CEO

8 ways big data analytics can be applied by any CEO

How do big data and data analytics play into strategy development at the chief executive level?

Should they play at all, or should CEOs and peers delegate data analytics to the experts?

It’s a discussion played out in businesses around the world. A recent report by McKinsey (Making data analytics work for you—instead of the other way around) shines a light on the value of data analytics to CEOs.

Often viewed in the context of addressing challenges, data analytics should also be viewed in the context of discovering, assessing and taking action on new opportunities.

I share the McKinsey view that data analytics do need to sit with the CEO, management team or board of a company – because analytics provide the inputs and insights essential to choosing future directions. Often viewed in the context of addressing challenges, data analytics should also be viewed in the context of discovering, assessing and taking action on new opportunities.

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In fact, seeking to redefine your organisation ahead of changes imposed by external forces is clearly the better option. Using data analytics anchors such considerations in firm foundations, to provide confidence in any decisions you make.

At the CEO level, data analytics can be defined as the establishment and identification of market threats and market opportunities. The data delivers raw inputs, and the analysis makes sense of this. With strategy setting the context, an open mind and ruthless objectivity are essential so boards and senior management can understand progress… and change direction as required.

Data analytics can expose the need to transform, identify new revenue streams, reveal new ways to improve operations or lower costs, or measure sales success rates. All are essential inputs on the CEO’s strategy dashboard.

Data analytics can expose the need to transform, identify new revenue streams, reveal new ways to improve operations or lower costs, or measure sales success rates.

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We’ve had experience of this at Lenovo with our PC business. Rapidly becoming commodity devices, desktop PCs are seemingly a dying product category if you believe some market and media commentary. But the data indicates otherwise. When asked to overhaul our regional PC business a few years ago, I pulled a team together to analyse our product range and the needs of the market. We discovered some surprising insights which allowed us to redefine how we went to market and how we developed product. Even in mature markets, we discovered that customers had a range of needs and preferences for how they wanted to use PCs.

The market was more granular than we’d assumed, with requirements that included premium performance for business and gaming, varying quality levels, specific applications for high-end graphics and gaming, and more. Speed and price were not the primary decision-making criteria. What’s more, all of this was as true in emerging markets as in mature ones – another surprise.

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We have been able to use these insights into our product development and marketing operations, and continue to maintain market leadership for PCs. The power of the data, and having the data analytics task linked explicitly to clear business objectives (in our case, how to grow a plateauing market and protect market share) allowed us to develop a meaningful strategy that worked.



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