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May 22, 2017updated 14 Jul 2022 7:04am

IBM’s Watson is just the beginning – in 2017 you may be working alongside Data Driven AI (or even a data loving CEO…)

People consume data in different ways. For some visualisation has been the missing link that unlocks their data passion.

By James Nunns

This year we’ve seen the mainstream adoption of data analytics for business use. Gartner has reported that over 1,000 large enterprises have a Chief Data Officer or Chief Analytics Officer and is predicting that 90% of large organisations will have the position by the end of 2019.

This is a huge deal for the data scene. Here are some predictions for big data and analytics in 2017 to help your organisation stay on top of a rapidly changing industry.

Large companies will trust self-learning AI to pull business insights and data

IBM’s Watson may have been the first of its kind but with intelligent AI, such as

Amazon’s Alexa, making its way into the mainstream consumer market, I would expect to see businesses embracing algorithmic business information. While I wouldn’t go so far as to say they could function independently within the next year, we should begin to see innovation organisations using them for services such as forecasting business growth and financial information that can be interpreted by the financial team and senior management. At some point self-learning models will build analytics very fast – by themselves.

Even traditional “last-frontier” sectors will begin using data analytics

As the benefits of big data become increasingly obvious I believe we will start seeing greater adoption of big data in sectors such as HR and education that have historically proven reticent. Thanks to a broadening analytics culture and self-service analytics systems that enable everybody, regardless of technical knowledge, to understand and decipher big data, I would expect to see even the most qualitative of businesses look to embrace the revolution.

In education, pupil data can be combined with data from society to help make better decisions to improve institutional and individual student activity. For the human resources department there’s a wealth of analytical techniques to turn on, from capability analytics (measuring the organisation’s talent), to competency acquisition analytics (assessing the acquisition of skills), capacity analytics (personnel efficiency), and of course employee churn analytics. Going deeper there is corporate culture analytics, recruitment channel analytics, leadership analytics, and of course, employee performance analytics – which is where analytics might start, but needed stop.

The democratisation of data will come into its own – along with greater data governance

Democratisation of data, that is self-service by the casual user will come into its own, and create the need for greater data governance. As a consequence, analytics and metadata management will eventually converge into single platform. Only eight per cent of employees are advanced spreadsheet users, and they spend 1.3 billion hours on repeatable work, compromising the integrity of data.

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Man and machine will really enter a truly symbiotic relationship

Humanity has bought into a machine symbiosis, and the trend is for more convenient, smarter technology that is easy to pick up and run with. This empowerment trend is part of the democratisation of data. The new simplicity means more users come ‘online’, using more applications – and creating an ever better man/machine relationship, as well as the continued upward curve of the data and metadata explosion.

So when a tool like IBM Watson can go through medical papers, research and journals, to present the best range of clinical decisions, the final stage is for the trained doctor to make the final decision for a patient, with the context and humanity of a real human being.

And in step with the rise of new, or more well-known tools and technologies, we will see the workforce reskilling through education courses like nanodegrees to further simplify interactions with data.

The bastions of traditional industry will fall to the data and analytics hordes

Some industries have been historically qualitative, or have only embraced analytics at the division/department level. This will change, all will become more quantitative. The broadening analytics will bring this new culture across all departments and will give organisations a truly 360 degree view of the business. From HR, educational institutions to non-profits, there are swathes of industry underserved by quality data practices.

Busting the ‘gut’ – finally, chief executives will really start to trust their data

The numbers are revealing. Managing directors still prefer their personal experiences – or hunches – over neutral, industry data. A 2016 study by KPMG of 400 CEOs revealed that a third of CEOs had a high-level of trust in the accuracy of their organisation’s data and analytics. In fact, 29 per cent had limited trust or outright active distrust.

Why should this be? Well, to many, and up to now, data has been seen as a black box. The skills to manipulate it (play with it, really), were specialised, and the technology was expensive, time consuming and required further skills or knowledge to utilise properly, from IT to software coding abilities.

Yet now organisations increasingly have a curator of data. Some few pioneers have chief data or chief analytics officers helping to create a data-driven culture across the enterprise. Many more are changing from a bottom up approach.

For the C-suite, better workflow visualisation has increased understanding of data at top levels. Yet 2017 should now see a broadening of reporting outputs to serve a wider variety of executives, and indeed, data users at all levels.

People consume data in different ways. For some visualisation has been the missing link that unlocks their data passion. For others, self-service solutions that remove the barriers of advanced statistical knowledge, or coding skills.

But, when it comes down to it, if organisations are really looking to become truly insights-driven, they must eventually assign data responsibilities. It might be to the CIO, CMO, and even the CEO. It’s more about the type of person who drives it, not the role. The personality with the will to unlock a data culture is the natural fit to drive fast business activity based on data-driven insights, and to share and ignite that passion for the organisation.

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