2016 saw the mainstream adoption of data analytics for business use. Gartner reported that over 1,000 large enterprises have a chief data officer, or chief analytics officer, and predicted that 90% of large organisations will have the position by the end of 2019. As Dean Stoecker, chairman & CEO, Alteryx Inc. explains, it means 2017 becomes a crucial year for those wanting to live these trends and become leaders in the world of data-led insights and decision making. It might just be the year your CEO learns to love data, you shack up with a machine, and even the most Luddite of industries open up to the data promise.

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

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. That will be a great tool in the kitbag for all marketing and advertising executive businesses who rely on speed as well as ‘smarts’. 

Data democratisation and greater data governance will come into their own

Even those businesses that don’t rely entirely on data analysis to make their business will see how the democratisation of data changes their inner workings. 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 a single platform. Only 8% of employees are advanced spreadsheet users, and they spend 1.3 billion hours on repeatable work, compromising the integrity of data through the well-known error-prone nature of the activity. 

The truly symbiotic relationship of man and machine

Once the majority of knowledge workers are connected to their data, data and man and machine will begin to co-evolve. Humanity has already 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 re-skilling through education courses like nanodegrees to further simplify and intensify their interactions with data. 

At last, 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 360º view of the business. From HR, educational institutions, to non-profits, there are swathes of industries underserved by quality data practices. 

Advertising and marketing departments whose success has been predicated on data-led insights for years will be able to lend expertise and show leadership, in the industries that have them. 

Even those 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 needn’t stop. 

And, at last, chief executives will bust the mythical gut feeling and really start to trust their data

It’s no surprise. Managing directors still prefer their personal experiences 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% had limited trust or outright active distrust. 

Why should this be? Well, to many, and up to now, data has been seen as a blackbox. The skills to manipulate it (or 'play with it', as data lovers would term it), 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.