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Libby Duane Adams: So what do the five most profitable companies in the world have in common? Cash reserves. Real estate? No. Each of these companies can collect, analyse and act on data at scale to make effective business decisions. Amazon is a perfect example of this kind of an organisation. Ben Franklin once said An investment in knowledge pays the best interest.

And today, data is knowledge and knowledge is power. We see this trend across a huge range of businesses as data-driven decisions continually deliver results. The importance of data cannot be overestimated. The market for Big Data Analytics is now set to hit over $100 billion by 2023, and by 2020 563, exabytes of data will be generated by us humans around the globe every day. But just 2% of those data are going to be saved. The rest will either be deleted or lost. So how much of that is even analysed? That’s a lot of wasted potential, according to Ben Franklin. We ran our own research with IDC and found that data workers waste 100,000 human lifespans each year on inefficient data work. They spend a fifth of their total working week redoing the same calculations that they did just the week before. It takes 6.6 million rows of data on average to deliver just four unique analytic assets.

My name is Libby Duane. I am chief advocacy officer and co-founder here at Alteryx, the Analytics Automation Company. Today we have a global customer base of almost 8000 customers across every industry and can count 43% of the global 2000 as Alteryx customers. While the power of data cannot be underestimated, many organisations face a situation where the wealth of data but the poverty of insights is stalling their transformation. The IIA and Forrester have a fascinating five-stage model that assesses and maps analytics maturity for businesses. This research shows where organisations are on their journey to becoming a truly data and analytics-driven organisation, while highlighting that analytically mature companies deliver better financial performance.

The IIA report also states that only 24% of companies are data-driven. This turns out that the average across about a couple of thousand enterprises is a score of only 2.2 out of five. In context, this is equal to roughly 1% of the workforce being analytically capable. digital transformation is not easy, but the blocker is not the tools and technology that are available. 91% of businesses say that they cannot meet their potential due to the skills gap in data and analytics. While many organisations invest heavily in transformation technologies, many fail to integrate digital across their business. They think that digital transformation means applying new technology to a process. But digital transformation is just as much about the human and managing through change as it is about the technology.

Business and government leaders tell me frequently that surfacing key insights daily is mission critical for them to stay competitive, but they also tell me they’re still in the early stages of their data journey. There is a real sense of urgency and pressure to upskill their workforces, to reduce that global skills gap in data analytics, because that skills gap is increasing. Most companies have some employees who can execute some pretty advanced analytics, but many more are still challenged by the terabytes of raw data piling up literally around the business. Even at many analytics focussed enterprises, most employees cannot work to be work beyond basic spreadsheet manipulation. Laggards in the data literacy race are leaving over 2.5 quintillion bytes of data untouched in the next few years. That analytic divide between companies that can harness these data and those that cannot is going to continue to widen, which is why it’s paramount that everyone in the workforce should be able to discover, analyse and reach answers through data, not just reserving that for a handful of specialists. The good news is, is pretty much all companies recognise that they want to move up this curve and are investing in data and analytic capabilities. But as businesses move from being data hoarders to driving real insights, they’re using far more of these data now by democratising the responsibility of analytics. What we see are skills constraints combined with the use of inefficient legacy spreadsheet tools hindering this progress.

This means a growing number of people versus technology divide, which is growing. Clearly, there will never be enough data scientists, but it does not need to stay that way. While companies look outward for technical solutions, data literacy comes from within. According to Gartner, by 2023, data literacy will become an explicit and necessary driver of business value. The truth is that many people in your business, they’re hiding in plain sight. Instead of hiring from the outside. For a limited number of positions. Companies need to look inward and upskill the existing employee base through the use of no code, low code, self-service analytic platforms. Organisations can open up the world of analytics to the entire workforce. This enablement of knowledge workers is what we define as democratising analytics. These employees are improving processes, mitigating risk and driving efficiencies across the enterprise. In the end, companies have a choice of how much time, resources and money they’re going to invest in upskilling and in the democratisation of analytics.

But the reality is, by upskilling domain experts who understand the business with data literacy, those are the ones who know where the gold is buried and they can deliver those breakthrough insights. While this journey is challenging as companies try to jump to full digital transformation, our experience in helping our customers on their digital transformation journey consists of your upskilling of your domain experts. The people who own the process are the ones improving the processes. This means people learning how to work with data in more advanced and efficient ways than using a spreadsheet followed by the automation of data processes. These domain experts or what we refer to as knowledge workers are then enabled to invest in the development of their analytic skills. And they are driving bigger value and bigger results for the company. It also greatly improves job satisfaction for these knowledge workers, exciting them about the impact they’re making while also driving results. But once these steps are understood, digital transformation will happen. With the democratisation of analytics and with the democratisation of analytics. Your organisation’s digital transformation will be driving results with significant impact. So while the road to a fully transformed, data driven company may be a long one, the talent, the tools and the learning to deliver business changing insights are all within your reach. It just needs a culture where every person across the business is empowered with the right skills and the right technology so that more people can use data to drive business value. Thank you.