Alteryx is a Business Reporter client.
Right now, it’s hard to define just how 2023 will go down in history. Uncertainty, disruption, innovation, differentiation? Is “AI” just hype, or are we on the precipice of a critical moment? With the current business environment still awash in risk and uncertainty, I don’t know many executives willing to rely on their instincts to overcome challenges facing today’s businesses. Most are looking for faster ways to make data-driven decisions with speed, gain the insights required to see around corners and navigate a safer course.
Today, all over the world, we are in the midst of a great shift. The data revolution has given way to the analytics movement. Because what good is your data if you’re not analysing and using it to drive better decisions? And once you realise you must, how do you do this at scale? Data-driven insights are reshaping outcomes right when business leaders need them most. But it is not a trivial undertaking, especially for large, multinational companies. It’s a journey – one many are struggling to progress on.
Taking advantage of analytic maturity
What’s stalling this journey to insight-driven decisions? According to recent Alteryx commissioned research into the current state of decision-making across global enterprises, sharing data has clear benefits for making intelligent decisions at scale, but some business leaders are still hesitant. While 80 per cent said that the ability to access and analyse data positively impacts their decision-making, 65 per cent of respondents don’t think employees who make decisions for the organisation should have access to data for decision-making.
Prioritising insight-driven decision-making is vital for growth in a turbulent macro-climate. Yet business leaders can’t wave a magic wand and add hundreds of data engineers and experts or spin up a data science team out of nothing. Even if they could, those data scientists wouldn’t have the specific business expertise needed in each area across the business to deliver insights at speed. They haven’t built a career managing supply chains nor know how to be great accountants or orchestrate HR operations. But there are people who do. How do we get the right data into their hands?
It is imperative for companies to provide access to the right data, equip domain expert decision-makers with accessible technology, and empower them to make insight-driven decisions up and down the organisation. Most respondents (61 per cent) of our research confirm this – citing advanced technologies such as analytics, business intelligence and artificial intelligence that deliver faster decision-making.
Going from insights to impact even faster
Feeling pressure from all sides, business leaders and decision-makers must move from the data era to the intelligence era. Faced with the paradox of doing more with less, they need to figure out how to accelerate the process of getting the insights required and make decisions from this sea of data.
Generative AI technologies can deliver this at every level, and for the business leaders I’m talking to, investigating this area is a top priority. According to Forrester, “Companies across all verticals and maturity levels are finding opportunities to implement AI.” From text-mining to PDF data extraction and natural language processing (NLP), generative AI and large language models are lowering barriers to entry, empowering everyone to ask analytical questions and breaking down silos to engage the world’s imagination in how we understand data.
Undeniably attractive, AI is now also increasingly accessible, largely thanks to innovative platforms that can automate key data preparation and analytic processes. But while AI has become truly viable, it’s when you put accessible AI into the hands of employees and empower non-technical users to build and automate processes without needing to write code that it becomes truly valuable to the business. For example, eBay used Alteryx Analytics Cloud to train 50 non-technical employees to use AI and build machine learning models. One trainee saw an opportunity to improve functionality in eBay’s checkout feedback process. Using the Alteryx platform, she built a model to determine problems and predict solutions before humans even stepped in.
As we blend generative AI technologies into the analytics stack, we’re observing the dawn of what we call multi-modal analytics – enabling decision-makers, analysts, data scientists and developers to collaborate and develop analytical insights in real time. Whether through no code and code-friendly workflows, chat prompts or Python and SQL, each can leverage their tool of choice because all of this can be live-translated, by generative AI, into a single analytical solution. A solution that:
- Improves time-to-value by reducing the time required to derive insights from data
- Reduces repetitive manual processes by automating content creation tasks to improve operational efficiencies
- Automates governance documentation tasks using generative AI technology while ensuring consistent and accurate output at scale
Over the past decade, we’ve seen the volume of data available to decision-makers grow exponentially. In this intelligence era, it’s no longer about how much data one company can generate, it’s about how they use it and knowing how to ask the right questions to get the right answers. While savvy business leaders have been leveraging analytics to drive real, tangible value, generative AI introduces new, intuitive and compelling ways for everyone to engage with analytics while accelerating analytical insights and collaboration across the enterprise.
I have seen many technology cycles and business trends come and go. Despite all the noise about new technologies enabled by AI dominating news headlines, we are at a time of tech-powered outcomes fuelled by data and driven by human intelligence. We’re in a time where generative AI meets trusted, accessible analytics – helping everyone to go from insights to impact faster. Allowing decision-makers to apply their creative potential to gain transformative insights. Empowering the business user – the accountant, the supply chain analyst, the merchandising analyst – to solve critical challenges in new and effective ways. Enabling analytical outcomes that reduce the time to value by putting the power of better decision-making at everyone’s fingertips.
Learn more about Alteryx and AiDIN - the AI engine that infuses the power of Generative AI and machine learning across the Alteryx Analytics Cloud Platform.
Mark Anderson is chief executive officer (CEO) of Alteryx— (Alteryx)
Prior to Alteryx, Mark was president of Palo Alto Networks, where he and the team grew the company from pre-IPO in 2012 to one of the largest security companies in the world. Before that, Mark led sales and go-to-market initiatives at F5 Networks, where he was instrumental in driving the company’s long-term, sustained hyper-growth.
Mark has also served on the Alteryx Board of Directors for the past two years. During his tenure, he played an active role in the company’s operations and strategy. He also served as executive chairman at Avi Networks, a private, multi-cloud ADC innovator in Silicon Valley (acquired by VMWare in 2019), and has served on the board of directors for Cloudflare, Inc. (NYSE: NET) since August 2019.
Mark held leadership positions at Cisco Systems and Lucent Technologies earlier in his career. He holds a BA in business and economics from York University in Toronto.
