Organizations demonstrate analytics maturity in strategy and data dimensions, but they lack workforce- and process-related analytics capabilities
Delivering fresh insights into Australian enterprises’ ability to create business value from data analytics, Alteryx, Inc. (NYSE: AYX), the Analytics Automation company, today released findings from its research report titled, “Toward Analytics Automation in Asia Pacific”. The research, conducted by International Data Corporation (IDC) and commissioned by Alteryx, reveals a significant gap between enterprises’ business priorities and performance, one that can be bridged by overcoming the lack of workforce- and process-related analytics capabilities. The study surveyed 100 organizations in Australia across a range of industries.
According to the research, Australian enterprises’ top business priorities include customer experience, productivity enhancement, business model innovation, new product development and cost reduction. However, major gaps exist between business priorities and business performance in areas such as productivity enhancement, cost reduction and risk mitigation. Currently, while more than 90 percent of business executives believe that data analytics are important for their organizations to remain performant, one in five enterprises have achieved high analytics maturity. APAC enterprises that are ‘Analytics Experts’ tend to outperform their peers across all major business priorities, especially in areas like cost reduction (56 percent), business model innovation (28 percent), new product development (17 percent) and market expansion (12 percent). Australia has the third highest number of organizations who are ‘Analytics Experts’ among the countries surveyed.
To help enterprises to determine their analytics maturity level, IDC designed a framework that assesses their standing across four key dimensions – strategy[1], data[2], workforce[3] and process[4], before providing an aggregated score that identifies Beginners, Practitioners, or Experts. In addition, the framework describes the journey to becoming an Analytics Expert by achieving maturity in strategy, data, workforce, and process.
The research found that enterprises are more mature in strategy and data dimensions, with 42 percent having achieved buy-in and alignment amongst key stakeholders regarding analytics initiatives, and interestingly, 53 percent having established policies and practices to ensure data integrity. Nine in ten enterprises, however, lack the necessary workforce and process capabilities, which are the most crucial for driving data-driven transformation at scale and deriving long-term business value.
It also suggests that enterprises need to build workforce or process-related capabilities to derive business value from data analytics. In their daily roles, executives across the region currently struggle with hard to use tools (55 percent), scattered and unmanaged tools (49 percent), lack of timely access to data (44 percent), data lineage and integrity (44 percent) and lack of data literacy (43 percent). These challenges are exacerbated by increased complexity and organizational demands for data analytics to be delivered at greater speed and scale, with the average enterprise currently facing internal requests to include 26 new data sources and 30 new data types per month.
“In today’s volatile, uncertain and challenging business environment, enterprises in Australia want to invest in mission-critical business areas. In addition, with the evolving needs of customers, enterprises must innovate their business models to meet new needs,” said Jody-John Phillips, Country Manager, ANZ, Alteryx. “The findings show a consensus towards the critical role that analytics plays in driving business performance. Yet, organizations are grappling with multiple challenges in using data analytics, uncovering the need to improve workforce and process analytics capabilities. To deliver breakthrough outcomes, organizations need to automate processes and democratize data analytics, elevating workforce’s ability to gain on-demand insights for thriving in their roles.”
“Despite the rapid rate of digital transformation and data generation, many organizations in Australia are not yet experts in data analytics. They are at the Beginners stage in their workforce and process dimensions which are critical for empowering employees to do their jobs better, faster and with greater impact,” said Dr. Chris Marshall, Associate Vice President, APAC, IDC. “In the face of workforce and process challenges, organizations today can close the gaps with advanced analytics tools. Analytic process automation, in particular, is a low-code solution that has emerged as a way forward to remove friction, enabling analytics capabilities to scale quickly across the entire organization.”
The research findings also highlight the potential of a self-service, human-centric analytics automation platform to bridge existing workforce and process capability gaps, address analytics challenges faced by executives, and put organizations on a path to become Analytics Experts.
The Alteryx Analytic Process Automation (APA) Platform™ delivers end-to-end automation of analytics, machine learning and data science processes. As a result, organizations can automate analytics and data science, embed intelligent decisioning, empower its employees to deliver faster, better business outcomes and ultimately, enable the agility needed to accelerate digital transformation.
“Data should no longer sit idly in an organization. With the help of analytics automation, an organization can leverage its best assets – people, processes and data – to empower their workforce to increase overall organizational performance and efficiency so that decision-making is faster and more reliable,” said Quinn.
To access the full IDC Infobrief: Toward Analytics Automation in Asia Pacific Report, please click here.
To assess your organization’s analytics maturity with IDC’s APA Assessment Tool, please click here.
[1] The strategy dimension assesses the presence of a carefully planned data and analytics strategy. Without a strategy in place, the interdependencies amongst stakeholders responsible for different initiatives will become a stumbling block to generating consistent returns from analytics investment.
[2] The data dimension assesses how data, the raw material, is systematically governed across the organization.
[3] The workforce dimension assesses whether productivity tools and automation has enabled and empowered people to do their jobs better, faster and with less effort.
[4] The process dimension assesses whether definition, standardization, and automation of process management are in place.
