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Alteryx Study: Improving Analytics Maturity Key for Bridging Gaps Between APAC Enterprises’ Business Priorities and Performance

Organizations demonstrate analytics maturity in strategy and data dimensions, but they lack workforce- and process-related analytics capabilities

SINGAPORE – Media
OutReach
– 7 September 2021 – Delivering fresh
insights into Asia Pacific (APAC) 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 regional enterprises’ business priorities and performance, one that can
be bridged by overcoming the lack of workforce- and process-related analytics capabilities.


 


According to the research, APAC
enterprises’ top business priorities include customer experience, productivity
enhancement, cost reduction, new product development and business model
innovation. Currently, while more than 90 percent of business
executives believe that data analytics are important for their organizations to
remain performant, less than one in five (19 percent) enterprises across the
region have achieved
high analytics maturity. 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).


 


To help
APAC 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 across the region are more mature in strategy
and data dimensions, with 48 percent having achieved buy-in and alignment amongst
key stakeholders regarding analytics initiatives, but only 38 percent having established
policies and practices to ensure data integrity. A large majority, however, lack
the necessary workforce (86 percent) and process capabilities (93 percent),
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 APAC 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 have expressed the need 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
Julian Quinn, Senior Vice President, APJ, 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 Asia Pacific 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 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.


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