The organisation released its findings following an in-depth survey of 110 Australian heads of data and analytics representing organisations responsible for 24% of Australia’s $1.8 trillion GDP and just over one million employees.
“Most innovation-based challenges can be reduced to a lack of understanding, with data being no exception. Businesses have become saturated by it, as their ability to collect it far outpaced their appetite to support, filter, and find the talent to manage it, leaving many with fast-growing heaps of information that they struggle to extract value from,” explains Adapt director of strategic research Matt Boon.
“Companies that can modernise their data culture and architecture to provide leaders fast and accurate insights will be rewarded with less waste, more effective employees, and happier customers through better experiences.”
Numerous challenges underscored by lack of confidence in data strategy
Just 41% of data and analytics leaders said they were confident in delivering on their data strategy with 46% remaining neutral, and 13% of respondents expressing they “weren’t confident”.
“A lack of standardised data definitions, low prioritisation of data by the C-suite and a skills shortage compounded by low data literacy has shaken the faith of executives in their ability to execute, compelling them to ask again how they should enable data-driven decision making,” says Boon.
Low levels of data literacy key obstacle to optimised decision-making
The study revealed businesses struggling to harness data and analytics with 64% of respondents quoting data across disparate systems and applications a key challenge to their strategies. Sixty percent of executives also quoted a lack of data culture, along with legacy architecture (56%), a lack of data skills (53%), and a lack of ownership from business units (44%).
“Despite a pandemic-driven desire to innovate, many companies are still struggling to do so, as lockdowns hampered our ability to have spontaneous conversations offering speedy issue resolution. In many ways, ‘innovation culture’ has fallen behind, post-pandemic,” comments Boon.
Significant skills gaps faced by data leaders as shortage bites
The study revealed which jobs are most sought after in data and analytics, listed in order of greatest need: Data architects, data scientists, data professionals with management potential, and machine learning/AI specialists.
“We still have too much information with too little insight. Data automation needs to take on greater focus as a way to mitigate the impacts of the skills shortage, which isn’t going away any time soon. While tech isn’t the answer to everything it can certainly help companies, many of which are still too reliant on human capital to overcome their data challenges,” Boon remarks on skills shortage, which he says is being felt in every business unit.
Investment priorities ranked
Data literacy training is a priority for data and analytics leaders with 73% of respondents intending to invest in the area over the next twelve months.
Significant interest was also found in self-service BI (business intelligence), data visualisation technology (69%), staff upskilling and training (69%), as well as governance, risk and compliance measures (66%).
“Organisational data culture is lacking, and analytics leaders are stumping up with measures to bolster data-literacy across the organisation, transforming their workforce into a unit capable of making data-driven decisions,” Boon said.
Top business outcomes to achieve in next 12 months
The results revealed that respondents seek to fuel revenue and business growth (78%), enhance the customer experience (70%), lay the foundation for emerging technology (68%), improve the employee experience (63%) and create real-time dashboards for executives and boards (61%).
“We tend to think first about technical ways in which we can help teams make value of the data being produced, but such diverse goals ask data and analytics leaders to remember their ultimate objective: improving everyday experiences for both their employees and customers. Prioritising activity using this mindset will help bring together issues which seem impossible to face all at once,” Boon says.
Top success metrics for tracking data initiatives
The survey ranked the top success metrics being used by heads of data and analytics in order: data quality, revenue, customer satisfaction, data governance, and accuracy.
Boon says there is a positive correlation between good data and strong data culture.
“Faith in data is improved as its quality improves - an aligned approach with the idea of improving data quality at its heart will naturally improve an organisation’s willingness to use it”.