Data Agility, Flinders University, and AIIA have jointly created this study to explore how leaders are planning to fix this lack of trust to achieve their AI aspirations. We look at their approach to data, its reliability, its value, and using data to make better business decisions.
- How developed are the data governance frameworks and data strategies in Australian organisations?
- Is there trust or a lack of trust in their org data?
- Where is the distrust generated from?
- How are Australian organisations preparing for the implementation of artificial intelligence (“AI”)?
This report is brought to you by:
Summary of study
There’s a clearly increasing desire to implement AI tools across the public and private sectors. However, the output quality from AI tools is only as good as the quality of the data inputted.
“A data lake without quality data is just a data swamp” Ted Friedman, Gartner
As this report will show, there is still a high frequency of inaccurate reporting due to poor data quality. 25% of respondents have regularly received reports or analysis with inaccurate results in the last 12 months.
To advance the application of the next generation of technology, organisations regardless of industry need a data strategy. It’s commonly agreed this creates better data governance frameworks which delivers better data quality. 98% of respondents agree a data strategy will help in achieving their organisational objectives.
There are also growing threats from bad external actors, such as the national headline ransom attacks. 4 out of every 10 public sector respondents are concerned or very concerned about deliberate hacking of their organisation’s systems by a third party. However, internal processes are not up to date to protect or react to these ransom attacks. 50% of executive management respondents agreed or strongly agreed their organisation kept data longer than it should have. Only 7 out of 10 respondents agreed or strongly agreed their organisation can respond quickly and effectively to a data breach.
We’ve gathered the most interesting results and statistics for you to read below.
Sections of statistics
Definition
Relevant commerce industries = banking, finance, telecommunications, IT, professional services, retail, hospitality
Do staff trust their org data?
Stat 1 – What decisions require data
80% of the healthcare and hospital sector use data to make decisions on improving service delivery. However, only 40% of the sector use data to improve policies and processes. This could be due to policy being directed from state and federal government agencies. Regardless, there is clearly a strong aspiration from the healthcare sector to deliver better planning and thereby better patient outcomes.
Interestingly, government and commerce industries have the same desirability to improve service delivery planning.
% of respondents from the relevant industry that selected these options
Stat 2 – Do gov and healthcare staff trust their data?
% of respondents that answered with agree or strongly agree to the following statements
Between a fifth and a third of respondents from the government and healthcare sector regularly receive reports with inaccurate information. This highlights how much wasted time and effort could be saved with better data governance frameworks. Poor quality data is a fixable problem.
Stat 3 – Why do gov and healthcare staff trust their data?
% of respondents that answered with agree or strongly agree to the following statements
The government and healthcare sectors understand how integral data is to make decisions, with 8 out of 10 agreeing with this statement. Yet there is low confidence in the validity of analytics gained, the data governance processes, and the quality of the data itself.
Less than 6 out of 10 government and healthcare respondents highly rate the quality of their org data. In comparison to 7 out of 10 relevant commerce respondents. Only 5 out of 10 government and healthcare respondents trust their data due to solid governance processes.
Stat 4 – Do executives and staff trust their data? And why?
% of respondents that answered with agree or strongly agree to the following statements
At least 8 out of 10 respondents agree or strongly agreed that data is integral in helping making org decisions. Yet 20 to 32% of all respondents, regardless of seniority, have regularly received reports with inaccurate results in the last 12 months.
Do organisations have data strategies in place to help build trust of data?
Stat 5 – Lack of data strategy in place even though needed
98% of respondents agree a data strategy will help in achieving their organisational objectives.
As with much of our research, there is a consistent trend of executive leaders not communicating the organisational data strategy to the rest of the organisation. This gap in communication is an important opportunity to improve data governance processes, data quality and thereby reporting and decision making. Operationally, this will reduce the large number of erroneous reports received by staff.
There is also a clear understanding from respondents that a data strategy will help to achieve business objectives.
% of respondents that answered with “yes” to the following statements
Stat 6 – FY23 vs FY24 aspirations from their data strategy
% of respondents from the relevant industry that selected these options
There’s a significant shift in objectives and aspirations from financial year 2023 (FY23) to 2024 (FY24) from the government and healthcare sectors.
Top objectives for FY23
- Improving the quality of data
- Improving regulatory compliance reporting
- Improving the efficiency of data management and analytics activities
Top objectives for FY24
- Improve operational efficiency
- Better service delivery to stakeholders or community
- Quicker access to critical insights
Both sectors had a joint primary objective in FY23 to improve data quality. However, for FY24 they have deviated in paths with the majority of the government sector focusing on improving service delivery to stakeholders or community. And the healthcare sector is focusing on improving operational efficiency.
Stat 7 – Financial value of data is unknown by a lot of organisations
% of respondents that answered with “yes” to the following statements
20% more private sector respondents know their organisation has determined the financial value of its data. This still leaves more than 5 out of 10 private sector organisations not knowing the financial value of their data.
Stat 8 – How is value extracted from data
% of respondents from the relevant industry that selected these options
An organisation’s ability to extract value from data is increasing all the time. 87% of all respondents are extracting value from their data in one or more ways.
1 in 3 healthcare respondents are using data to increase funding. This is being driven by an uptake and application in specialist technologies, such as Code Focus.
The most common method to extract value from data for government and healthcare sector respondents is through better service delivery planning, with 45% and 60% of respondents respectively stating this.
Where is the trust or lack of trust generated from?
Stat 9 – Are staff trusted with data? And how ready are organisations to deal with data breaches and leakages
% of respondents that answered with agree or strongly agree to the following statements
% of respondents that answered with concerned or very concerned to the following statements
- Only 7 out of 10 respondents trust their employees to handle data responsibly.
- Only 7 out of 10 organisations can respond quickly and effectively to a data breach.
- 5 out of 10 respondents are concerned or very concerned about accidental release of sensitive information.
With half of respondents showing concern of sensitive data leakage, there is a need for solid and well communicated data governance frameworks in government and healthcare organisations.
This is especially true for organisations that don’t trust their employees to handle data responsibly and cannot respond effectively to a data breach.
Stat 10 – Has data been kept too long
% of respondents that answered with “yes” to the following statements
1 in 2 executive leaders believe their organisation keeps data longer than they should, whereas only 1 in 20 of their staff believe they keep data longer than they should.
The staff entering and interfacing with the data see a necessity to keep data longer than is needed. There is a human tendency to over collect data, as well as to never delete data. This is why a data governance framework and its processes are so important.
Our research continues to show there’s a lack of consistent connection between exec level management and front line staff. Having a well communicated data strategy in place will minimise this disconnect.
What are the implementation plans for AI?
Stat 11 – How do staff see the impact of AI next financial year
% of respondents that answered with agree or strongly agree to the following statements
Although AI has a tool-in-use in some industries such as tech and retail, it is still not yet a front line problem solving tool for organisations in government or healthcare. Only 13% of healthcare respondents expect AI to provide a significant impact on their organisation in financial year 2024.
% of respondents that answered with agree or strongly agree to the following statements
There’s a growing number of non-executive staff that are expecting AI to provide significant impact to their organisation from 2023 to 2024.
% of respondents that answered with agree or strongly agree to the following statements
Stat 12 – What challenges lie ahead to implement AI
% of respondents from the relevant industry that selected these options
Interestingly, the government sector’s most common challenge to implementing AI is the lack of internal expertise. However, they are also very aware there isn’t a lack of talent with AI skills to hire from.
94% of government sector respondents know the external talent pool for AI skills is not a problem. However, 32% do see lack of internal expertise as a problem.
Stat 13 – How clear are leaders on their AI aspirations?
% of respondents that selected “Not sure”
Data Collection Method
Next steps
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