3 ways to leverage data automation for business productivity, quality and integration
Data automation is fast becoming a cornerstone of operational efficiency and innovation. Automating workflows, improving data accuracy and compliance, seamless data flows, and standardising processes – automation capabilities are evolving.
Below we explore three ways your business can harness the power of automation, and the steps you can take to implement them successfully.
How data automation transforms business operations
Let’s face it, automation isn’t a new topic. It’s been a key focus for businesses for many years – with Covid-19 and the rise of the remote worker a catalyst for automation integration.
But, its key benefits still remain:
- Increased productivity: automating repetitive tasks frees employees to focus on strategic activities, enhancing overall productivity and job satisfaction.
- Improved data quality and compliance: eliminating human involvement can ensure data accuracy and consistency.
- Unified data integration: integrated systems eliminate data silos, providing a unified view for faster, more accurate reporting and decision-making.
- Standardised processes: promoting consistent and streamlined processes, automation reduces variability and ensures reliable outcomes.
But what does automation mean in 2024? According to Australia’s Engineering Institute, automation is being enhanced by AI in all shapes and forms. With powered automation leveraging AI to streamline processes across healthcare, finance, and manufacturing, and hyperautomation leveraging AI, robotic process automation and intelligent process automation to optimise end-to-end processes and automate decision making.
For our data and automation team, we’re seeing more management and data integration requests as businesses look to link systems and outputs to drive business growth and reduce risks.
Data automation to optimise workflows
With rising budgets, resourcing constraints, and the increasing reliance on data intelligence, for our business and IT teams workflow automation is no longer about streamlining but optimising processes. Getting every second dollar and minute they can get!
To truly optimise your workflows and processes, it’s important to:
- Identify automation opportunities: thoroughly audit your processes to identify tasks that are repetitive and time-consuming. For example – data entry, report generation, and leave application processes.
- Choose the right tools: Microsoft Power Platform offers a suite of tools, including Power Automate, Power Apps, and Power BI, which can be tailored to your specific needs.
- Design and test workflows: map out each step of your workflows and test them extensively to identify and address potential issues.
- Implement: deploy automated workflows and monitor their performance. Adopt a continuous improvement approach to ensure they deliver desired productivity gains.
Automation for data quality and compliance
High-quality data is essential for effective decision-making. Compliance with data privacy regulations is also critical. And in today’s risk-focused and compliance-heavy world, the accuracy of your data could be the difference between a minor and major incident.
By maintaining data accuracy and leveraging it to continuously monitor and maintain compliance, you can better manage your risks and make more informed business decisions.
Here, it’s important to:
- Audit data: identify inconsistencies and areas prone to human error to establish a baseline for your automation efforts.
- Implement data cleaning: automate data cleaning processes to ensure continuous monitoring and correction of errors.
- Enable automated checks: use automation to regularly check data against compliance requirements and generate alerts for discrepancies.
- Integrate data quality tools: tools that offer advanced features for data profiling, cleaning, and validation, enhancing your data automation efforts. Not sure how to do this? Our data team can help.
Integrating systems for seamless data flow
No matter where you’ve worked, most IT and operational teams have had a data integration experience. But while combining data from different sources or systems into a unified view - reducing duplication and errors – sounds simple, it can go wrong fast without the right preparation.
Assess your system interoperability with the below steps:
- Identify data silos: conduct an audit to understand where data is isolated within your organisation.
- Choose integration tools: evaluate tools like Microsoft Power Platform and Azure Data Factory to integrate disparate systems.
- Design integration workflows: create workflows that outline how data will move between systems, ensuring efficient and secure data transfer.
- Implement and test: deploy the integration workflows and conduct thorough testing to ensure they function as intended.
Don’t have the resources in house? Our data and automation team can guide you through the process or manage the entire project for you end to end.
Food for thought: risks and considerations before starting your data automation project
Whether it’s an uplift in accuracy and compliance through automating data cleaning and regulatory checks, streamlining common approvals processes such as annual leave, or perhaps integrating systems to avoid duplication of data - there are many ways you can gain a competitive advantage through automation.
There are however some areas you should carefully consider.
- Data security: ensure robust security measures are in place to protect sensitive data during automation and integration processes. This includes encrypting data in transit and at rest, using secure protocols for data transfer, and implementing access controls.
- Privacy and data governance: understand where your data is traveling and how it is stored. Recent amendments to the Australian Privacy Act emphasise the importance of protecting personal information and maintaining transparency about data use. Ensure compliance with data privacy laws such as the Australian Privacy Principles (APPs) by securing consent where required and having a clear data governance policy.
- Change management: provide adequate training and support to employees to facilitate a smooth transition to automated workflows.
- System compatibility: ensure the automation and integration tools you choose are compatible with your existing systems to avoid integration issues.
Are you ready to unlock the full potential of data automation in your organisation?
Contact our Automation team today. We’re here to answer all your questions and get you started on your automation journey.
