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We’re all becoming familiar with the metaphor: “Data is the soil of the digital age”. When cultivated in the right way, there’s an inherent quality and richness to soil that makes it a foundational element for growth and innovation.
But we’re now operating within a new paradigm in which AI performs as a catalyst for transformation.
Everyone is creating their own data trail. And these trails are creating layer upon layer of information. When cultivated and processed in the right way, this data can be leveraged into a data-rich environment. And just as a catalyst accelerates chemical reactions within the soil, AI processes data into valuable information and insights that can drive the performance of the organisation.
Automation, Data, and AI encapsulate potential. Working together they are accelerating processes, driving efficiencies, and reducing energy requirements. For these reasons (among others) they’re playing an increasingly important role in driving the performance and economic viability of just about every organisation operating in the world today.
And as automation and AI become ever-more important, the quality and integrity of our data is coming under the spotlight too.
The point at which this question comes into quick focus is different for every organisation.
Let’s say, for example, you and your team have already realised the potential of automation and AI and have started to scope out the main opportunities in your organisation.
You’ve looked into the ways you can embrace OpenAI, GitHub, Microsoft Copilot, and other generative AI technology, and this discovery process is getting everyone excited about the impact these game-changing technologies will have.
In this scenario, data will become an obstacle if you’ve realised that it isn’t ready, in terms of quality, accuracy, consistency, or completeness.
For your data to drive your automation and AI projects, you and your team are identifying the need to verify sources of data, address data entry errors, remove duplicates or irrelevant data, and perform data cleansing and validation processes.
And because there have been so many cases of the misuse of data in recent years, you’re probably getting a lot of pressure from your leadership teams to ensure you have the Governance policies in place to ensure your organisation will only use data in a compliant and ethical way.
Ensure the quality and integrity of your data with a Data Landscape and Maturity Assessment.
Tecala’s recently launched Automation, Data and AI (ADA) business unit is currently engaging with mid-market organisations to ensure they get the best outcomes from their automation and AI projects, including Copilot and other native GPT initiatives.
We’ve developed our Data Landscape and Maturity Assessment (DLMA) to provide an organisation-wide review of the quality of your data, and your organisation’s effectiveness in using it.
The DLMA starts with an assessment of the current state of your data, collaboratively formulates the future state based on your goals, and provides a gap analysis between where you are now and where you need to be.
The output of this assessment is a roadmap of projects with cost and duration estimates.
At a basic level, the roadmap may be focused on a simple ‘clean up your data’. On a more complex level it may deliver a roadmap to ‘transform and elevate’ your approach to data management across the organisation.
All outcomes deliver a clear view of where your data can be used to deliver the outcomes you need, while complying to your own governance standards and relevant regulatory requirements.
Unlike other maturity assessments, which can be purely technology focused, Tecala’s DLMA provides a 360-degree view on the intended data use within your organisation, which takes into consideration your people, processes, data landscape, organisational vision, and mission, as well as looking at your cultural and ethical guidelines around how you should and shouldn’t use your data.
Security and privacy – enabling a seamless flow of data to your applications and surfaces
With the DLMA ensuring the quality and integrity of your data, your Cyber Security policy enables it to flow freely and securely through your operations. Connecting your data through integrated cloud and on-premise systems and applications enables you to exchange data and implement business workflows.
Without the right systems, processes, and infrastructure in place to gather, structure, review, analyse, refine, store, back-up, and protect your data, it won’t be able to deliver the outcomes you need.
Staying compliant in a highly regulated environment
Many mid-market organisations operate across multiple jurisdictions or states within Australia, and each region may have its own specific IT compliance requirements. Understanding and adhering to different regional regulations can be time-consuming and may require significant expertise. The complexity of this challenge results in many mid-market organisations struggling to keep up with frequent changes, especially if they lack dedicated compliance teams or resources.
Unfortunately, failure to adhere to the latest regulations can lead to penalties, legal issues, and reputational damage. Therefore, deciding if you have the internal expertise to manage this complex regulation and compliance is important.
Data Literacy and Skills
Data is only going to deliver value if your people have the skills and training to interpret and use it effectively. Data and AI literacy should not be limited to a Centre of Excellence (COE) but should be embedded into the organisational culture.
With structured training and relevant resources, your teams will be able to understand and analyse your data, so they can make smarter decisions that deliver genuine value to your organisation and society generally. This is how you create a truly a data driven organisation, at all levels.
Environmental, Social and Governance (ESG)
In this context, ESG relates specifically to the ethical and responsible use of data, that complies with all your regulation requirements. This puts a layer of certainty and confidence into your operations that you’ll create products and technologies that align with societal values, promote trust, and prioritise the well-being of users and stakeholders.
Working in a holistic way, your ESG framework should foster a more responsible and sustainable technological landscape.
Data Landscape and Maturity Assessment (DLMA) is the first step in ensuring effective use of your data. In a three-step approach we assess the current state of your data, formulates the future state based on your goals, and provides a gap analysis between where you are now and where you need to go.
With the promise of unleashing creativity and productivity, we ensure the most effective route to a truly empowering and game-changing experience.
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