MSE Sector Realizing the Power of ADM for Enhanced Data and Analytics Governance

According to a recent report by Gartner, “By 2027, 60% of organizations will fail to realize the anticipated value of their AI use cases due to incohesive ethical governance frameworks.” 

Following the rules and regulations of the industry where you run operations, is of the essence. And this is why adhering to Data and Analytics Governance is essential for micro and small enterprises (MSEs) across Canada. But what exactly is it? Let’s dig deeper to know more about the concept and see how MSEs can bring it to the best of their use post-deployment, this 2024.

What is Data and Analytics Governance?

When an organization’s policies and processes are deployed across every vertical and every department to manage its activities effectively and efficiently, that is when we say its data and analytics governance are being followed, keeping its goals, regulations, and best practices in mind. From its application integration to analytics, data governance needs to be applied thoroughly by MSEs. 

Some of its key aspects include: 

• Accuracy, consistency, and quality of data
• Keeping data safe and secure from unauthorized access, breaches, and misuse, 
• Ensuring compliance with relevant data privacy regulations like GDPR, CCPA, etc.
• Controlling data access, through role-based access controls (RBAC) and data access policies.
• Data integration, storing, and management to ensure consistency and interoperability
• Data lifecycle management, including data retention policies and procedures.
• Analytics governance that ensures insights are accurate, ethical, and aligned with business goals.
• Making sure that data and analytics practices comply with industry laws and regulations.

What is Application Data Management (ADM)?

When the data of one or more than one software application within an organization is managed with the help of a single process that is said to be the practice of Application Data Management or ADM. Whatever data is generated and utilized by the application, becomes a part of this whole process. This high-value technology needs to be planned with meticulous deployment across one and each company under the MSE sector in Canada. The ADM empowers MSEs to focus on the needs of individual applications as it supports the quality of your organization’s data.

A Personalized Roadmap to Better Data Governance for MSEs

If you are a data and analytics leader, looking to gratify the demands of your business by meeting the modern-day industry expectations of better value, enhanced operation scaling, and more speed, follow this roadmap to succeed because a conventional method is not going to cater to your evolving and trending digital needs.

1. Lay Governance Foundation

By making sure that the right governance practices are followed throughout every vertical of the organization, MSEs can actually strengthen their position on the data and analytics front.

2. Build Governance Structure

To go ahead on this path, your MSE business needs to define objectives, identify key stakeholders, create data policies and procedures, establish data quality standards, implement data governance tools, etc.

3. Deploy Governance Policies

Now comes the next step to design and deploy your governance policies and standards. Once implemented thoroughly, you can start monitoring and measuring the overall performance of your MSE. 

4. Evaluate and Improve

Once done with the deployment, get started with performance evaluation and improvement which will eventually help you promote a culture of data-driven decision-making in your organization.

5. Iteration and Learning

To make sure that the power of data governance is realized thoroughly, your micro or small enterprise needs to establish a process of iteration and learning that will be followed with diligence. 

Approach Ahead

Among all this continuous process of deploying, monitoring, and improving your data governance, you also need to shape your AI vision in order to make your data, AI-ready. You could take triple E (3E) actions to ensure the same:

Embrace – your organizational flexibility

Extend – the data literacy to include mastering AI

Establish – a new leadership paradigm

All these small steps will help your organization facilitate autonomy and flexibility, get training resources ready that are needed to bring your workforce to par with new skills, and in the long run, lead your enterprise to achieve your goal, more efficiently, saving time and cutting cost.

Conclusion

To address future requirements and foster innovation throughout the organization as you develop flexible AI strategies in your entity, you would require frameworks in place for expanding generative AI based on high-quality enterprise data. Let SkyTrust be at your disposal and help you enhance the digital transformation of your business in the MSE sector of Canada.