Ashley Fernandez is an accomplished Data & AI leader with extensive experience in driving organisational transformation. He is currently the Chief Data & AI officer leading the Applied Intelligence Office at Huawei International in Singapore, where he develops innovative strategies and solutions across Cloud, Data & AI.

Previously, Ashley led the Data & AI Center of Excellence at Maxis Malaysia, where he developed the Data Science & Advanced Analytics Practice supporting various business divisions. He is an expert in Data Science and Applied AI, with successful patents under his belt.

Ashley’s passion for Data & AI is evident in his pursuit of a Ph.D. in Artificial Intelligence specialising in Cognitive Science. He is a well-known Data & AI evangelist, using his expertise in Data Engineering, AI/ML, and Governance to drive business success. As the leader of the Applied Intelligence Office, Ashley is driving the development of cutting-edge solutions that harness the power of Cloud, Data & AI to transform businesses and drive growth.

In an exclusive interaction with us, Ashley shares his thoughts on best practices for leaders to leverage data for strategic decisions and tips on smarter data utlisation.

As per a recent Salesforce Survey, business leaders are struggling to put data into practice to quickly make strategic decisions. What steps do you recommend towards addressing this conundrum?

I believe and have seen this struggle go through different cycles defining right practices over the years but one thing for sure is that more business leaders are definitely more aware of a few foundational principles that must be laid out for this to materialise. For e.g., centralising data across different systems into a single repository aka single source of truth – although this poses a series of challenges in itself- it’s definitely a core need. Further, using modern day data architectures like Data Mesh that focuses on Domain Driven Decentralised data-analytical practices, forming the right organisational mix of domain and data teams to operate as hub & spoke, and building a foundational data literacy program that advocates for data to be a mainstream agenda are some other steps.

Almost one-third (30%) of business leaders are overwhelmed by the amount of data, which is expected to more than double in size by 2026. What best practices do you advocate for organisations to utilise data amidst data bombardment?

At the heart of it all I would boil it down to 3 things:

Defining a clear Data strategy: This data strategy should be reviewed regularly to ensure it remains aligned & “relevant” with your business goals and objectives. Regularly assess your data sources, data quality, and the tools and technologies you’re using to manage and analyse your data. This data in terms of its magnitude is never to plateau or stop growing, hence embedding Data Observability practices helps you manage at an operational level that aligns back to your Data Strategy.

Mainstream Data Security: With the increase in data, the risk of data breaches also increases. Investing in data security measures, including encryption, access controls, and regular security audits, to protect your data should become a mainstream agenda within business leaders.

Investment in the “right” Tools & Automation: Automation and machine learning tools can help you manage and process large volumes of data quickly and accurately. A common example I typically use to contextualise this is, “what excel as an incredible tool did for us till this day, enabling us to crunch, visualise & analyse data, calls for us again on this quest in finding the right new “Excel” that helps you do the same but at a different scale and purpose.”

Data fragmentation and lack of cooperation across the business remain an issue. What steps can be taken to address it?

Let me share with you a perspective by drawing a comparison between two segments-Long tenured enterprises that required transformation across all fronts from IT to Data vs Enterprises / Startups born most recently over the last few years.

The former have oftentimes, almost definitely have experienced the pains of data adoption, questioning data authenticity, ease of use, new ways to acquire-transform-develop insights, that brings friction and push backs from business. And all of these are simply because of its push to change and transform existing processes within business that are not relatively easy to accept and adopt. We have seen that newer enterprises or startups almost run through this problem at ease as they were born in the era where their systems, data & applications are by design integrated as foundational practice from the get go.

Now with that being said , I would like to share two key areas across Organisation & Process that would prove vital in addressing these problems we have today :

Organisation: Establishing a Top Down Agenda advocating Data as an Org culture: Encourage a culture of collaboration and data sharing across the organisation. This can involve providing training and resources to employees on how to use data effectively, incentivising data-driven decision-making, and promoting a culture of continuous improvement.

Process : Data Governance at the heart of Data Operations & Adoption: Having a framework that outlines the roles, responsibilities, policies, and processes for managing data across the organisation. This can include establishing data standards, data ownership, data quality controls, and data sharing protocols.

With increasing digitalisation, the lines between apps and infra blurring, the importance of data security has become a top priority for organisations. What are some of the best practices you recommend towards it?

This question is an interesting one, with new tech emerging more rapidly than ever, speed and scale of innovation has increased exponentially, forcing us to rethink what we define as best practices almost every other day. But in essence, it comes down to few key themes of what we should do that always remains , for e.g:

1. Access Controls: Implementing access controls and authentication mechanisms to restrict access to sensitive data to authorised personnel only. This includes strong passwords, multi-factor authentication, and role-based access controls.
2. Encrypt Data: Encrypt data both at rest and in transit to protect it from unauthorised access. Encryption ensures that data is unreadable and unusable by anyone who doesn’t have the decryption key.
3. Conduct Regular Security Audits: Conduct regular security audits and vulnerability assessments to identify security weaknesses and vulnerabilities. Having a close loop process to address any vulnerabilities immediately to prevent exploitation by cyber attackers.

All the above is almost like a “must do doctrine” that if we have not yet started, something must be extremely wrong and at risk in how we are currently operating. But I think the most important theme that makes turns this practice into a “cultural implementation” ever so robust is by promoting “Cybersecurity Awareness” that constantly keeps these practices in check & relevant as security is an ongoing improvement process that aligns with business & operation change

Lastly, what will be your one go-to advice to CIOs and CDOs for smarter data utilisation in 2023 and beyond?

The one go-to-advice worth sharing is to start by defining the right data strategy playbook.It is the utmost foundational pillar that propels organisations’ data adoption & ambitions forward. This foundation often involves a series of many different yet relevant moving (Cloud, Data, Security, AI/ML) parts that essentially needs to be best stitched together operating a Data Core Function.