This article first appeared in Digital Edge, The Edge Malaysia Weekly on May 27, 2024 - June 2, 2024

Data literacy among businesses in Malaysia is gaining significance against the backdrop of a booming big data analytics (BDA) market projected to reach US$1.9 billion (RM7.85 billion) by 2025. Yet, local businesses continue to grapple with data literacy challenges, impeding their capacity to leverage data effectively for informed decision-making and innovation.

The skills gap is particularly evident, with many businesses lacking the necessary expertise to harness the full potential of their data assets.

Initiatives like Malaysia Digital Economy Corp’s (MDEC) “DataKITA” aim to address this gap head-on by fostering data literacy and cultivating awareness for data-driven strategies among businesses. And while many forward-thinking enterprises are increasingly investing in training programmes and strategic partnerships with data analytics firms to enhance their data literacy, many still “need more support to make full use of their data”, says Hemanta Banerjee, vice-president of public cloud data services at Rackspace Technology.

“Organisations may also struggle to transition to a data-driven culture where employees feel empowered to use and interpret data for decision-making. An indicator of data literacy within an enterprise would be the existence of initiatives to improve employee competencies in data analysis, interpretation and decision-making. However, effort does not necessarily equate to impact.”

Businesses currently require significant improvements in data pipelines to ensure the availability and quality of data. To effectively enhance data literacy within Malaysian businesses, the implementation of robust change management practices is imperative. This entails fostering a culture that values and uses data across all levels of the enterprise.

One of the primary challenges encountered in this endeavour, says Hemanta, is the difficulty of transitioning to a data-driven culture. Organisations often struggle with empowering employees to confidently use and interpret data, which is essential for informed decision-making. “Siloed approaches and leadership based on intuition rather than data” can further hinder the desired cultural shift towards embracing data-driven methodologies, he explains.

Another significant obstacle faced by organisations striving to improve data literacy is the constraint of limited resources and training opportunities. Investment in comprehensive training programmes and the acquisition of advanced data analysis tools are critical steps towards bridging the skills gap.

In some cases, hiring data specialists may be necessary to augment existing capabilities. However, resource allocation for such initiatives can pose challenges, requiring strategic planning and prioritisation within a business’s budgetary framework.

In addition to cultural and resource-related challenges, establishing a robust data platform is vital for sustainable data literacy growth. Beyond leadership initiatives and training efforts, organisations must prioritise building a sophisticated data estate, stresses Hemanta.

Moreover, enhancing data infrastructure is essential for supporting advanced initiatives like artificial intelligence (AI) and machine learning, which rely heavily on comprehensive and reliable data sets. Addressing these challenges holistically will enable organisations to cultivate a pervasive culture of data literacy and effectively leverage data for strategic decision-making and innovation.

The first step towards fostering a data-driven culture starts with “sitting down with management to set expectations and establishing a roadmap for implementing a data-driven approach. Once a road map based on realistic expectations has been set, teams within the organisation can determine how their efforts contribute towards meeting the overall goal”, Hemanta says.

In developing a roadmap for data literacy, it is important that key performance indicators (KPIs) align closely with a nuanced understanding of the business context.

“For instance, Rackspace’s Global Business Intelligence team exemplifies this by consistently evaluating the impact of each KPI on decision-making processes,” he adds. This approach ensures that KPIs are directly influencing actionable insights. It also fosters a shared understanding of data management principles and facilitates cohesive and effective data governance practices across all departments, reinforcing the integrity and usability of data assets within the business.

“Once various teams begin sifting through data, a common source of confusion for decision-makers is the existence of multiple terms or numbers for what is essentially the same metric.”

And while defining objectives in data literacy can be a challenge for many as the digital landscape evolves rapidly, applying the “circle of competence” mental model is a great way to increase the likelihood of employees maximising their usage of data for decision-making, says Hemanta.

“What this means is that employees focus on their knowledge domains so that the organisation ensures that decisions are made based on expertise and competence. This, in turn, leads to a more effective utilisation of data and other resources.”

Data integration and analysis can oftentimes meet a stumbling block in the form of legacy systems. These systems, often in the form of outdated or even obsolete hardware, software or technology infrastructure, lack compatibility with modern data analytics tools and practices.

“The existence of data silos in legacy systems makes data extraction and integration difficult, reducing the overall quality of the data. Furthermore, legacy systems often have limited scalability and performance, making it difficult to handle the volume of data required for modern data analysis,” says Hemanta.

In addition to manual errors, organisations face challenges with data stored in outdated formats within legacy systems, requiring standardisation processes that further contribute to delays.

The limited scalability and performance of legacy systems also hinder efficient data integration and analysis. These systems often lack the computing power needed to handle the demanding workloads of modern enterprises, leading to delays and inefficiencies in data processing and utilisation.

The easiest way for businesses to enhance data literacy when dealing with an existing legacy system, suggests Hemanta, is to “start by identifying what kind of data is available internally, where it is located and how it is created. Only then can it be determined where data should reside and how to run analytics without disruption”.

Decision-makers should also prioritise identifying achievable use cases that generate significant value. Focusing on one pilot project enhances overall buy-in and clarity. Next, they must align the enterprise’s data infrastructure, ensuring that access, processing pipelines and delivery mechanisms support the selected use case. Lastly, decision-makers should ensure adaptability for future use cases through a strategic modernisation approach that anticipates future analytics needs.

Hemanta also insists that there is no dichotomy between balancing data literacy with other skill sets for a more holistic approach as both of these go hand in hand.

“Imagine embedding data skills curricula into programmes as diverse as leadership development, sales training and customer service. Not only does this equip people to understand the prevailing imperatives in these roles, it also equips people to hone domain knowledge in a data-driven manner. This allows people to apply their data literacy skills to everyday scenarios instead of being an abstraction of real life.”

A good example of this is the transformation that First National Bank, a leading South African bank, undertook to convert its legacy operations with limited data sharing. Hemanta says its senior leadership recognised the need for accessible data to drive decision-making and to use the insight to guide the bank’s inaugural self-paced learning and development (L&D) initiative, highlighting the importance of data accessibility in fostering a data-driven culture.

“The organisation also established centres of competency to centralise and democratise its data. This was an outgrowth of adopting the ‘circle of competence’ mental model. As a result, staff could align their skills with organisational needs while empowering collaboration and improving decision-making.”

Fostering data literacy in Malaysian businesses involves practical, achievable steps. For starters, leadership within the organisation plays a crucial role in fostering and sustaining any data-driven culture. Leaders also emphasise the importance of data regulation, ethics and governance to ensure data integrity and compliance.

In addition, decision-makers can mandate the establishment of centralised centres of competency to democratise data access and streamline data processes. This, in turn, enables more efficient collaboration and informed decision-making, which helps prevent situations in which end-users are unable to effectively leverage internal data assets.

“Leaders should help employees at all levels realise that data is essential for the decision-making process throughout the organisation. Data-driven decision-making is relevant, from senior management all the way to even junior and entry-level employees. After all, people make decisions on a daily basis with data even if they are unaware of it,” Hemanta says.

Businesses should also foster cross-functional collaboration and maximise impact by establishing clear and open communication channels for sharing data insights, best practices and lessons learned.

An agile organisation encourages meaningful engagement and dialogue through formal and informal avenues. Implementing a centralised platform also helps break down data silos, enabling easier access to insights and facilitating collaborative cross-functional teams. This approach enhances knowledge sharing and collaboration across departments, ultimately leveraging data more effectively for overall success.

For companies beginning their data journey, conducting a transparent assessment of data literacy and the overall data landscape is crucial. This assessment helps identify gaps and sets clear objectives, ensuring alignment towards common goals.

Encouraging curiosity is key. Creating an environment that fosters critical thinking allows individuals to ask insightful questions about data, bridging the gap between data analysis and decision-making. Even organisations starting from scratch can kick-start their data literacy initiatives by fostering this mindset.

Establishing a common language around data is equally vital to avoid confusion. Developing standardised terminology and a framework for discussing data promotes clear communication and understanding. This ensures consistency and clarity in data discussions, especially during key meetings.

To tailor training and development programmes effectively, businesses should conduct a thorough skills assessment that identifies existing knowledge gaps and proficiency levels among employees. This helps customise training modules for beginners, intermediate learners and advanced users.

“Management needs to understand that people want to learn more skills but they will naturally feel malaise if they are faced with inflexibility. Continuous learning that also enables advanced training and access to certifications will signal to employees that this is the organisation investing in them,” says Hemanta.

Offering diverse training formats — such as online courses, workshops and self-paced modules — accommodates different learning styles. Hands-on practice with real data sets reinforces skills. Continuous learning opportunities, including advanced training and certifications, supported by mentors or coaches, foster a culture of continuous improvement among employees.

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