Big Data Analytics Capability Ecosystem Model for SMEs

Abstract

The unprecedented COVID-19 pandemic, together with globalization and advanced technologies, has drastically changed the business environment and forced companies to become more innovative and agile in the way they run their business and respond to the needs and wants of customers. Survival highly depends on the adaptability of SMEs to this ever-changing complex dynamic environment by taking steps in implementing Big Data Analytics as the next frontier for innovation, competition, productivity, and value creation. Based on the grounded theory, this study employed a qualitative method via focus group discussion. Focus groups were conducted with 14 government agencies, SMEs associations, business owners, Chief Operating Officers (CEOs), academic and industrial experts and directors of SMEs in Malaysia. The study revealed the challenges of Malaysian SMEs in adopting Big Data Analytics Capability, presents the criticality of Big Data Analytics Capability to overcome the identified challenges, and develops a BDA Capability Ecosystem Model that integrates the internal enablers, external barriers and support to explain the adoption of BDA Capability for value creation and support the decision-making process. This paper is followed by some policy suggestions for companies’ owners, policymakers, government agencies, universities, and SMEs. This study directly impacts Malaysia’s economy as a whole by addressing Malaysia’s Shared Prosperity Vision 2030. This research contributes to industries that are still in the low value added category with low adoption of technology. Furthermore, it will ultimately lead to the realization of SMEs as ‘game changers’ to transition the economy to a high-income nation. This study proposes a model that could help SMEs improve their value creation performance, directly influencing the country’s GDP and employability.

1. Introduction

Big Data Analytics (BDA) has been an emerging trend in both academia and industry. BDA has the potential to transform businesses and provide business intelligence to firms to respond to opportunities and challenges in this current environment. Current practices of manually obtaining, accessing, and analyzing data may no longer be relevant [1]. It is imperative that decision-makers use BDA to create the necessary strategies to meet customer needs and outcompete their competitors [2]. It also provides improved data-driven decision making for companies to be innovative [3]. BDA is taken as a significant game changer between high-performing and low-performing firms, as it allows firms to be proactive and forward-looking, resulting in revenue enhancements [4].

Data analytics capabilities refer to a firm’s ability to use technology in its business activities to capture, store, and analyze data to generate greater insight [5]. Data analysis skills are now considered a source of competitive advantage for companies to improve their performance due to their high operational and strategic potential. For example, big data analytics can help firms track their customers’ purchase behaviors, allowing companies to predict their buying trends and come up with personalized purchase recommendations [6]. This action would attract the customer’s attention and improve their purchase experience with the personalized services provided by the firm. Big data analytics is perceived as a technology that is difficult to implement, but provides significant value for firms that had successfully integrated big data analytics into their business activities, and it is also one of the reasons why big data analytics had become a powerful source of competitive advantage in the business environment today. While technologies are easy to apply and imitate by competitors in their business operations, personalized technologies such as big data analytics are nearly impossible to replicate by competitors. In addition, big data technologies will also help firms reduce cost, waste, and fraud due to their ability to convert data into intelligence and insights, improving firm productivity and business growth [7].

The significant effects of big data analytics capabilities have been discussed in various recent literature, in which firms that have stronger data analytics capabilities will have higher chances of outperforming their competitors and achieving a high level of customer satisfaction that would help improve firms’ performance in the market [8,9]. The study of Upadhyay and Kumar [10] has proved that firms’ big data analytics capabilities are closely associated with their organizational culture and internal analytical knowledge in improving the competitive performance of firms. However, in the context of the supply chain industry, the capabilities of big data analytics will positively influence the supply chain ambidexterity of firms, including the agility and adaptability of the supply chain, and therefore the improvement of organizational performance [11]. Furthermore, big data analytics have the potential to transform the way of business operations of a firm along with the challenges and opportunities presented by the environment, while at the same time keeping focus on sustainable competitive performance [12]. It suffices to believe that the competitive advantage and performance of a company can be improved by building technologies capabilities, specifically big data analytics, to enhance the customer experience.

Considering the significance of BDA, this fundamental study using grounded theory aim to address three objectives, namely (1) to investigate the enablers/importance of Big Data Analytics capability in business (2) to identify the challenges/barriers faced by SMEs in adopting Big Data Analytics in their business operations (3) to develop Big Data Analytics Capability model that explains how it can create value and support the decision-making process for businesses in the volatile environment (i.e., COVID-19).

In addition, this study addresses three research questions as follows:

• What are the enabling factors that lead to Big Data Analytics (BDA) Capability adoption for SMEs?
• What are the challenges faced by SMEs in adopting Big Data Analytics (BDA) Capability in their business operations?
• What value and how can the Big Data Analytics (BDA) Capability create value for SMEs?

The following section will discuss the methodology and the findings through focus groups in answering the above research questions. Subsequently, the findings will be presented together with the policy implications.

2. Methods

This paper uses grounded theory and employs focus groups to explore and find out the answers to the research questions. Grounded theory methodology is appropriate when little is known about a phenomenon; the aim is to produce or construct an explanatory theory that uncovers a process inherent to the substantive area of inquiry [13].

Two focus groups were conducted to explore the importance and challenges to adopt Big Data Analytics Capability among SMEs in Malaysia. Focus groups discussion was used as the method to collect data from key informants as it is the best-suited method to explore a phenomenon [14] (p. 4) and in facilitating the efforts to “generalize from a map of variation” [15] (p. 95). A total of fourteen (n = 14) key informants were selected by snowball sampling using the personal and professional networks of the researchers. Researchers also used cold calling to contact key informants via their email addresses published on their organization’s website or social networks (i.e., LinkedIn), as it was important to include key players in the industry such as government agencies, non-governmental organizations, and experts from leading organizations. The key informants consisted of representatives and leaders of local SMEs, government agencies, big data experts and researchers, policymakers, and service and solution providers. They also included leaders from national and state trade and commerce organizations that were the voice of local SMEs. After getting the contact information of the participants, the principal investigator emailed them a formal invitation. Then those who responded and agreed to participate in this research received a confirmation email with the consent form and participant information sheet. Fourteen (n = 14) key informants were deemed to be sufficient as it achieves saturation in results.

Ethical approval to conduct this study was obtained from the Scientific and Ethical Review Committee of the University of Tunku Abdul Rahman (U/SERC/75/2022). The research questions designed by researchers for the focus groups were categorized on the broad areas of importance, challenges, and role of government and government agencies to adopt BDAC among SMEs in Malaysia.

Focus Group Discussions Data Analysis Procedure

The first focus group meeting was held on 10 May 2022 in a restaurant located in Cyberjaya, Selangor, comprising 10 participants and five members of the research team. The four researchers were present to coordinate, facilitate and record the session. The principal investigator provided a briefing to the participants on the research project and informed consent. Permission was also sought for video recording. The informed consent form was then sent to each participant for their signature. The participants also received a token of MYR200 (approximately USD47) for their participation. The discussion took 3 h.

The second focus group meeting was held online on 21 May 2022 using Microsoft Teams as the platform. A total of four participants and four members of the research team attended the meeting. After a briefing by the principal investigator on the project and informed consent, participants were asked to sign the consent forms and permission to record the meeting. The meeting took 2 h. Each participant received a token of RM100 (approximately USD 23).

Participants who participated in the focus group discussion from Malaysia Digital Economy Corporation (MDEC), MASA, SME Association of Malaysia, Malaysia Chamber of Commerce, Department of Statistics Malaysia, TM one, Managing Directors and CEOs of Techno companies, Vice Chancellor and Professors from universities.

The audio and video recordings of both discussions were transcribed verbatim. Two researchers independently coded the data using the Braun and Clarke [16] 6-step guide, referring to their field notes to perform a thematic analysis. The coders familiarized themselves with the data, generated initial codes, and searched for themes independently. Then they met to discuss those themes and review them. The coders then came together with other team members to discuss and define the themes before collaboratively completing the report.

3. Results

This policy paper presents the findings in two main sections. Section 3.1. presents a review of the current policies pertaining to the digitalisation and adoption of big data analytics among SMEs in Malaysia. Evidence for Section 3.1. is derived from reviewing existing policies and followed by empirical study through focus group discussions to further highlight the shortcoming of the current policies from stakeholders’ points of view. Section 3.2. then presents major themes that emerged from the analysis of empirical data collected from the focus group discussions conducted in this study.

3.1. Critique of Existing Policies

In Malaysia, there has never been a shortage of policies or blueprints, but the execution has always not met up to expectations, especially recently. On 19 February 2021, the Malaysia Digital Economy Blueprint/MyDIGITAL Blueprint Initiative (2021–2030) [17] was introduced. By leveraging the usage of digital tools by Malaysian residents and enterprises, it aims to lead the development of the country’s digital economy. This is demonstrated by the missions carried out by the Malaysian Digital Economy Corporation (MDEC), which is charged with the additional task of developing a national Big Data Analytics (BDA) to support economic growth across all sectors and to increase local market access to the global eCommerce market [18]. The goal of MDEC is to establish a thriving BDA industry and to make BDA a requirement across all sectors, including the government sector. The goal of MDEC is to promote workplace productivity, encourage IT sector development, and give people access to the advantages of having a robust BDA. Big Data technologies are important for Malaysia’s digital economy since they are essential for the provision of effective citizen services, for the growth of innovation, and for the addition of value to industries [19].

The Malaysian Investment Development Authority (MIDA), the Malaysian Administrative Modernisation and Management Planning Unit (MAMPU), and the Economic Planning Unit (EPU) are other coordinating organisations in addition to the ones mentioned above. Data centres, cybersecurity, artificial intelligence (AI), and creative and digital content are just a few of the digital tech industries that MIDA has been pushing. Similar to this, the Science, Technology, Innovation and Economy Framework (MySTIE) of Akademi Sains Malaysia will assist in accelerating the national niched markets and socio-economic drivers that are essential in creating a long-lasting tech-savvy workforce.

Considering that Malaysia has a far higher proportion of medium-skilled workers than other Southeast Asian nations, it is critical to acknowledge the need to retrain and reskill our workforce. However, when it comes to highly trained workers, we continue to trail behind Singapore. The objectives of MyDigital blueprint, which include creating an adaptable, competent, and highly qualified workforce for Malaysia, were informed by this disparity. Given that these are the major forces driving change in businesses, a good assessment of the diverse knowledge needed for staff retraining and reskilling. In order to steer the adoption of digital capabilities in the appropriate direction, the calibre of re-skilling and training programmes is crucial. As a result, data analytics, automation, new energy technologies, and mobile internet access will be crucial industries.

One such instance is the partnership between Fusionex International Plc and Alibaba Group to offer e-Services and a digital trade facilitation platform powered by Big Data [20]. It gives SMEs opportunities to get connected with global consumers via e-commerce in Malaysia. However, Big Data’s revolutionary effects on the economic sector come at a cost. Big Data’s unique characteristics could make it more prone to security and privacy problems. It becomes a more appealing target for hackers and, as a result, presents a potential opportunity for cybercriminals due to the sheer volume of large-scale data that contains important and sensitive information that belongs to an organisation. The nature of big data, which typically contains enormous volumes of personally identifiable information, has sparked consumers’ concerns about privacy. Big Data involves data reuse, which results in data repurposing. Credentials, which include logins, passwords, and card payment information, are the most targeted data and are typically personal information. Cybercriminals will sell the data they have stolen to another organisation, which will cause many people to lose their personal information. Big Data has led to privacy-related problems such data profiling, a lack of openness in privacy policies, unintentional data disclosures, and fake data or incorrect analytics results. The current legal framework is insufficient to effectively regulate user privacy in e-Commerce due to the complexity of big data. Implementing a specific rule pertaining to big data is challenging since lawmakers are struggling to determine the best definition of big data for the Personal Data Protection Act 2010 (PDPA 2010) [21]. The next stage is to determine whether a regulation tailored to technology is required to control Big Data in eCommerce. To do that, it is necessary to strengthen the area of legislation that does not adequately manage Big Data in e-Commerce by analysing the governance standards for Big Data as a core idea. Therefore, in order to effectively manage Big Data, proposals and recommendations to enhance the current legislative framework addressing privacy law in e-commerce.

The PDPA 2010 was adopted to govern the handling and gathering of personal data for commercial reasons as well as all other issues that are connected to, whether on purpose or unintentionally, consumer personal data. The Act mandates that businesses and organisations that deal with consumers’ personal data in commercial transactions notify the data subject(s) and seek their consent before collecting or processing any of their personal data. In addition to the PDPA 2010’s applicability, there is a lack of knowledge about the PDPA 2010, specifically the idea of personal data security in general. Data users are unsure of what matters are covered by the PDPA 2010 and what actions they must take. Owners of businesses are still uncertain of what personal data constitute. A mandatory awareness campaign for every business or even for the general public would therefore offer them some exposure. By leveraging media awareness campaigns and seminars, there is an effort to raise awareness of the PDPA 2010. However, there is still potential for advancement in terms of educating the general public and business organisations. Business entities and service providers must register in order to comply with the PDPA 2010’s enforcement requirements or else they risk fines under Section 16(4) of the PDPA 2010. Since the PDPA 2010 has been in effect for some time, it is necessary for the authorities and other concerned parties to take action to determine where there are still gaps in the law that need to be filled in order to meet industry standards and legal requirements. Users must be aware of their legal protections against data breaches under this Act. The data user can be provided with simple instructions so they can easily access them and learn more about the necessary actions to take in case of an emergency.

In the private sector, there is a significant unmet need for more statistical data (Department of Statistics Malaysia) [DOSM]. To better comprehend and trust the data, stakeholders also requested more face-to-face sessions with DOSM for “data crunching” sessions. Owners of data frequently claimed to be unaware of the market demand for their data or potential use for their data. There may be severe delays because data requests are handled individually. Results of data requests are unknown due to a lack of clarity regarding the legal issues surrounding data availability and release, particularly the various acts and laws that apply to each department and agency. Data requesters indicate that the routinely provided data does not match their expected level of comprehensiveness. External stakeholders largely questioned the level of knowledge that government employees possess regarding the function and significance of open data, even though they acknowledged developments in the open data portal. Many external stakeholders complained that it was unclear how to make a request to a data owner. To ensure that a request reaches the appropriate authority and is considered, it is deemed advantageous to know someone within the organisation that owns the data.

The government has established smart automation grants for SMEs businesses under the PENJANA programme to pay up to 50% of the cost of automation. Despite the difficulties, it is important for businesses to automate some activities to increase efficiency and effectiveness. Furthermore, it is equally crucial for us to revise our perspectives on work to develop and optimise our approaches and tools. The present epidemic has demonstrated to us that businesses must automate, including embracing online business platforms, to continue providing a service to the market. The rise of online commerce and home-based companies is proof of this (especially in the retail, food and beverage industries) offering direct delivery services to the home. Over the years, banks have also adopted digitalisation at various stages and through various channels. With the expansion of platforms like FPX, Direct Debit, JomPay, and Interbank Giro, together with efforts from the local banking sector to tap into online enterprises, the digital payment industry has been expanding rapidly. As a result, fintech businesses are crucial to the nation’s process of going digital across all industries, not just banking. It is common knowledge that Malaysia is good at outsourcing and providing global business services. However, more specific action plans are needed with the MyDIGITAL blueprint [17]. What has not been mentioned in the document is the role of state governments, government-linked companies (GLCs) and government-linked investment companies (GLICs) as these entities facilitate many investments from corporate and capital markets. Thus, good collaboration and coordination among all entities are essential in creating and implementing an effective digital economy. Upon reviewing the current policies and discuss with key stakeholders in the focus groups, below are the critical points highlighted as shortcomings of the current policies:

One of the pertinent critiques of current policy options is the frequent change of policies. As corporations use policies as a basis for their decisions, changes in policy regardless of where they originate—grassroots, political leaders, or advocacy groups—will cause stress and temporary paralysis for organisations. Frequent policy changes will also cost organisations their resources, e.g., time, manpower, and extra expenditures, apart from disrupting long-term goals and directions.

The adoption of big data has been driven by technical communities so far, as opposed to the needs of SMEs. Current policies do not drive the adoption of big data among SMEs; instead, it is left to organic forces. Thus, the adoption of BDA is not structured or organised, leaving SMEs to decide and gradually adapt to the push from market forces. This could result in inequity, displacement, and exclusion of SMEs who are late or non-adopters to be left behind. Current policies in data security, privacy, and protection are perceived as insufficient to establish trust and confidence among SMEs to adopt big data. SMEs perceived the risks to be high if suppliers, organisations, or users are not adequately protected because they face risks of security breaches, and the misuse or abuse of data that may result in crisis, lawsuits, corruption of databases, and intellectual property theft.

Human resources policies do not have enough provisions to address the issue of brain drain. Current policies are not helpful in retaining local talent. Many highly talented and educated people resort to migrating or looking for work overseas where they are paid better, and their talents appreciated and rewarded. Additionally, current policies do not facilitate or encourage SMEs to attract foreign talent to Malaysia to fill the gaps and drive the adoption of big data. Moreover, projects for big data/digitalisation are awarded to foreigners or foreign organisations. Current policies do not prioritise local SMEs to undertake these large projects. One of the reasons for this is the lack of capacity and talent in local SMEs.

3.2. Emerging Themes

Further to the above results for shortcomings of the current policies, this study has further discussed in the focus groups the enablers/importance of BDA, the challenges of adopting BDA, Government, and institutions support to gain BDA capability, and what value can be created by having BDA Capability for SMEs.

3.3. Theme 1: Enablers/Importance of BDAC

3.3.1. Theme 1.1 Organisational Culture

Top Management Vision and Commitment

Based on the findings from the focus group discussion, organisational culture includes the attitude and mindset of the top management, and the digital transformation readiness of the company are critical in BDA adoption. According to one of the respondents, some senior management teams are not in favour of BDA adoption as well as expanding new markets via digitalisation. They believe that adopting e-commerce is to replace the existing business strategy, which most of the existing customers are comfortable with the traditional methods.

According to respondent Participant G, “SMEs are required to change positively in terms of working culture, innovation culture, transferring and adapting modern technology that leads to increased profits, and growth”. Yet, the SMEs readiness is a huge question mark whether they can sustain or collapse easily. Participant F mentioned “the problem in terms of the talent we are pointing up but some SMEs typically laggards in terms of the adoption of the digital method. So right now, they are catching up”.

Participant O provided further explanation “what happens is in SMEs normally, the management or the CEO or the directors would attend the exhibitions, seminars and road shows and so on. However, they are not very clear about how they could move their company due to the lack of vision and commitment”. He said “after getting back to the company from those events, they just flush it out to the middle management to the operators and engineers’ level. You saw the direction is from the management, but that direction is not being flown into the entire operations. This is the issue. In fact, one of the reasons why engineers don’t understand is because they are working inside, and they can’t see the bigger picture”.

Participant N mentioned that “SMEs will never be successful if they make a U-turn at the first juncture of a challenge. Therefore, SME leaders require the right mindset to understand the benefit of adopting digitalisation and BDA is not an option anymore, it is inevitable”. Participant A said that “digital transformation is like 90% human. 10% technology doesn’t mean that you buy a supercomputer today will transform your business”. The evolution of the BDA business models in SMEs can only happen when we have the leaders’ support to mandate and trust. Data from across all divisions will be shared only when they have a clear direction by management and clear picture of the tangible result.

Data-Driven Mindset

In today’s environment, data and information are regarded as a company’s most valuable assets. Companies of various sizes, from large corporations to small and medium businesses (SMEs), are experimenting with new transformations around the world. The use of big data is not limited to analytics of multinational businesses, SMEs also can take advantage of having enormous data to make accurate and precise decisions to enhance their company’s functions.

According to Participant E, having the right mindset is critical for leaders and subordinates. He has highlighted that “The mindset is very important, we need to create the right mindset then I think the SME can succeed”. Participants D and G reiterated that having the right mindset and willingness to change is imperative to dynamic organisational culture to adapt to the latest technology adoption.

SMEs are late adopters of big data and as a result, they are missing out on the benefits of implementing BDA into their business strategy. In recent years, many industries around the world have been transformed by big data. However, for SMEs, it is not always evident how big data is useful or even beneficial. Participant N mentioned that we should not approach this initiative and say that we want to do big data because when you do that, everyone just looks at it like it is a myth or legend, but they don’t really know what it means. You should approach this as a business objective that can be easily understood by clients, sponsors, and by all employees’ level. “For example, I am going to use the data to increase our revenue. I am going to use the data to increase our online sales”. Thus, not only leaders, all employees’ levels should build this capability to gain analytical skills and mindset to understand what data can do for them and what are those benefits before collecting any data.

Inter-Departmental Collaborations

Inter-departmental collaboration is another critical factor that was highlighted during the focus group discussions. Participant N highlighted that “some management teams oppose the use of BDAs and the expansion of new markets through digitalization. They contended that implementing e-commerce will replace the current business model, as most of their current clients are at ease using conventional techniques. Digital change, according to participant A, “is probably 90% human and 10% technology do not imply that purchasing a supercomputer today will revolutionise your company.” Only with the support, mandate, and trust of the employees and top management across different departments, the BDA business models could evolve in SMEs. Each division requires a distinct understanding of the practical outcome of BDA so that data from all the divisions be shared among them. In addition, participant H said that “before you become proficient at something, you must be ready to fail and learn a few times. Top management should provide continuous support and provide training across departments for the new initiatives taken by the employees”.

The role of coordination and control attributes within the organisation is very crucial in BDA management, which makes it easier for information to be shared and knowledge to spread among various organisational divisions. This approach not only aids businesses in understanding the precise circumstances surrounding resource consumption, but it may also result in a new method of resource integration, which is crucial for businesses to determine when and how to use various types of resources. Hence, businesses should foster a data-driven culture, encourage digital communication between departments and improve data sharing in interdepartmental cooperation. Therefore, attaining digital management of high-quality resources and examining the viability of incorporating big data into the information flows within organisation to support value chain activities in inbound and outbound logistics will be very crucial.

Skillful Talent

A critical component in the growth of an organisation is talent. SMEs are hampered by a lack of funding and a severe talent shortage, which has increased their demand for outsourcing partners. It is obvious that the HR and talent management professionals must start by educating themselves on the technology in order to bridge the skill gap in the Big Data domain. They need to understand how Big Data will serve as the strategic engine for giving their organisations a competitive advantage. The true potential of big data must be understood by managers and senior managers as well. There is general agreement in the industry that there is a talent shortage, and businesses are working to address it by reskilling the current staff and implementing a new employment model that is centred on choosing individuals with a variety of talents. SMEs must develop a thorough understanding of big data and adopt a holistic viewpoint on the big data adoption through the development of big data knowledge and education, on job training, honour recognition, awareness and promotion, etc., so that members of all levels and types of organisations can understand the importance of big data application and experience the positive impact that big data application in improving organisational performance. Businesses are employing various measures, such as upskilling or reskilling current employees, to address the lack of skills and recruiting contractors or outsourcing work to a third party supplier. This enables businesses to seize opportunities from risks. Skilful talent is critical component in any organisationt. The addition of talent can support an organization’s transition and modernization, as well as its increased competitiveness and capacity for technological innovation. SMEs should give both introduction and cultivation equal priority and do a good job of reserving and utilising big data professionals. SMEs can adopt more practical and functional methods to attract in big data talent. On the one hand, SMEs should deliberately select industry talent when hiring new employees who have specific big data knowledge and abilities and those who already have both big data skills and industry experience. On the other side, SMEs should train current employees in big data-related skills and promote their existing staffs.

3.3.2. Theme 1.2 Data Management and Infrastructure

Quality Control in Data Collection and Data Usage, Timely Manner, Reliable, Complete Data

Participant E criticised the SMEs that collect data without any objectives. He added that “I had in one government project, we received the data, the project was one year, and we have spent eight months cleaning the data because the data was just dumped there without any quality control, without any purpose, and without any objective”. He argues that leaving the reporting to analysts and data scientists alone is an ineffective method. There should be collaboration and engagement between those who provided the findings and those who use the results to make decisions. Therefore, the data scientist and data engineer team will not be able to communicate with top management to identify or translate problems into solutions if they do not have a clear direction of what is required by the management. He mentioned that leaders should have a data-driven mindset. It is obvious that the first step in closing the talent gap in the Big Data field is for managers and senior managers to educate themselves on the technology. They must understand the true potential of Big Data as a strategic engine for their companies competitive advantage.

Participant O described “What data can tell me? What analysis can workers do? What is the objective? What can I do with this? And what is the summary like? For instance, if a typical SME they have all kinds of demands and supply data. I have historical data from the last three years, but if I can comprehend the data, I can focus on seeing in the next six months what items I need to buy and keep in the manufacturing company and what demands I can fulfill for my customers”.

Therefore, according to Participant O is that the main issue is not only a lack of awareness but also a lack of capabilities because after collecting the data, they don’t know how they can actually use the data to utilise it in order to be more productive. In addition, the SMEs are on the search for the appropriate type of expertise to help them to advance their Big Data projects. SMEs are confronted with two significant issues. The first one is that there are few people who have worked with Big Data technology before. The second point is that deriving useful insight from Big Data takes a long time. Participant P said: “Typically, when you talk about data, you know that it is not concentrated in one location, it is not on one single platform. You have bits of data here, there, everywhere, you know, either from Excel to SQL to ERP or stuff like that. So, the data are everywhere, right? And I think the biggest challenge here when it comes to SMEs is how do you consolidate, how do you put this thing together in one location? Since the SME could not understand the potential of BDA, they could not mine these data in a lucrative manner”.

Technological Strategic Roadmap, Equipment, Software, Technological Process

Although equipment, software and technological process are not important as skilful talent, mindset and attitude of senior management and personnel, however the lack of such equipment and software could result barriers for digital transformation. According to Participant N, technology infrastructure is equally important, he said that “you have so many cloud providers, from Amazon to Alibaba Cloud to Google, and so many others, you should be open to utilise them”. Participant O also added that there is a need for technological roadmap where SMEs can look for future directions and also use as guidance across departments in adoption of technology and harmonising the direction. He said “that does not mean that they will not face challenges. They will still face challenges, but minimally they will have fewer chances of falling.” Other participants also agreed with technological roadmap and reiterated that” “it does not mean that they will not face challenges, but minimally they will have fewer chances of falling.”

3.4. Theme 2: Barriers/Challenges of BDAC

3.4.1. Theme 2.1 Financial Barrier

A few respondents highlighted that the implementation of BDA requires funding, which are not limited to the purchase of equipment, set up website or account, but also recruit and train staffs to manage the BDA applications. One of the respondents argued that IT department or data scientist is not a mandatory position in a company. He added that some companies do not aware of the importance of the skill set required to adopt BDA. SMEs could train an existing staff rather than hire a new staff who equip with IT knowledge. Many well-established Apps or databases are available at zero cost for SMEs to utilise to benefit them. According to the respondent, some companies are also concerned about the return of investment, due to low turnover and sales and they believe that cash flow management in physical brick and mortar business is better compared to digital transformation. Therefore, SMEs are not prepared to renew their business model and use the digital transformation and BDA because of the additional costs incurred.

Participant F said that “I think one of the problems with a lot of SME is they do not know how to invest and they do not know the reason to invest. And then typically a lot of solutions come in heavy costs. He added that solutions are simple to address in a specific way and there are a lot of solution which are affordable. Participant G argued that all this BDA is a cost for SMEs. “For them, to spend every single cent should be able to increase 10 times in terms of productivity”. How many SME do you think believes that BDA application will be able to improvise? Yeah. Okay. Then listen, if anybody wants to install the right it will cost easier than the other easily from the little ringgit. I don’t think so. And we have proposed to the government those days saying that some of the standard programs which SMEs can utilise reduce the price.

Participant C mentioned that the cost vs. benefit analysis plays a significant role when SMEs make decisions on BDA investment. The main concern of SMEs is how much they will be able to get in return to the money spent for BDA in terms of profitability. Participant D added an issue related to strategy. “How as a CEO of a small company will benefit from BDA aligned it with the strategy. At one point there are some SMEs which have benefitted from BDA application. However, on the other point some of them feel that if I invest in ecommerce now, down the line that technology will obsolete, and we are not sure what is going to come up next? We anticipate innovative technology will be coming in or upgraded in the next 6 to 9 months and therefore my investment, does it still make sense?”.

3.4.2. Theme 2.2 Technical Barriers

According to the focus group discussion, the main issue that frequently occurs during the adoption of BDA is the lack of technological know-how that prevents small businesses from understanding the flow and process of conducting BDA in small businesses. Most SMEs are influenced by the lack of information about BDA, benefits, and its functions. Furthermore, SMEs need to implement digital transformation, followed by BDA adoption. Digital transformation will require an effective technology support system; however, most SMEs have outdated technology infrastructure and facilities that cannot support a diverse range of organisational tasks and commercial processes. SMEs are unable to stay abreast of digital technologies in the adoption of BDA, claiming an inability to keep up with the pace of technology-based operations. They argued that the features and functionalities of the BDA market are significantly more complicated, requiring technical expertise and competent professionals to update and maintain systems on a continuous basis.

According to participant B, the biggest challenge will be the data source. ”You see that everyone is talking about big data. But, first and foremost, without data, how can you do data analysis? We are talking about an SME. Many SMEs are so focused on making profits, but they never put a strong emphasis or focus on collecting data. So what the government can do is, instead of collecting and remitting data, it should be consolidated and then shared according to the ministry”. Participant B also suggested that governments should start compiling these data, as some of the data are not publicly available. He added that some data which are industry relevant can be shared to specific industry examples like specific SMEs involved in international trade will require import-export related data. Participant A provided an additional explanation regarding open-access data, which are readily available such as Euromonitor, but unfortunately, it has been underutilised. She also added that there is a need for more real-time data as well. “My good case study would be my personal investment in the chocolate company. We use a lot of data. I can tell you who likes chocolate and what type of chocolate they prefer. And you can use those kinds of data to work towards your strategy on how much money you are going to spend before you can convert one person to become your customer. These data are captured on e-Commerce platforms such as Shopee. They give you a lot of data. You can even mention the customer lifetime value example for every RM15, I put on Facebook, I acquired one customer. I know how much this customer will contribute to me and whether it is worth spending RM15. So, these are the platforms that are already available, but whether the management look at it and acts on it is crucial. Because data will remain as raw data if you don’t act on it?” Participant A added.

3.4.3. Theme 2.3 Shortage of Skillful Talent

Almost all the respondents reflected that lacking local talent is a stumbling stone for Malaysia be competent in Big Data analytics. The main reason for causing low adoption of BDA is due to lack of local talents in the job market as generally known, high technology required skill labour. SME industries are undoubtedly required skill labour to execute job task for BDA.

Participant F mentioned that skillful talents such as data scientists are highly in demand for BDA adoption in these industries. He also said that “we have data scientists, unfortunately; I think the numbers that will be created by universities is not enough because the larger companies are grabbing all of them”. This is because companies like Petronas are able to pay the data scientist high. Therefore, SMEs are struggling because they cannot get their expertise.

Participant O suggested if there is an ideal data expert who knows the whole big picture of the business that would be great. “If he is brilliant at mathematics and statistics and works in the manufacturing sector but isn’t well-versed in the said industry and have knowledge about the restrictions of supply chain operations, he won’t be able to use Big Data to address supply chain challenges”. Therefore, sophisticated computational science and advanced analytics are all part of data science. Even though there are specialists skilled in one of these areas, the industry needs a consistent supply of workers who are knowledgeable in a variety of fields.

When asked to comment on the shortage of talent in Malaysia, Participant N commented that “is not just in Malaysia, everywhere around the globe I go to where they it’s in United States, San Francisco, in China, in India and Thailand, Singapore, it does not really matter. Talent is always in shortage and that comes back to the same thing as to write work to work with the right partners so that they can supply you with the talent and the experience, not just from a technological forefront, but also how to approach the business objectives. That is important”.

Another respondent, Participant N was of the opinion that the problems within SMEs are the same as those within large enterprises. The weightage could be different. He said that “over the many years, we have noticed that today the problem with adopting big data is really the human factor problem. It is a human factor problem and not a technological problem. Today, technology is so mature and there are so many options that technology is no longer the problem and no longer the barrier. Let us just say that whenever SME or even enterprise organisations, for that matter, enter a big data initiative, expectations are not managed. Why is that so? They do not really know what they are going through. They do not know what the result is”. He also mentioned that SMEs are not aware of the potential challenges and are totally blindfolded by the issues they could face in BDA adoption. Therefore, when they face problems during the implementation, they would just easily abandon the project.

3.4.4. Theme 2.4 Data Security

Participant E highlighted that BDA presents a significant issue, particularly for SMEs, in terms of data protection and privacy. In BDA, there is a chance that personal data will be misused. The adoption of big data, particularly in the financing agencies, academic, and medical sectors, is lower due to data privacy and security concerns. Several studies on data privacy and security have been undertaken by various scholars. Malaysian SMEs, on the other hand, are unable to absorb these higher expenditures. Participant E also mentioned that some SMEs are also worried if their proposal being taken by other people. He added that sometimes the proposal submitted for grant and being rejected but being used by somebody else who advertised the same type of product and with same objectives with the grant they received.

3.4.5. Theme 2.5 Lack of Data Literacy

Participant A mentioned that data are available, but in a form that only data scientists could understand. SMEs, who lack data literacy and would need someone to do some cosmetic translation, reinterpret the data so that it is easily understandable. According to participant H, ‘Actually, the use of data is very wide. We want to look at advantages now where we build capabilities. Looking at the process, you only need data to optimise the process regarding technology and strategies. You look at the data to grow your talent pool. Like, for example, a simple manager would ask me if I want to increase revenue. It is quite a simple question to increase revenue. But then again, as an entrepreneur, you should know where the source of revenue is and what the strategy is to get it. So, if you do not ask the strategic question, they do not get the solutions or answers they are looking for. The quality of entrepreneurship in SME is very low.’ Participant D added that SMEs are having problems making sense of the data available. SMEs need to find support by asking the right questions to the service provider so that they can find solutions. According to Participant B, the biggest challenge will be the data source. “You see, everyone is talking about big data. But first and foremost, without data, how can you do data analysis? We are talking about an SME. There are many SMEs that are so focused on making money, but never put a strong emphasis or focus on collecting data. So, I think the government can do is, instead of collecting and remitting data, it should be consolidated and then shared according to the ministry”.

3.4.6. Theme 2.6 Lack of Awareness

Respondents were not satisfied with the dissemination of information by relevant organisations, as their level of awareness on the social media and websites of government agencies was still low. Respondent participant A stated that they were not aware of what kind of information available on the government agencies’ website. Regarding the evaluation of the experience with government agencies, respondents were of the view that their cooperation and communication with government were good. Respondent Participant B commented that government agencies need to be responsive and proactive to the issues and challenges faced by SMEs, particularly the small and medium industry, especially in reaching out to new markets and taking efforts toward sustainable growth of the industry. A few respondents commented on the smoothness of the application procedure, documentation process, responsiveness of staff toward inquiries, and duration to obtain approval/reimbursement from government agencies. The respondents viewed government agencies as proactive in organizing and conducting relevant programs for SMEs. However, government agencies must be more concerned with industry needs, especially when they decide on their programs and services.

Participant G highlighted whether the government has created enough awareness about BDA. “Are we doing enough of an advertisement or explanation for how big data will make SMEs a better competitor compared to others? I have not seen anything on television so far or in any other advertisement. So, awareness can say less than 20%. Second, how are we going to guide them to adopt this technology? “ However, the true hurdle for SMEs arises when they consider investing resources to translate big data into business applications, as the related hardware and software costs are too expensive for small businesses.

According to participant P, there is a lack of awareness which is the main reason SMEs are not implementing BDA. He said that Malaysian SMEs have a very poor degree of awareness of big data, and they appear to be reluctant to enter an area that they do not seem to grasp. He highlighted that it is a bit slow for SME owners to understand the benefit, the overall benefit, or the big-picture benefit to operations. Another respondent, Participant O, also agreed with Participant P’s point, where there is lack of awareness among SMEs. But he said that this is due to lack of understanding on how BDA can contribute to ROI. Participant O said”Because we are talking about the SME and for them it’s all about money for sure and when they make some investments, what kind of ROI can they see in the next three or five years? So, this is something that it is very hard for them to comprehend. Machines can produce output so it is straightforward and they can see the results. But when we talk about big data, they need resources. This is another issue as well. They do not have enough resources”.

According to Participant E, “first of all, when we discuss awareness, for example, every decision maker in any SME is going to make sure that if they adopt this technology, what can they gain, how this technology can help them, how this technology can generate values for them”. He added “Even if you show them a lot of success in fact task or project. You have no idea whether that technology can help them or not. This is one issue. The second one is most of them, don’t have the right data and they don’t have enough data. And mostly they are totally distributed, and they are not integrated. And the most important part of this data is not being collected for analytics. They just dump data. If we manage to help them to define what data set should be collected, for what purpose?”

3.5. Theme 3: Government, Institutions Support and Universities Collaboration for BDAC

Results from the focus group discussion imply that respondents were partially satisfied with the relevance of the information provided by government agencies to industry, especially on information related to market trends, market analysis, and so on. This indicates that there is room for improvement regarding information dissemination. Based on one of the respondents, the government is not taking a leading role in many of the BDA initiatives. There is a lack of government support and involvement; moreover, the government’s incentives and policies are unclear, training is not relevant, government’s response is slow and takes a long time. SMEs are reluctant to adopt e-commerce, which is relatively new to them, due to perceived uncertainties that resulted from their past experiences dealing with government agencies.

In addition, stakeholders’ concerns regarding the accuracy of information from government agencies, highlighted that the information provided by government agencies is complicated and has too many datasets as it takes too long to find specific information. These may have contributed to the lower satisfaction levels related to the information dissemination criteria.

Companies are seeking the best available techniques to get information from the massive amounts of data that are being generated on a regular basis. Experts who could use BDA to make successful judgments are in demand. They must be able to combine Big Data results with information gained through other methods. Participant P shared his opinion “how can you use this data to provide meaningful information for the business direction. So, this is the gap right now with these particular industries”.

The process of obtaining a grant from the government is difficult and takes a long time. Participant N said, “there have been many complaints and a lot of feedback from the industry saying the entire process does not provide a lot of clarity as well in terms of what needs to be done and the level of details and information that needs to be provided to agencies and ministries sometimes”. Since the procedure is very lengthy and it is not sustainable.

There has been HRDF support in terms of financing and supporting talent training, providing skill sets to build the competency of SMEs. Participant N mentioned “we do a lot of those training as well, and we see a lot of SMB players alongside enterprises as well come in and provide the necessary personnel for us to train. But again, that is not necessarily something that can be done overnight, because even if these talents are trained in big data technology, that is the very first time that they are experiencing it”. It is likely SMEs will face huge challenges and without the support of the executive, clarity and expectations being managed, it will be a failure as well. Participant N insisted that “The government does provide the kind of support and they have received valuable feedback as to the manner of how it has done but whether the public is embracing it in the right way with the right expectations remains the challenge.

Participant P is of the opinion that the government is providing these trainings by MDEC, MIDA and so forth. He added that the challenge comes back to the implementation part of it, where it depends on how SMEs relate big data analysis to their existing processes because this is where it will make the most difference. This includes an understanding of the current processes, the challenges and then how do SMEs use the output from BDA initiatives to optimise their operation. Participant O mentioned that it is important for SMEs to look at three distinct factors in terms of people, processes, and technology. He also added that it takes 1 1/2 years just to get approval for the grant and SMEs should not rely too much on grants and be able to be financially independent.

Therefore, the government needs to take a more transparent approach and share some of SMEs success and failure stories on how they have utilised that sort of grants and how they become successful in terms of integrating that loan into their operation to other SMEs. Participant P commented that there is no transparency as to which grant is successful, what was the output, how they achieved it and how did this benefit the SME entirely?

Participant E said that there are initiatives from the government and associations that are helping SMEs to build these sorts of capabilities as they supported the individual volunteer to learn data science. The government gave financial assistance and loans which is based on mechanical and quantity. Unfortunately, there is a lack of evaluation of whether they are offering to the right people, or whether these people are capable of utilizing it efficiently. He also highlighted that the government do not have a proper monitoring system at the end of the period to see what sort of result they can receive from the grant to SME’s as they never follow up.

There is a suggestion that instead of the government providing grants, loans, and financial assistance, it is important to develop mechanisms for better evaluation and monitoring. Rather SMEs must go through very tedious process to apply for the grant but finally, there are loose procedures to monitor them. Participant E said, “just, frankly speaking, I must say 90% of them just wasted time and money”. Therefore, the government needs to take a more transparent approach and share some of SMEs success and failure stories on how they have utilised that sort of grants and how they become successful in terms of integrating that loan into their operation to other SMEs. Participant P commented that there is no transparency as to which grant is successful, what was the output, how they achieved it and how did this benefit the SME entirely?

Participant N mentioned that the government, in its fairness, has been trying to do all that they can do such as providing grants, approving grants, allocating of loans, training, and business integration. “I think the challenge over here is not what has been implemented but how it has been implemented” he added. According to Participant N also, Higher learning education institutions could provide the resources and talent to sandbox certain solutions. He added that government and ministries have been trying their best to introduce all these policies and spread awareness however “the teams who executing it misused their power to monetise for their own interests. They viewed it as an opportunity to bring in their cronies and their preferred suppliers or they view it as an opportunity to steal the intellectual property”.

Participant N also shared his experience about “CNN management is not technological guys, and they are not even functional or business guys. They are just looking at P&L balance sheets etc. So, it must translate to a value in ringing or U.S. dollars. So, we went back, did computation, and work out scientifically and came back and told them that you could save at least $7 million on a yearly basis based on this piece of technology”. This is because the management and shareholders could see tangible factors and results that hit their balance sheets and income statement. Therefore, Participant N insisted that if SMEs are trying to revive or initiate such BDA initiatives without having a dollar or ringgit sum attached to it, even the piece of technology can enhance efficiencies, benefits, and advantages but unfortunately it will not be supported”. “So, I think that awareness should take a distinct perspective. Many of the shows and events where people talk about technology and the wonderful things that they can do, but more importantly is that does it bring a business benefit that has a dollar attached to it, and that comes in either an increase of revenue or profit” he added.

Participant N commented that “there are so many initiatives taken by various parties such as MAIDA and KMS. It is in terms of ministries and agencies, they have grants, and they have loans for SME’s to use and utilise to adopt big data capabilities. So that is all helpful. But I think the reliance on government should not be there.” According to Participant N, even though we do not receive incentives from the government, SMEs still should proceed with BDA initiative. If SMEs view BDA as not an option, it is something that they must do, then they would persevere through all challenges, whether it is monetary challenges or technological challenges. He added that businesses today with a traditional approach and not using BDA is not a wise choice. Many competitors overcome many challenges and they are coming in with visual technologies together with traditional methodologies. Therefore, it is a disadvantage for SMEs to just do their business in a traditional way and they should not rely on government support. In addition, a lack of investment in this sector hinders the adoption of digital technologies and their efficient use to boost productivity and gain access to new markets. In addition, a lack of entrepreneurial skills may prevent SMEs’ and entrepreneurs’ adaptation to digitalisation and segmentation of industrial processes.

Participant N explained further that “it’s important to have the right set of partners because whatever you are doing for the first time, you do not want to be doing it alone. If you’re combining data sources from 10 different data sources, for example, it’s unlikely that within the organisation you have people who are still in Oracle, Siebel, IBM, Microsoft, in social media. That is highly unlikely, but you can find partners who do this on a day-to-day basis and two or three partners or even one partner who has specialisation in different data sources”. When the companies are combined, they will be able to provide their expertise and experience from the pitfalls that they have accumulated over the number of years and key success factors. He believes that there are exceptionally good Malaysian companies who have experience in doing this. He explained further that it is a challenge for SMEs as well whether they want to use the partners recommended by the government because sometimes the government ministries, bodies, or committees who oversee these recommendations might be perceived as being biased with hidden agendas because they are closer to certain partners. Anyway, whether it is true or not is left to be seen by the industry players as it can be a perception which causes some level of suspicion.

3.6. Theme 4: Value Creation

3.6.1. Theme 4.1 Understanding Customer Needs

Building good customer relationships and understanding the needs of customers is essential for business. People are more likely to buy from brands with whom they have a personal connection. Big data can be used to foresee the demands of certain consumer groups, as well as assist SMEs in gaining a better knowledge of their customers. Both criteria assist SMEs in microtargeting customers, allowing them to engage with individuals who are most inclined to buy at a certain moment. Using big data to get to know a customer on a more personal level could improve sales by proposing more relevant products and contacting them during peak buying periods. BDA can also be used to reduce the time it takes to create sales while boosting the effectiveness of campaigns by exceeding their goals through customer, product, and promotion data. Participant N further explained that “what we do is to use data sets such as customer data, online traffic data, external data sources such as social networks, and open data sources such as Agoda, and travel agencies from airlines, we combine those datasets and find insights intelligence to see how we can improve the sales of a specific hotel or a specific resort. So, what we do is combine our datasets”.

According to Participant N, they can advise this hotel on the best price point. How should they price their online suites for their online rooms so that they can get the best number of transactions? The total number of transactions so that they can increase their revenue or reduce the cost. So that is one example, or you have done that for insurance companies as well large and small to see how they can increase their profitability, how they can increase their sales by 178% for example.

3.6.2. Theme 4.2 Improving Operational Efficiency

Generally, BDA projects begin with the identification of a significant business problem and the development of a solution approach. According to Participant O, any company process that creates data may be enhanced by proper data analysis. He also added that by scanning the customer logs data to establish which methods consumers will use to contact the organisation and the duration of each conversation, small businesses utilise data analytics to generate value from their idle data assets. This analysis can help SMEs not only improve customer service efficiency but also gain insight into client preferences and demographics. Participant P mentioned that supply chain management and resource optimisation are made more effective by evaluating data collected as part of everyday operations in near real-time.

Participant N mentioned ”I am going to use data to reduce our operational inefficiencies. I am going to use the data to reduce our costs. So, when these things are spelt clearly as a business objective, a business use case, rather than saying that I am going to adopt big data technology. I think it gives much more clarity. You will have more support and better comprehension of the relevant parties. So, as an example, we have done this for many of the travel and hospitality clients. The hotels are 3 star and 5 stars.”

According to participant P, ”We had an extensive portfolio of products, services, and costs during the pandemic. One of the efforts that we made was to try to streamline this in a sense that, let us say, using the data that we had and mining those data objectively. The objective was to streamline our product portfolio. Since we manufacture most of these products, those data were also used to forecast the purchases of materials and the use of warehouse space, the use of the factory shop floors, etc. What I mean by the output was the results that we obtained so that we were able to basically streamline our existing product line. We had approximately 62 products and we were able to streamline them to about 38 products now because now using the data, we had visibility to how fast those products moved”.

Participant P mentioned that his main source of data is from his ERP system, as he can generate information on sales, finance, manufacturing, and resources. They integrate and consolidate all the information together to get visibility of the product in terms of how fast the product moves and how they can forecast stock. Therefore, these data are transformed in the way that is relevant and beneficial for them to conduct their business. As a result, the tangible result was that they were able to reduce costs by about 15%.

3.6.3. Theme 4.3 Improving Future Sales

Through the BDA application according to Participant N, customer experiences and behaviours can be captured and gathered from a variety of devices, including smartphones and tablets. Businesses can predict the time, place, and other variables that are most likely to lead to future sales by collecting and analyzing data about their customers’ transactions linked to customer loyalty cards to better understand purchasing patterns. BDA may help SMEs identify patterns and learn what their consumers find intriguing or appealing. Businesses can monitor consumer habits and market patterns using data gleaned from social networks, browser logs, and public data sets, helping them actively engage with their potential customers. According to Participant N also, data analytics can record information on a reference, whether favorable, bad, or neutral, and produce insight that leads to a wiser strategic decision whenever a small business is referenced on Facebook, Twitter, Instagram or other social media sites.

3.6.4. Theme 4.4 Increasing Profitability

A data-driven culture, according to Participant E, is one in which data is accurate, shared across divisions, easy to access, and low-cost to maintain. All workers can use data in their daily choices in ways that quickly address business problems and provide the organisation with a competitive advantage. According to Participant O, the greatest value of big data for small businesses is how it automatically and instinctively converts workers into data specialists, without requiring substantial training or programming expertise. Data analytics is the key to enabling today’s and tomorrow’s workforces. Business benefits from data-driven analytics systems such as BDA include more effective marketing, better customer service, enhanced operations, additional revenue prospects, and competitive pressure over competitors.

Participant N, SMEs can use online data and external data sources to help them increase their revenue or reduce costs. And once that is achieved, then SMEs would have more sponsorship and stronger support from companies because they are now seeing tangible results. Generally, SMEs work around two main objectives, that is, increase the top line or safeguard the bottom line.

According to Participant O, if I can predict when my machine is going to be down based on the data that I have received before, that really helps especially for planning and scheduling in operation. So, it is an exceptionally good advantage if the SMEs can add a kernel of technology to be honest, especially in big data. But right now, they have all these data as I mentioned. So, they take all the temperature data and all the process parameters data, but they keep it for auditing purposes and not translating it into business value.

3.6.5. Theme 4.5 Ability to Forecast Sales

Participant O claimed that one of the advantages of BDA for SMEs is that it can forecast sales and also estimate preventive maintenance for machines. Therefore, SMEs can plan their preventive maintenance even before any downtime occurs to ensure that their operations are not interrupted. Eventually, this will help them meet on-time deliveries and satisfy customers, which can generate more profit. He added that BDA will increase ROI while reducing costs and generating value for SMEs.

Participant E said that “just having the tool and using it does not necessarily make any difference. No business value generated. Normally, SMEs already have plans to do something; then they will be looking for data to support their decision as to whether they are on the right path. Rather than the other way around, the data should tell them what kind of decision they need to make”. Therefore, there is a need for the right mindset and to implement or use those data for decision-making.

4. Discussion

The enabling factors that influence the adoption of BDA are categorised into five groups: leaders/personnel/support, top management, data management systems, technological factors, and organisational culture. Leaders/personnel/support emphasise the importance of developing talents’ skill sets and knowledge in the area of BDA. The top management in SMEs must also have vision and commitment to steer the organisation in the right direction. The right data management system is one that collects complete and reliable data and subsequently translates them into usable insights or solutions in a timely manner. The dynamic organisational culture would consider the importance of data in business. This data-driven culture would serve as a catalyst for inter-departmental collaboration and knowledge sharing within the organisation. Finally, technological factors entail an overall strategic roadmap of technology within the organisation that details the required equipment, software, and technological processes. It should be adaptable to keep up with technological advancements.

The barriers to adopting big data in SME operations are found to be the influential factors that affect the success rate of adoption. The barriers identified in this study are the awareness issue about the benefits of BDA, technical know-how, data literacy, financial restrictions, shortage of local talents, lack of institutional policy and support, lack of leadership commitment, lack of the data-driven mindset of leaders, and the issue of data privacy and data security. These issues are perceived as barriers to big data analytics adoption that lead SMEs to face risks, undertake extra costs, and face uncertainties.

Government and institutional support are aimed at creating policy support. Several implications could be evoked from this area. They are digitalisation adoption programs, national data sharing policy, and mentoring/networking matching. The foundation for BDA adoption must first focus on digitalisation, as BDA will be ineffective if SMEs have yet to start their digitalisation journey. Subsequently, a national policy should aim to encourage all stakeholders to share data. The participants mentioned the need for a centralised channel to obtain data. With many SMEs still lacking in BDA capability, the mentoring/networking matching would bring about inter-firm strategic collaboration between SMEs who use big data and late adopters. The government plays an important role in the ecosystem by working by setting the policy and provide a support with universities and providing institutional support. The government-universities collaboration aims to reform education systems by developing a progressive and up-to-date curriculum. This will generate more young talent, ensure a steady supply of skilled graduates in BDA and address the issues of the shortage of data-skilled human capital. At the same time, this will also benefit universities, as it will allow them to stay up to date on industry developments.

Value creation as a result of BDA capability, comprises as understanding customers’ needs on a more personal level, improve sales by proposing more relevant products, and also reduce costs by improving operational efficiency. BDA not only improves customer service efficiency but also gains insight into client preferences and demographics. Through the BDA, customer experiences and behaviours can be captured to predict the time, place, and other variables that are most likely to lead to future sales. BDA can help SMEs identify patterns and have more effective marketing, better customer service, enhanced operations, additional revenue prospects, and competitive pressure over competitors. BDA can forecast sales and estimate preventive maintenance for machines to increase ROI while reducing costs and generating value for SMEs.

In summary, the above discussions of the themes for the enablers/importance of BDA, challenges for BDA adoption, the role of government and institutional supports are integrated to develop a BDA Capability Model that able to create value for SMEs. The model is discussed in the following section.

5. Policy Implications

The results of this paper imply that the existing policy needs improvement given the significance and importance of the adoption of big data among SMEs. This policy paper found that developing BDA capability among SMEs in Malaysia is challenging although industry players, policymakers, and government agencies recognise the importance and urgency to do so. The importance of developing BDA capability among SMEs is found to be crucial for business sustainability and performance, but also for survival in the coming years. However, the overwhelming challenges were perceived as barriers that obstruct and prevent a faster and more consistent in adopting BDA among SMEs. In general, the entire ecosystem lacks the necessary mechanisms to support and facilitate the development of BDA capability such as data security, lack of awareness among and support from internal and external parties, and others. Thus, to overcome these challenges and improve the quality, pace and sustainability of developing BDA capabilities among SMEs in Malaysia, this study synthesises empirical data (i.e., focus group discussions) and reviews of past literature to develop a model that integrates the factors in creating an ecosystem in which BDA can add value and support the decision-making process (see Figure 1).

6. Policy Recommendations

The findings show that lack of awareness consistently surfaced as a barrier to BDA Capability. Government should increase its awareness campaigns specifically on user-friendliness, up-to-date website content, and accessibility. The government should continue to promote more publicity using commentaries on various social networks, the Internet, magazines and newspapers to increase stakeholder awareness. On the issue of creating awareness, government agencies, councils, and associations should publish and share materials with SMEs through talks, exhibitions, and roadshows to disseminate information that is relevant to them.

Government should continue its effort to consolidate its activities and make excess easier and faster for those who are interested in gaining more information. The consensus among the focus group participants also indicates that there are overlapping roles of various government agencies that provide the same function. These government agencies with the same objectives should join efforts and develop better programs and services. The consultation process with the multistakeholders must be meaningful and inclusive to ensure the sustainability of these programs with a focus on clear targets that cover all outcomes. Therefore, it is important to set up a multi-stakeholder committee comprising of stakeholders from the ministry, council, associations, public listed companies, SMEs and universities to oversee and formulate a robust framework for future execution nationwide. Stakeholders’ priorities may differ for specific types of training, so it is reasonable to explore the preferences of stakeholders in the context of the training needed for their businesses. Government agencies should collaborate and work together with one of the ministries becoming the leader rather than all agencies having the same agendas. Furthermore, it is recommended to have a data exchange platform where all government agencies are linked together, such as one-stop center.

Government and universities should work closely to develop adoption programs, and the focus is very much on digitisation to utilise big data analytics. Big data will not be effective without focusing on digitalisation. Our findings indicate that one of the biggest issues is that a lot of SMEs have not even started the digitsation journey. Therefore, government agencies should support SMEs in terms of digitisation, such as online payments and digital marketing. It is recommended that SMEs owners also start small by engaging in digital marketing, such as how to sell things online. Government agencies should provide training and financial support to SMEs on digital marketing perspectives and access to sell online, how to look at the target marketing by utilizing big data analytics. This is a good stepping stone to solve a basic problem.

The government should develop a national data-sharing policy. So, under this policy, it is not a mandatory policy, but it is basically the start as a guide everyone to encourage everyone to share data.

Relevant ministries and agencies should mandate to create projects with new opportunities for SMEs which have some form of big data elements that more talents will be gravitating towards the country’s initiatives. Malaysia used to be at the forefront in terms of digital technologies, IT, computer science, and 3D. Therefore, such a policy would help Malaysia move in a similar direction.

Government policy should not play the role of providing the solution, as the cost comes from the taxpayer. It is recommended that government create open-source solutions which are easier to use and a premium from the business innovation standpoint. Government agencies could focus on developing a Consortium Business Support System through Collaboration among private sectors, government, Higher education Institutions, multinational companies, and business associations. This could be a common platform for knowledge sharing for technology and skills and consultancies regarding BDA applications that operate at a prominent level of accountability and transparency which consists of advisory/expert panels from successful companies. This consortium could focus on strengthening ICT capabilities, business mentoring, product innovations, event management/promotion, and working on a shared platform with special incentives to enhance competitiveness in existing markets and create new possibilities for market expansion through BDA adoptions. Apart from that, through this collaboration network, a Knowledge Management System can be developed and made readily available to ensure the reduction of unnecessary duplication of data.

Furthermore, government agencies must collaborate with SMEs and other companies to reform the education system to ensure that graduates have the appropriate skills. School curriculums should be progressively revised to include updated content on BDA starting with the primary school level. Government policy should encourage industries to participate in these programs, as it will increase the employability of students by inculcating the skills required for the BDA. Relevant programs should be designed and provided for internship placement for students, as well as employment opportunities once the student graduates.

The government should collaborate with universities to produce more young talents that would help in injecting innovative ideas and perspectives on how BDA could serve the industry better. Universities to send full-time staff and students for training and Continuous Professional Development (CPD) seminars, workshops, educational visits to SMEs so that they are kept abreast of the latest developments and continue to enhance SMEs by providing business solutions.

Government agencies should provide data scientists services by providing expertise and consulting so those small companies can use their service to analyse their data instead of employing data scientists, which is very costly. Universities can also provide these services to SMEs to analyse their data to be more relevant. Universities are a neutral party. The companies will have trust in the universities as the data is protected and will not be leakage. The student could be involved in this project and they will be absorbed later to work with the company after their graduation. Collaboration between universities and industry needs to be bridged as well, especially for big data analytics, what is expected in the industry basically what is happening on the real application.

The findings also raised the issue that there is no transparency as to which grant is successful, what was the output, how they achieved it, and how the grants benefit the SME entirely. Thus, the government needs to take a more transparent approach and share some of SMEs success and failure stories on how they have utilised that sort of grants and how they become successful in terms of integrating that loan into their operation to other SMEs. It is highly recommended that instead of giving government grants to individual companies to hire data scientists, it could be channeled to universities to support the SMEs and produce more data scientists.

Recommendation for lack of talent issues, government policy should be drafted to attract and help to retain talent within the country and create job opportunities such as more projects that utilise the latest technology from the government sector and private sector. Our findings indicate that if new technologies are not made available to them, even if they are paid high, they will fly to Singapore, the United States, or UK, where the challenges and opportunities are in abundance.

SMEs are recommended to develop a technological roadmap on where they want to be in five years or 10 years from now and how they would like to move on.

Government agencies could take up more initiatives and collaborations to regulate, support, and promote collaborations/bilateral relationships within SME industries and with other public listed companies. Moreover, processes, systems, and policies must be specific and solidified to encourage all SMEs to provide relevant information regarding their business success factors on BDA application and competitiveness.

Government should showcase examples of successful companies in implementing BDA, sharing information about how BDA has improved sales, reduced cost, and increased profitability is very important. It is recommended that the training provided to SMEs by government agencies needs adequate monitoring to determine whether the SMEs who attended achieved their objectives in terms of using BDA to be more productive.

It is recommended that government not work in silos, rather they need to be in the industry assembly to collaborate with the investigation on what the industry is lacking and required. Perhaps the focus can be on innovation, come up with companies that can offer solutions to address innovation for SME. The focus must be more market-driven and on finding a simple solution with lesser costs. Therefore, it is necessary to make it simple and affordable to encourage small businesses to adopt BDA. Government agencies could play a very crucial role in educating the public by a section in every newspaper and mass media to publish about the benefits of big data analytics and sharing some successful business cases to create awareness and encourage other SMEs to adopt BDA.

The policy recommendations will need to be in line with the National Recovery Plan. The National Recovery Plan has outlined that the digitalisation of businesses is a key factor for SMEs’ survival as consumers move towards online purchasing. With this digitalisation, the usage of big data is inevitable. The literature has also pointed out that when SMEs adopt BDA capabilities, it would lead to gains in areas of strategic decision-making [22], a better understanding of customer needs [23], and of course, business performance [24]. The above recommendations provide a list of suggestions which can be taken up by the various stakeholders, including the relevant government ministries and agencies, and the SMEs themselves.