Building a Brighter Future for SMEs with Data Analytics and Machine Learning

27 Jan 2025

6 Min Read

Taylor's Impact Lab (Digital Innovation and Smart Society)

IN THIS ARTICLE

Small and Medium Enterprises, or SMEs, make up the bulk of our Malaysian economy. In fact, according to Ernst & Young , 97% of the Malaysian economy comprises SMEs which accounts for 48% of employment, even contributing to 38% of total Gross Domestic Product (GDP).

In this Digital Innovation and Smart Society impact project, Taylor’s University students demonstrate to Malaysian SMEs how Data Analytics and Machine Learning insights can benefit their business growth. In return, business owners provide feedback on the students’ presentations and recommendations.

On 3rd January 2025, 21 groups of Taylor’s University students - mostly from the School of Computer Science and the School of Accounting and Finance under Taylor's Business School - presented their research-backed business insights to SMEs as part of the Data Analytics and Machine Learning module. Having started in August 2023, the Data Analytics and Machine Learning module has been running for three consecutive semesters since, and is continuing to yield positive outcomes since its launch. By allowing students to collaborate with SMEs and their provided datasets, students are able to gain hands-on experience in the field, observing the impact of their work directly while receiving “client feedback” unlike the usual classroom assignments.

Three out of the 15 invited SME representatives, with the majority based in Malacca, were involved in evaluating and judging the student presentations on the day. The evaluation and judging were based on meeting the stated objectives, presentation skills and recommendations. The representatives present were Puan Noriha Binti Jamari representing AKAR Global, Pn Nur Mazratul Iza Binti Hussain representing AL JANNAH SHOP Enterprise, and Puan Nurhidayah Binti Abu Bakar representing JH Enterprise.

_{Selected SME Business Representatives judging student presentations}

_{Ongoing student presentation #1}

Data Analysis Is Crucial for Sustainable and Substantial Business Growth

“What we wanted for this project was to make all the SMEs aware and realise the importance of data. In SMEs, they have some business transaction records, but they don’t know how to use their data to improve their businesses. Hence, the impact we hope to see from this project is firstly, to help them know how important data is now and secondly, we want to show them how we can actually transform their data into something that is very important, very helpful and very insightful so that they can use those recommendations to improve their business,” shared Assoc. Prof. Dr. Afizan Azman, Director of the Digital Innovation and Smart Society Impact Lab, and Assoc. Prof. at the School of Computer Science, when prompted about the expected outcomes of the project.

“Early on in every semester, I will approach a group of people especially the SMEs and then ask whether they are aware about the importance of data. They may have their own business data, but the way they analyse and handle their data isn’t appropriate,” said Assoc. Prof. Dr Afizan Azman. He added that he initially became acquainted with the SME business representatives through a Data Analytics and Machine Learning workshop held in Malacca where he was a trainer. Thereafter, the SMEs approached him hoping to have their own business data analysed, having heard about the importance of data analytics.

_{Ongoing student presentation #2}

Empowering Students Through Real-World Data Analytics

Each presentation was unique to the data set provided, offering different, corresponding solutions depending on the specific problem they were tackling. The common theme observed was how best the SMEs can leverage predictive analysis - whether it be in relation to income prediction, inventory management, cost efficiency, customer engagement or product sales - for more informed decision making.

To increase awareness of machine learning for SMEs, students highlighted its crucial role, emphasising that integrating machine learning is non-negotiable, especially when considering ways to enhance a business. Recommendations included optimising costs for raw materials through long-term contracts, diversifying suppliers, and leveraging bulk purchasing; improving supplier negotiations by utilising broader insights; shifting focus towards gathering customer feedback; and adopting more sustainable business practices. While machine learning, including techniques like the Random Forest classifier (an algorithm that uses multiple decision trees to improve predictions), can initially seem intimidating, it ultimately offers a vital reality check when planning for the future of a business.

Despite the insufficient data and some communication barriers with the SME representatives, many students went above and beyond. Many students even made the commendable effort of stepping outside their comfort zone by conducting the presentation in Bahasa Malaysia, which was challenging as all other university presentations are carried out entirely in English.

“I think it’s quite fun to be able to deliver the insights directly to the SMEs, and especially seeing how we can apply what we learned in class to help the SMEs,” said Wing Hoo, Bachelor of Computer Science.

_{Selected SME Business Representatives judging student presentations}

Beyond the Classroom: Turning Datasets into Real-World Impact

“Real business owners are coming in and we present to them on how to improve their business, which is a really good experience for us to start with… so we get a rough idea of how the industry works,” says Rishi Sanjay Ramdin, Bachelor of Computer Science.

_{More ongoing student presentations #4}

“It’s a good learning experience because if we were supposed to Google some random company and do research to gain some normal clean datasets, it’s not very realistic and it also defeats the purpose as we won’t actually meet the companies. However, in this case, our work gives the SMEs insights on how to improve. Dealing with real-life situations gives us a good sense of what we are going to do in a job after we graduate,” shares Mohammed Fadil, Bachelor of Computer Science.

_{More ongoing student presentations #5}

Closing Feedback from the SME Business Representatives

“Thank you so much to Assoc. Prof. Dr Afizan Azman and team. It’s been a blessing to witness the students’ presentations. There’s so much to learn. Overall, the students showed good communication skills, body language, eye contact and their ability to present in Bahasa Malaysia is commendable,” shared Puan Noriha Jamari, SME representative from AKAR GLOBAL.

“I’m impressed with the students’ efforts to finish the assignments although there were some communication barriers and insufficient data provided. Congratulations!,” expressed Puan Nurhidayah Abu Bakar, SME representative from JH Enterprise.

This impact project has demonstrated that it is worth taking the time to closely examine how to improve the efficiency of our SMEs; after all, as shown, they are the ones who collectively shape the future of our Malaysian economy. It is also important to note that awareness alone is only valuable when followed by meaningful action. Through the Data Analytics and Machine Learning module at Taylor’s University, the recommendations shared by students have benefited the SMEs involved, providing them with a fresh perspective they would otherwise not have been able to gain. Machine Learning is a powerful tool for improving the well-being of SMEs, offering significant potential for transformative change. However, without imperative action, the risk is that these tools remain just that, without making any lasting and meaningful impact.

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