Seng Hua Hng (SHH) Foodstuffs Pte Ltd, the largest nuts manufacturer in Singapore, was the company behind Camel Nuts, a trusted household brand name in nut snacks in the country. Camel had a prominent brand presence both domestically and internationally in 29 countries. Aspiring to continued growth, in 2016, the company set a strategic target of 100-100-10, which stands for S$100 million (US$72 million) revenue, geographic presence in 100 countries and a profit of S$10 million (US$7 million) by the year 2020.
In late 2017, a year into his new role as Head of Group Finance at SHH, Colin Chin commissioned a team of SMU accounting students to build data analytics capability in-house to help the company achieve its strategic goals.
In the past, SHH as a traditional family business would rely on ballpark estimates to make key strategic decisions, for example, to determine annual production capacity. The practice of using past years’ demand in current year’s production planning had continued throughout the decades. Some of the key challenges SHH faced was the lack of accurate demand forecasting on a periodic basis and the absence of important financial information that would support the risk assessment of expansion to new foreign markets.
By leveraging the power of predictive analytics, Colin wanted to find answers from the data insights to help him overcome some of the challenges the organisation was facing. How could SHH grow its existing markets, both domestically and overseas, and by how much? What are some of the new markets SHH can enter? Will there be any potential cannibalisation of existing products if SHH were to introduce a new product line? Could data analytics help decision-making at SHH to become data-driven, hence enabling the company to better assess if the goals of 100-100-10 were within or out of reach?
This case is about an SME’s journey in developing its data analytics capability, through which the students will learn (1) to determine the relevance of data analytics to companies; (2) about the steps taken in a typical data analytics development project and its critical success factors; (3) how data analytics may enhance a company’s strategic planning and operation execution; and (4) about the next steps upon completion of data analytics capability development.
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