The consumer industry’s journey towards digital maturity
A focus on data analytics and digital commerce strategies in Southeast Asia
What we found was unanimous agreement on the proven value creation of data analytics: all survey respondents reported significant cost savings and revenue growth from their organisation’s investments in data analytics, with the majority also expecting future spending to increase.
When it comes to utilising digital commerce channels, digital marketing capabilities were perceived to be the top advantage; however, several pain points relating to channel conflict, fears of cannibalisation, and gaps in IT support capabilities continue to hinder efforts.
The consumer industry’s journey towards digital maturity
Building a digital enterprise
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By embedding data analytics in their digital commerce strategies, consumer companies across Southeast Asia are looking to capitalise on opportunities to better meet customer expectations and improve business performance. Achieving this, however, will require a doubling down on commercial analytics tools, such as dynamic pricing and digital marketing analytics.
Illustrative case study 1: A regional agri-business
Confronted with high logistics costs and the need to accelerate consumer uptake for its B2C digital commerce model, a regional agri-business leveraged the use of predictive data analytics to increase its productivity and conduct end-to-end customer profiling.
Illustrative case study 2: A retail chain
A retail chain with a start-up position and low market share in the digital commerce space was looking to improve its product positioning for target customers. To do so, it leveraged point of sale (POS) data to perform an integrated profiling of its end-customers and their purchase behaviours.
Embracing a digital culture
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To truly achieve digital maturity, consumer companies in Southeast Asia will need to focus on making intentional changes to their organisational culture. This, in turn, necessitates the development of an organisational digital mindset, as well as clear leadership direction and ‘tone from the top’.
Illustrative case study 1: An Indonesia-based household products manufacturer
Constrained by limited access to data science talent within the local market, an Indonesia-based household products manufacturer adopted a fast follower strategy by investing only in proven data analytics models. To strengthen its data analytics capabilities, it also hired data analysts locally and abroad.
Illustrative case study 2: A multinational retail chain
Facing a strategic choice for a make-or-buy decision on its POS system, a multinational retail chain is in the midst of conducting pilot trials with an external vendor. To boost sales on its digital commerce channels, it is also analysing trends across different Southeast Asia markets, and analysing keyword search to drive sales in response to dynamic consumer demand.
Adopting a seamless omnichannel approach
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With the subsiding of COVID-19 concerns across Southeast Asia, there has been a noticeable resurfacing of the consumer preference for offline channels. For consumer companies, this underscores the importance of developing and adopting an omnichannel approach – one that seamlessly integrates customer experiences across both online and offline channels.
Illustrative case study: A Thailand-based personal care retailer
In its move to embrace the shift to an omnichannel and data-driven business model, a Thailand-based personal care retailer created a centralised data division to support the data analytics needs of all of its business units, and merged the digital commerce sales teams with the offline sales teams to provide a more holistic omnichannel experience for its customers.
Overall, these efforts have resulted in more integrated and targeted marketing efforts, as well as more coordinated channel management. To enable more data-driven decision-making, the retailer also standardised dashboard reporting for its leadership, and introduced data governance safeguards to ensure effective master data management.
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Focusing on four critical priorities
Given that Southeast Asia is currently still at a relatively nascent phase in the adoption of data analytics technologies, consumer companies across the region display a marked preference for fast-follower strategies over leader strategies. Such follower strategies offer a number of advantages – in particular, the ability to identify proven use cases and common pitfalls for the implementation of a given digital application. The key to success, however, lies in being fast: to quickly close the gaps with leaders, they will need to adopt accelerated strategies to advancing and operationalising their technologies. Achieving this, in turn, will require them to overcome several identified challenges in data integration and channel conflicts.
The ability to implement and optimise both prescriptive analytics and predictive analytics functions is central to the success of any organisation-wide data analytics initiative. Depending on their job function, different teams within an organisation are likely to have differing levels of reliance and use cases for the two types of tools. For example, Sales & Marketing may leverage prescriptive analytics to gain a better understanding of consumer behaviour trends in their development of commercial counter-strategies, while Manufacturing and Supply Chain may rely on predictive analytics to develop their future-focused demand and supply forecasts.
To support the expansion of their digital commerce models, consumer companies should focus on optimising their delivery networks and investing in logistics capabilities. Players in the fresh products segment, for example, may need temperature-controlled shipment capabilities, or a rethink of inventory management strategies to execute next-day deliveries. At the same time, with reverse logistics becoming a major challenge for many players, companies should also consider how they can leverage data analytics to not only determine where items should be returned and plan efficient shipping between distribution centres, but also reduce the number of split shipments and optimise store-to-store transfers.
Attracting and hiring specialised talent in the areas of data analytics and digital commerce is challenging in and of itself, but this challenge has been exacerbated in recent years with skyrocketing demand for talent and the relative scarcity of such expertise in the market. For many consumer companies, this means that investments in in-house talent development has now become a necessity – and not merely a ‘good to have’ – to support their ongoing adoption of digital technologies.
