SINGAPORE (July 10): In a remote city in Thailand, about 2,000km from Singapore, a poultry farm has a problem. The five million chickens it produces weekly suffer a high mortality rate. The farm also struggles with non-uniformity in bird sizes, and an inability to detect disease early. The solution? Advanced analytics and the Internet of Things (IoT).
By collecting information on feed, body weight, egg production, egg weight and ventilation, and then using advanced image processing, deep learning and other machine-learning technologies, this farm can identify disease and predict mortality rates with far greater accuracy. Efficiency has been revolutionised. The farm is producing higher-quality chickens and eggs. And, it is differentiating itself from its competitors.
This project raises the bar for innovation in the Southeast Asian poultry industry. It also shows the game-changing power of data and analytics, as well as their potential to disrupt business models and challenge the status quo. It is no surprise, then, that the recent report from Singapore’s Committee on the Future Economy (CFE) singled out digital capabilities — especially data and analytics — as key growth strategies for the future.
Improving business performance with data and analytics is nothing new for companies in Singapore. But, the lightning speed of today’s technological evolution — accelerated by explosive growth in open source and cloud-based solutions — means more effective techniques, better tools and more connected data are fast emerging. This presents new opportunities to build highly differentiating competitive advantages. However, it also poses serious threats to companies that fail to keep up. Data and analytics are now “must haves” in driving productivity, cost-efficiency, revenue uplift and overall competitiveness.
So how should companies respond? Here are five priorities:
• Embed analytics right across the enterprise. Harness real-time data streams to capture new perspectives on the business. Use analytics to drive predictive up-selling and cross-selling, detect fraud, identify customer attrition risk and predict machine failures. Monitor customer traffic with video analytics, or get actionable insights into cyber threats, operational optimisation and employee attrition risk. Successful companies embed industrialised analytics at scale into all core processes.
• Build talent. Analytics talent is in global demand. So, look for internal potential as well as external hires. Identify employees with a passion for manipulating data and give them the latest techniques and tools. Create an analytics hub, a centre of excellence or some kind of community of practice. Ensure clear leadership by appointing a chief data officer or chief analytics officer, and give talent an avenue to exchange ideas and a proper career progression.
• Operate with new agility. Pilot new ideas with rapid prototyping and experimentation. Leverage open-source technologies to deliver fast results ahead of significant technology investments. That is what leading Belgian pharmaceutical company UCB, working with Accenture, did when they established an innovative, cost-effective Data Lab to identify untapped pockets of business value across the company. The Lab explored a series of business questions in time-boxed “sprints”, applying advanced analytics to a broad range
of internal and external data to reach an answer in each case. The approach was flexible, enabling each sprint to redirect or finetune its efforts to drive the highest possible business value. This agile approach was key to making UCB’s analytics vision a tangible reality, and creating demonstrable insights and business value.
• Think data ecosystem. Explore the possibilities of cross-business data sharing, while remembering to observe strict rules on data privacy and the Personal Data Protection Act. Form new data ecosystem partnerships to create more compelling customer value propositions. That is what one European bank has done, for example, in positioning itself as an “everyday bank” offering its customers highly targeted lifestyle products from third-party merchants. That level of innovation was only made possible with the bank’s creation of a data ecosystem supported by advanced ecosystem analytics.
• Scale and connect the technology platform. New data and analytics technologies are coming of age. Big Data Hadoop has taken the centre stage of all future data architectures. Businesses are looking at platforms that can store both structured and unstructured data and scale in a cost-effective way. These platforms connect internal data with external data sources. Businesses also expect more real-time, quicker access to much richer and bigger data sets, so that they can experiment and discover insights from data. Leading companies are carving out analytics sandboxes — special discovery environments, separate from daily operations, that enable users to experiment with new ideas.
The age of big data and analytics is not just here — it is pushing the boundaries of what is possible every day. There is an urgent need for companies to ensure they do not get left behind. Those that ride this wave of change will find themselves better able to disrupt their competitors, and better prepared for the Singapore data economy of the future.
Lee Joon Seong is managing director of Accenture Digital. He is the Accenture Analytics lead for the Asean region
