Randy Goh, managing director of the Singapore SAS office, recently wrote an article for The Business Times describing how Singapore is advancing its digital and traditional economies through the use of data science and analytics. Goh discusses how enterprises and organizations across Singapore are discovering how data can help them predict new trends, save energy costs, and more.
Barghest Building Performance (BBP) is featured prominently in Goh’s article. Goh writes that BBP is a “great example” of a Singapore startup noticing this need for data analytics serving organizations of all industries, from business and tourism to education and government. Goh applauds BBP for building its innovative, energy-saving solutions from a data analytics foundation, and he notices that this approach has made the company’s impact on client savings “huge,” up to half a million dollars per year. Data analytics can be used to record, monitor, and manage existing systems that are usually energy intensive, such as ventilation and air conditioning. So BBP’s approach saves the costs of both energy and of clients needing to construct entirely new buildings! Below the full story as published in Business Times:
Singapore has made significant progress in strengthening its digital economy. Almost daily, we see headlines about organizations harnessing data and analytics to boost sectors from tourism and retail to shipping and transportation. True to the Singapore spirit of innovation, the nation even set up the Singapore Data Science Consortium, under the National Research Foundation, to propel Singapore’s advancement in data science and analytics.
In a nation with limited natural resources, data is the fuel for Singapore’s economy. There are stellar examples of organizations, such as DBS, that have successfully leveraged enterprise-wide analytics to digitally transform their business, compete effectively with digital-native competitors and drive business results.
More Southeast Asian companies are following suit and embedding some form of intelligence into their operations, according to IDC’s latest Asia/Pacific Enterprise Cognitive/AI survey. However, Singapore Inc. is still in the early stages of its data analytics journey. For most organizations, taming big data remains an elusive undertaking. Traditional business intelligence approaches look at data to find out what happened and why it happened. In the analytics economy, data is harnessed to predict or influence future events, also known as predictive or prescriptive analytics. This is the realm where analytics plays an important role in powering advanced systems such as IoT, machine learning and artificial intelligence (AI).
Uncovering ‘new truths’ in a new economy
Singapore has always been credited for investing in the future. From creating a technology skills accelerator for all ages and establishing an open innovation platform for crowdsourcing ideas to committing to the digitization of the public sector, the country has already invested billions of dollars into various initiatives that advance the digital economy.
These are exemplary initiatives that send a clear signal to the nation to transform and embrace the constantly changing face of the future economy. Local organizations have already started being receptive to this signal. A great example is home-grown start-up, Barghest Building Performance (BBP). Analytics capabilities form the basis of their solution to help industrial and commercial buildings in Singapore save energy. BBP’s impact on their customers’ business has been huge, and the company is driving Singapore’s sustainability agenda forward. Resorts World Sentosa, one of BBP’s customers, has saved over half a million in annual energy costs. This was achieved simply through using analytics to better manage air-conditioning!
Analytics will indeed be the driver of the future economy.
However, to create lasting impact and compounding value like BBP, holistic data management is key. Each insight must feed further analysis, multiplying the value of that data and uncovering deeper insights.
This cannot happen by simply investing in point solutions or rolling out big data projects to augment functional areas such as marketing and HR. Organizations must rethink business processes, structure and even culture to significantly accelerate collaboration across the entire organization and discover ‘new truths’ that fuel differentiation, innovation and growth.
However, breaking down organization silos doesn’t mean replacing existing tools and techniques within your organization. Rather, it is about mining data across the organization to bring all the intelligence onto a single canvas of organizational strengths and opportunities.
The democratization of analytics
While harnessing data for innovation may be the promise of the analytics economy, the speed of innovation is a crucial success factor to staying ahead in this economy. To this end, organizations must make analytics accessible to every layer of the organization. A solution that is easy to use and tailor to job function needs allows employees to quickly create value from data and reduce uncertainties in decision-making.
A data-driven mindset among employees will also drive innovation and collaboration across organizations. A consistent set of integrated tools and repeatable processes for analytics will make living and breathing the innovation culture much easier for employees to embrace. Naturally, this will also propel data and intelligence sharing, allowing cross-functional teams to build on insights and compound the value of data for the organization.
Disrupt or be disrupted
The digital economy spells disruption for many organizations and industries and this can come from any source – new competitors, new business models, changing customer behaviours or eroding value in traditional business offerings. In an era where change is a constant, organizations have a choice to disrupt or be disrupted.
While data intelligence and analytics are not new concepts, what’s different today is the accessibility of data brought about by advances in computing power and connectivity. Coupled with the availability of powerful analytics solutions and AI to accelerate insights, organizations now have the opportunity to mine intelligence from their data and create compounding value across the organization.
Yet, there are some stumbling blocks. For instance, AI, one of the keys to creating value from data, still lacks sufficient adoption in Singapore according to IDC’s latest Asia/Pacific Enterprise Cognitive/AI survey. The same IDC survey found that while Indonesia (24.6 per cent) and Thailand (17.1 per cent) lead the Southeast Asia region in AI adoption, Singapore is significantly behind, coming in third. A conservative outlook coupled with the perception that the ROI is hard to quantify has led to only 9.9 per cent of companies here adopting AI, significantly behind other countries in the region.
This needs to change. Embracing advancements like AI and machine learning early on will enable Singapore businesses to stay ahead of the curve and continually provide greater value to their customers.
We are still at the beginning of our analytics journey and maximizing the potential of analytics requires the ability to capture, manage, regulate and govern crowdsourced analytics and insights. Businesses need to strengthen their analytics culture and invest in skills, training and the right platforms to set themselves up for success in the digital era.
Published in Business Times on 15 February 2019 by Randy Goh — managing director of SAS, Singapore office.