Photo: Tan Shong Ye
Data analytics is the process of examining data with the purpose of getting information to provide useful insights and help with strategic business decision-making. Data analytics plays a pivotal role in the decisions made by corporations, regardless of size. Currently, most companies, whether big or small, are doing some form of data analysis.
Despite being ranked by CEOs as the most 'strategically important' for digital technology in PwC's 18th Annual Global CEO Survey in 2015, data analytics has not been successfully adopted and embraced by most. Companies generally have huge amounts of data, but it appears that they are either not doing much with the data, or simply have no clear strategy on how to use it.
Data analytics can also be applied in businesses for various benefits. Firstly, businesses can rely on the information derived from data analytics to make smarter, faster and better business decisions. Secondly, insights can be drawn from the historical data, and these insights usually reveal certain information which would have gone unnoticed otherwise. Lastly, depending on the types of data available, predictive analytics can be performed to identify future risks or opportunities.
Some challenges which companies find hard to overcome include:
- Data management/governance — companies do not have the right software applications and IT processes to tap data that is usually stored in separate databases. This is common; as a company grows, the types and amounts of data it generates and handles will grow along with it, and most companies tend to use separate databases for each set or type of data. Companies tend to manage data in silos, usually in their individual departments, and there is a lack of consideration on how the data from one silo can interact with another. For effective data analytics, it is important to have all the data connected, directly or indirectly, in a clear and structured manner.
- Talent and mind-set — data analytics requires employees with the right data skill and mind-sets. A good data analyst must not only have the necessary technical skills, but must also understand the company's business strategy and objectives in order to get the most out of any data analysis. Most companies do not naturally identify these types of soft skills and attributes, and thus do not have the right talent to handle their data.
- Data privacy — without the necessary manpower, companies have the option of engaging external parties to perform the data analysis. However, the data might need to leave the companies' servers, and this increases risk in data security.
The Singapore government is encouraging companies to implement data analytics in their businesses. In the recently launched Infocomm Media (ICM) 2025, the government has outlined objectives that the nation can achieve by 2025 in the area of data analytics. The five strategies which will most likely be implemented over the next 10 years are:
- Establishing an agile, pervasive, and trusted ICM infrastructure
- Building vibrant, strategic and enabled ICM sectors
- Growing and retaining passionate ICM human capital with required skills
- Enabling people and businesses to harness the power of ICM
- Building a R&D ecosystem that supports ICM innovation and commercialisation
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