Experience on Data Analytics
By Kee Siang Lee, and Chief Information Officer,
The adoption of business analytics has seen a significant acceptance to support business operations and strategic business planning. Yet, many organizations still face the steep learning curve to establish a culture that incorporates data-driven decisions as part of standard operations and decision making.
Key Management Support
Senior management’s unwavering support and recognition of the value of data analytics is critical to ensure a successful adoption across the organization. The direction for the usage of data to strategically plan and support operational improvements hinges on management’s belief and confidence that data can provide valuable insights to improve and enhance the work productivity and benefit the organization. Such insights are essential and need to be transformed into actionable plans with clear deliverables.
"While organizations want to embrace data analytics, it is a common concern and a challenge to determine where this competency should resid"
For effective usage and analysis of data, it is paramount that data is needed to be seen as an organizational asset and not as one that resides solely within individual departments. The mindset of drawing departmental boundaries for own use only and prohibition of data sharing across departments should be removed.
Leadership and Governance
While organizations want to embrace data analytics, it is a common concern and a challenge to determine where this competency should reside. The question of centralization where there is a center of excellence, versus decentralization where the competencies reside in different departments has to be addressed.
Over the time, as business users begin to have a better understanding of what data analytics is about, this capability may gradually move to be overseen by the business users or to the strategic planning department in certain organizations. Regardless, there is a need to identify a single party which has a decent knowledge and an oversight of all the Business Analytics initiatives to promote the sharing of data and co-ordinate the programmes across the organization.
A reliable and scalable technical architecture is essential to ensure that data is being retrieved from the appropriate sources. The architecture would need to address where the data should be coming from, optimizing the retrieval and analysis of the data, as well as specifying the right platforms and tools to use within the organization. Besides data that is gathered internally, there is also a grave need to identify and source data from external sources. This is the part of the intelligence that needs to understand the changing trends and behavior of its customers in consuming similar services offered by other organizations.
Operationalizing Data Analytics
To develop a data-driven culture and working environment, there is a need to embed data analytics into work processes. For instance, as a part of work planning exercise, a trend analysis activity using data analytics can be incorporated to allow the senior management to study the performance and industry trends so as to identify gaps in services and potential new services. A critical aspect of this exercise is to translate the findings into actionable projects which then need to be monitored and followed through.
Data analytics should be used consistently as a tool for discussion on business operational performances. Discussions centering on data, and how they can be interpreted in different ways to reveal operational performances would be helpful to inculcate a data-driven culture and a brilliant working environment. This would then gradually build up the organization’s confidence and capabilities in the use of data analytics to further drive business efficiency.
Benefits from using data analytics is maximized when it is aligned to the organization’s business purposes, culture and environment. Generating insights through the use of data analytics should be accompanied with actionable plans and deliverables. Bold data-driven decisions are required to use such insights to innovate and transform an organization.