Organisations are realising significant business value through data analytics. A recent Forbes Insights and EY report ‘Data & Advanced Analytics: High Stakes, High Rewards’ puts the Asia Pacific (APAC) region top of the global table in advanced analytics maturity.
However, only 4% of organisations polled in Singapore had achieved a well-established company-wide analytics strategy, which is linked to the central business strategy. Research suggests that despite a fierce commitment to being data-driven, there are significant hurdles and specific challenges to overcome. Singapore’s talent gap has been discussed at length and we have seen curricula in schools and universities shift to support the Smart Nation. Interested in further challenges, we consulted three data leaders on their top tips and key strategies they have deployed:
Positioning data and analytics at an enterprise level
Perspective by: Shameek Kundu, Chief Data Officer, Standard Chartered Bank
Every Chief Data Officer must answer this for their own industry and company context. For regulated industries such as banking, the positioning typically starts at the “defensive” end: protecting the bank through assurance on the quality of data that underpins critical risk and regulatory processes. In a banking context, this can impact a wide range of processes including compliance, risk measurement and reporting, financial reporting and regulatory submissions.
However, the Chief Data Officer’s proposition needs to quickly move on to more explicit business value – e.g., the ability to use data to make better business decisions, improve the quality of the customer experience, become sharper with the proposition for individual customers. Without this shift, it is difficult to sustain the investment and interest in large scale data programmes over time. Ultimately, the data/ analytics proposition should become an integral – and very important – part of the company’s overall digital agenda.
Fostering collaboration between IT, data & analytics, & business teams
Perspective by: Dr Michael Fung, Chief Data Officer, SkillsFuture Singapore (SSG)
Being able to ‘translate the language’ across different levels to achieve alignment across IT, data team, business teams, and management is vital to maximising the strategic value of data. Some of the major considerations at the different levels are:
Management level – the use of data to drive the organisational business strategies and outcomes;
Business team level – the unit’s business performance and cost-effectiveness;
Data team – the availability and access to reliable data;
IT team – the system and implementation considerations.
Organisations that are able to bridge across these very different teams and agendas will be able to reap the full benefits from its strategic data assets.
Identifying new business opportunities in data and analytics
Perspective by: Mohit Das, Vice President, Global Marketing Analytics and Effectiveness, Kellogg Company
Most savvy leaders have a vague sense for the ‘opportunity spaces’ that exist on their business. Key for data analytics organisations is to stay close to these business leaders and identify their pain points and solve for that. The pain points are mostly in 2 areas:
a) How big is the size of prize of this opportunity in the short term/ long term b) How do I prioritize and invest in the top opportunities that give me the best bang for the buck
Data analysis should focus on these internal pain points by:
1) Simplifying, structuring and visualising these opportunities for better understanding 2) Quantifying the size of prize for each and create some future looking scenarios 3) Provide a framework for comparing opportunity spaces for better prioritisation
Also, Data analytics organisations should always strive for creating ‘Eureka moments’ for business leadership. These are insights & business opportunities that business leaders have never thought about and robust analytic tools are able to sniff out to challenge existing paradigms. These new insights then need to be massaged with cross functional partnership and feedback so that a business case can be created for investing behind these opportunities.
These are key strategies to overcome obstacles to the use of data as a strategic asset. We are interested in your views on these key challenges and in particular, data monetisation – how to extract real value. Get in touch if you would like to share your perspective.