Smart data and the rise of super-adaptive enterprises

Hidden amid every data set is knowledge that can generate disruptive competitive advantage and improve business responsiveness. Decoding this secret requires rigorous analytics and Google and IDA’s Squared Data & Analytics Programme. 

We are living in the age of the zettabyte.

According to IDC, 1.8 ZB of data was created in 2011. That is 18 with twenty zeros behind it. Since then, the world has been doubling its data every 18 months. At that rate, we will generate a staggering 40 ZB by 2020. On the commercial side, Gartner predicts that enterprise data too will be growing by more than six times in the next five years .

Whichever way you look at it, there is a lot of data produced globally.  Buried within it is intelligence that can save cost, improve productivity and ultimately, make organisations more adaptive and resilient to change. The big question for businesses is: how do you uncover these benefits from data?

From big data to smart data

Catherine Khaw, Chief of Intelligent Systems Practice in NUS-ISS, thinks that part of the answer lies in creating smart data and developing a comprehensive information strategy.

Data are useful only if they can be used to support enterprise decisions and solve business problems. But in reality, a lot of the data are not fully utilised in the organisation; with large data sets, there are lots of noise and concerns over the quality of data. Sifting through the data to extract valuable information has remained a major challenge for many organisations who have to consider other data management issues like data formats and data quality. There is also an infinite number of ways in which the data can be combined, compared and analysed to extract useful patterns and business insights.

“Data collection and interpretation should never be a random exercise.” said Catherine. “It should be guided by a clear information strategy that is designed to deliver reliable and actionable inputs to decision making.”

To ensure reliable and quality output, an analyst must have sound understanding of the business environment and its processes, coupled with strong training in analytical thinking and approach to sample, hypothesise and validate the outcome.

Smart data is the resulting set of data that will address a specific business context, for instance, what a customer is doing before and after a transaction or who has influenced the customer intelligence for better customer service. What are the useful data that will keep company delivering better customer service and greater return per customer? Catherine believes rendering smart data into predictive analytics can be an effective way for enterprises to capture and retain tacit knowledge and critical intellectual assets.

“At the present stage, we are not short of data but talents who can make sense of the data,” said Catherine. “It’s the intelligence and knowledge from the data that will allow enterprises to drive business in the right direction and create a truly data driven organisation.”

Chef de Data Analytics

That’s where a programme like Squared Data & Analytics comes in. To spur the local analytics industry, the Infocomm Development Authority of Singapore and Google launched the programme in 2014 to train fresh university graduates in data and analytics and to apply their knowledge in media agencies, creative agencies and companies in Travel, Finance and e-commerce sectors.

Now into its second year, Catherine and her analytics team at NUS-ISS have been selected as one of two training providers in addition to Google to provide advanced analytics training for the participants.

Ruth Beattie, Google’s Head of Squared Programs and Industry Partnerships was pleased with the collaboration, citing NUS-ISS’ deep subject matter expertise, excellent lecturers with strong industry experience and its practical and theoretical learning approach among the benefits.


Catherine (1st row, most right in photo on left), with Ruth (1st row, most left) with the Squared Data & Analytics programme participants

Within their 6 week training period, Squared trainees completed 2 short module courses at ISS on predictive and text analytics with a mix of exercises, real-world business applications and case studies bolstering the learning. This training period at Google and ISS gave the trainees a strong platform ahead of the 6 month job placements.

“The first cohort of 20 graduates from the Squared Data & Analytics program are employed n full-time roles as Data Analysts. They are all making significant contributions; from building out a team of analysts to consulting with key clients to define and tackle business issues, to partnering with business leaders to shape new strategies. The current group of 25 trainees are now completing their work placements, returning to Google each month for more training. I am excited to see the contributions they are already making to their host companies.” Ruth said.

For Catherine, she likened her task in developing the league of professional data analysts to that of grooming a brigade of chefs, “A good data analyst is like a chef who is skilled in both culinary art and gastronomic science. To create an original dish, the chef must possess a palate that understands flavours intricately, the techniques to create the dish and the morals to serve only good quality and safe food. It’s the same in analytics where the dish would be the predictive model, the spice and ingredients, the data, and the kitchen appliances, the software and analytical tools.”

Like any great chef worth his salt, analysts will have to rely on their skills to create new recipes through meticulous research and repeatable experimentation. There is no cookbook approach as each organisation, issue, context and dataset will be different. To get the analytics Michelin stars, hard work and consistency is key.

Data-driven economy and responsive enterprises

The potential upside of analytics can be huge. According to a report by consulting firm Analysys Mason, data-driven innovation has already contributed more than S$4 billion to Singapore’s economy and this figure is expected to exceed S$11 billion in the next four years.

Several enterprises are already fast catching on to smart data analytics and using it to improve performance across the value chain and to gain actionable insights.

“It’s going to be Moneyball at every conceivable level once the analytics industry takes off,” Catherine predicted, referring to the Hollywood movie where an undervalued baseball team, assembled based on complex sabermetric, went on to win a record 20 consecutive games and make American League legend.

In North America for instance, a survey by digital marketing firm QuinStreet with 540 IT decision-makers showed that data analytics was now a top priority for eight in 10 mid-size and large companies. The respondents had reported faster, more accurate and timely decision-making and citied other benefits that included greater transparency and usable information and scalability. Most analytics projects to date were centred on enhancing efficiency, reducing complexity and improving customer loyalty .

The lesson? Try analytics early if you want an unfair advantage over your competition.

About Catherine Khaw. A Senior Member of the Business Analytics Practice at NUS-ISS with 20-over years of market intelligence and business analytics experience in IBM, Cisco Systems and marketing research firms, Catherine has established data research services, developed business intelligence blueprints and applied data for decision-making and strategy formulation. Catherine is at catherinekhaw@nus.edu.sg if you would like to find out more about the potential of data analytics or how to get started on the analytics journey.

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