Upselling and cross selling and the driving of operational efficiencies. These were the key business imperatives driving the implementation of next generation analytics, according to CIOs and IT leaders at a recent Talktech roundtable organized by Computerworld Hong Kong.
Hosted by Hewlett Packard Enterprise (HPE), 15 IT leaders from industries spanning financial services, insurance healthcare, fashion retailing and also the Government sector shared insights from their organization’s journey with analytics.
Tellingly, around half of these organizations now have a role equivalent to a Chief Data Officer who is responsible for aggregating data and then mining it for insights which can help power the business.
In 2016, organizations are grappling with greater volumes of data than ever before. But before analytics can deliver insights, there is a major data aggregation process to be completed, in which unstructured and structured data needs to be integrated for data scientists to work on it.
Cally Chan, the Hong Kong managing director of HPE, outlined some of the changes in how HPE was using analytics to better understand customer behavior and cross sell and upsell themselves.
“At our online shop, we recorded customers’ caching to understand their behavior,” she said. “With old technology every time we processed a query it took 24 hours, but now we have a new analytical platform the query time is reduced from 24 hours down to 15 seconds, and that is with data size four times larger than before.”
Local R&D effort in analytics
Chan also described HPE’s partnership with the Hong Kong Science and Technology Park (HKSTP). Since December 2013, they have created a venture with a “particular focus on big data technology adaptation” in the city.
Using HPE’s Bamboo platform, the company has completed an analytics program to understand the sentiments of visitors to Hong Kong through their posts on social media.
“We extracted sentiments from social media starting from the first day of Chinese New year for a consecutive of two weeks period,” said Chan.
As Hong Kong looks to boost its tourism industry, sharing this insights on what attracts tourists with the tourism industry players will enable them to identify opportunities of cross sell and upsell—one of the key themes at the roundtable.
From the Hong Kong Government, GCIO Allen Yeung shared the ongoing smart city projects and the role of data, which differed from the commercial imperatives of other commercial organizations.
Data as the foundation of smart city
“To be smart we need to have the source of the information and we need to understand the data, which will help us make our city smarter, like being congestion free,” said Yeung.
“We are mandating government departments to publish data in machine readable formats, but we shouldn’t stop there and we need to think progressively on how we can open up more data.”
“A lot of data also resides with the private sector, like bus and ferry operators. To make a holistic plan for a smart city, we need all the data from everyone and that is an important part of the journey we are going through.”
Digitizing industrial sector
At global conglomerate GE, the company’s IT Director for Global Infrastructure Services Shashank Bindal also talked about that GE’s journey to transform itself from a “big industrial company into a big digital industrial company.”
He used the example of the company’s jet engine division, where GE was taking data from engines “to make better decisions and drive customer outcomes.”
“The business is concerned about the time the engine stays on the wing, and if predictive analysis can keep it stay out of the workshop,” said Bindal.
Analytics also had a contribution to make the operational efficiency of the engines in areas such as fuel consumption.
“If you can get something like 1% of efficiency around fuel cost that is a pretty big deal,” said Bindal. “Every two seconds, an aircraft with GE engineering technologies is taking off somewhere in the world, so if you do the numbers on that 1%, that is quite significant.”
Transparency in insurance and medical sectors
In the insurance industry, the Regional Chief Information Officer in the Asia Pacific for Lockton Companies Suk-Wah Kwok, said that in her organization data was driving a more transparent understanding of how to improve cross sell.
The company this year appointed a Chief Data Officer with global responsibilities, and one of the challenges was to aggregate data across the silos in the business.
“Our customer retention rate is 96%, which is high for the industry, but if we are targeting a growth of 15% a year and making up the 4% customers churn, so that pretty much a 20% increase in revenue, and where do you get that from,” she said. “So we need to identify penetration and cross sell opportunities, for example, whether there is a corporate customer with an insurance area that we haven’t yet tapped into.”
Also from the insurance industry, Ash Shah, AXA Asia’s regional CIO for property and casualty insurance said his company had set up a “data lab” in Singapore which is planning to deliver data to help customers better manage their health.
The company had invested heavily in data and was using APIs to drive the connectivity of disparate systems to “get the data flowing.”
“For example, we know that a customer is 52 years old, slightly overweight and has visited a doctor recently and the blood test result was X,” said Shah. “Using this data we can say that the likelihood that you are going to have a heart attack in the next three years is Y, so we can recommend a visit to a specialist.”
“So we look at using the data for people’s health, and that is where you can also get a better cross sell and upsell,” he added.
Fresenius Medical Care, a leader in dialysis services with more than one thousand clinics across 100 countries, is moving to the second generation of its big data analysis journey. It is combining and standardizing data from three regional divisions: Asia-Pacific, North America and combined Europe, Latin America and Africa.
“In the past we had the data in three silos and we never exchanged and standardized,” said Sylvester Wong, senior director of IT for the Asia Pacific. “So now we are going to have one platform, and we are going to collect the data from many thousands of our machines day and night, so that it can be benchmarked and compared we can use it to become the voice of our industry.”
Analyze for fashion and function
In an industry where success is highly dependent on the performance of the supply chain, luxury goods retailer Kering Asia puts its data to a different use.
Kering owns 20 brands including Gucci and Bottega Veneta, its interim IS Director in Asia Kristian Michael Hertel said there are three main areas the company relies on data analytics for insights: efficiency improvement across the supply chain, customer insights, and thirdly a combination of the first two, where Kering sought to predict future trends.
In the supply chain, the company had moved from a model which updated every 12 days, to full realtime updates across the board.
In terms of the customer, Kerin has information on customer time spend on websites, the time they spend looking at specific products, the time they spent in a store, and the products they purchase.
“All this is combined and analysed so we know the main trends and information,” said Hertel. “And from this we try and predict what will be interesting in the future, and it even gets down to changes in temperature. If one region is not too cold, its not selling well in heavy suits.”
“All this we try and bring into a big analysis model to create a collection which is fitting the world and every market individually, so we have products specifically for China and Japan which you will not find in Paris,” he added.
Original article written and published by Computerworld Hong Kong