Innovation: The new and Qrious way of doing things

We've placed significant investment into the platform already so our customers don't have to - Ed Hyde. Photo / NZH

Last year Spark announced it was moving the business beyond the brand overhaul. Digital services were to become the backbone of the organisation, with no move more radical than the establishment of Qrious - the new big data arm of the company.

Qrious aims to take the heavy investment and infrastructure requirements away from big data, creating a platform offering analytics and data science under a SaaS (software as a service) model.

Rather than trying to compete with big, long-established players - the likes of SAP, IBM and Amazon - Qrious' offering is New Zealand-focused, designed for local businesses and to integrate domestic data.

"The combination of data science with New Zealand-specific data sets is unique in the market place. While you can procure some pretty heavy equipment, they don't typically come with much in the way of in-region technical expertise and knowledge, nor do they come pre-packaged with relevant data sets," explains Qrious CEO Ed Hyde.

"Some of the investment in these big data technologies is substantial, so a big part of our offering is making it cost-effective to just get going. We've placed significant investment into the platform already so our customers don't have to."

The Qrious model consists of three main pillars, brought together on a case-by-case basis depending on the customer.

•A high performance data platform which ingests data in a variety of formats, with a host of tools to manipulate the data. The tools can be used in an accessible, business friendly way, or for more technical users using big data tool kits, on a more raw level.

•The second component brings a variety of data sets into the platform. "We've got anonymous network location data coming in from the Spark network, customer segmentation data which is being provided by Roy Morgan through their Helix Personas programme, along with weather and sensor data from around New Zealand," says Hyde.

•The third pillar focuses on analytics, using the Qrious data science team to make the information meaningful, bridging the gap between raw data and business insights - identifying opportunities and areas for improvement - and packaging those up for end-users.

"Using tourism as an example, we package up services which are a combination of those three different factors to provide information around event visitation, tourist numbers in a particular region - where they've come from, what profile of people they are and the recommendations on how to extract the most value," says Hyde.

Qrious is remaining focused on specific sectors, predominantly transport, tourism, retail and local government, while dipping its toe in the water with health and agriculture.

With a tentative date set for September, Qrious will launch a service with completely secure domains so customers' own data science teams can store and use their data. Qrious could engage its own data science team on request for certain projects, but the focus will be on a "hands-off" model to attract a new customer demographic.

Still in its relative infancy, Qrious has targeted businesses at the top end of town while building out its platform - now boasting close to 20 major customers. But with accessibility in mind, creating offerings to smaller players in the market is one item now heading the agenda.