Laneway Rebrand – new look & new focus on Superannuation

Laneway Analytics launches new Brand

14 March 2018 | CONFERENCE of MAJOR SUPER FUNDS (AIST), BRISBANE, Australia

“Today, we are launching our new Laneway Analytics brand at the peak industry conference for Australian Super Funds, the Conference of Major Super Funds“, said Laneway CEO, Grant Callaghan, “and we are announcing our focus on the superannuation sector. Super Funds recognise the significant value their large sets of data contain. They want to leverage this data to better engage and assist their members and employers. The key challenge is: how to take on this complex data and analytics journey?”

Laneway Analytics moniker comes from its Melbourne-based laneway headquarters – right in the heart of start-up land and Australia’s traditional superannuation centre. It partners with the world’s most innovative business intelligence vendors and its customers are some of Australia’s leading Super Funds, including Australian Super and HESTA, amongst others.

Laneway Analytics has unveiled its new data and analytics platform designed to help Super Funds better connect with members and employers; Provident Lane – a powerful specialised analytics solution for Super Funds.

“We have created Provident Lane as the analytics solution to help Funds rapidly deliver value from their large, complex data sets. Our partnerships with leading Funds, and our unique analytics platform and client portal set us apart, and enable us to deliver value quickly” continued Callaghan.

Funds have historically outsourced many of their core systems to Administrators. However, Callaghan is seeing a dramatic change across the industry as Funds are bringing more business processes and key capabilities in-house.

“Internal teams are growing, as is the number of systems. This results in an explosion of data. Funds need strategic partners like Laneway Analytics to help them bring their diverse sets of data together and enable operators, analysts, and managers to self-sufficiently access this data, take meaning from it, and actually use data to help these skilled operators better perform their jobs” he concluded.