Rip Curl barrels ahead with data transformation delivering insight everywhere

His perfect wave may be a six-footer, peeling off a point break on a crowd-free day in Uluwatu; but Stuart Connell will happily settle for a surf at one of the breaks around Victoria.

Like most Rip Curl personnel Connell loves the surf; as the company’s Lead BI Architect his day job is to make sure staff get as much out of data as they do from a day at the beach.

Over the last couple of years, the surfwear business has been consolidating its data collections to create a single source of truth that’s available to deliver instant insights to executives and retail managers wherever they are located, and ultimately deliver an enhanced customer experience.

In the past managers juggled spreadsheets to find the information they needed, and could struggle to find the consolidated data that they required. By creating a data warehouse and deploying Power BI across the organisation Rip Curl now has enterprise-wide clarity.

Connell worked with Microsoft to use Azure Data factory to handle the ETL (extract, transform, load) processes required to transition from Rip Curl’s previous on premises platforms to Azure which houses the company’s data warehouse.

“We do have some tricky old 32-bit systems that don’t work within the Data Factory platform, but Microsoft always has a solution. So we’ve got a virtual machine that sits inside the architecture where we use some open source Python scripts to connect to some of the more tricky infrastructure and do our ETL that way,” he says.

“That was the best decision we made – 100 percent Microsoft architecture,” says Connell, who also lauds the support he received from the Microsoft Rip Curl account team and Fast Track specialists.

The wisdom of moving to the cloud was thrown into sharp relief during the COVID-19 lockdowns.

The iconic Rip Curl Pro surfing competition at Bells Beach in Victoria was postponed in early 2020,

Now the focus is on growth supported by intelligent analytics. While the company has performed some cube-based analytics, ultimately Rip Curl wants to use Power BI to handle all its data analysis.

And the data collection available for analysis continues to grow. Rip Curl is currently tackling data integration to its point of sale information and to retail store door counters which will give it much more granular insights about who is buying what and when.

“It’s a key part of the business that’s only going to grow over the next five to 10 years,” says Connell who is focussed on accelerating the pace at which information reaches key decision makers to drive greater efficiencies.

Surfing the data wave

As COVID related restrictions eased and stores started opening again store managers have been able to use Power BI to get up to the minute information to help manage shops and inventory.

As the data warehouse links Rip Curl’s eCommerce system and image database, managers can even see an image of the wetsuits or T-shirts that people are buying rather than just bald SKUs and sales figures which can be harder to interpret.

That visual component allows managers to work out where to locate stock, and because wholesale and retail systems are integrated, Power BI can also generate a delivery report so that store staff can see images of what is being delivered in each box and carton.

“That’s great because we have a casual workforce and people have been with the business varying lengths of time. To come into the business, pick up that screen, see what’s expected in the box and check it off, is something that I see a lot of demand for from the business,” says Connell.

Initially around 200 people had access to Power BI but Connell says that Rip Curl has expanded its licence to cover the whole organisation, with data access on a need-to-know basis.

Connell has intentionally leveraged Microsoft Azure out of SE Asia in order to; “Communicate and cross pollinate between our major head office locations in Hossegor, France and Southern California, USA.  We have already completed many projects in other regions – in the one tenancy – and are in the process of rolling the solution out to end users.”

In terms of what data can be analysed Connell says; “We feel confident now that our team can connect to anything and pull in whatever we need for future analysis.”

He says that pilot projects are underway exploring how external data sets could help the business develop broader insights to optimise decision making. “How does weather impact our sales in store? How do other trends globally impact us? Are general retail sales statistics across Australia, important for Rip Curl sales or do surfers completely ignore what’s happening in the retail landscape?”

Beyond that he can see a role for artificial intelligence for inventory automation and machine learning supported decision making to ensure that Rip Curl remains at the top of its game.