Published on the 29/03/2023 | Written by Heather Wright

It’s a marathon that brings teams together…  

Data analytics isn’t a sprint you can win overnight, it’s a marathon which needs to be run at optimal pace, continuously – and it’s definitely not an individual sport.

That’s the message from Varun Verma, L’Oreal Australia and New Zealand chief data analytics officer, who says successful data and analytics, and pervasive decision intelligence, requires involvement well beyond the data analytics team.  

“Democratisation of data is only one side of it, allowing one unit of the company to share the data. But it is also important that the other side of the company starts consuming it for the purpose of their decision making,” Verma says.

“Data democratisation has to be done with the mindset of understanding the right business objectives.”  

“Technology and business objectives both need to come together to build the right level of data democratisation.  

“It can’t be by looking at just one side of the coin. Instead, it has to be with the mindset of understanding the right business objectives, then enabling the right technologies. That’s the core foundation,” Verma, who is speaking at the 2023 New Zealand Data & Analytics Summit in May, says.  

“You don’t want to just give users a dump of data. You don’t want to give them the crude information that they don’t know what to do with. You want to give them a curated path, and therefore the business context also comes into the picture – understanding the needs and finding out what is relevant, doing a discovery from the genesis of the decision making and what decisions the different profiles and personas would like.”  

At L’Oreal Australia and New Zealand, the data and analytics strategy is focused around the two pillars of data usage and bringing curiosity to the business to lift the data culture.  

This falls into two categories – ‘descriptive insights’: providing real-time dashboards, perhaps some ad-hoc dashboards, and business intelligence products; and ‘advanced analytics’: covering the likes of demand forecasting and revenue growth optimisation. 

One example is L’Oreal’s advanced analytics solution being used to ensure the company’s media mix – where it’s putting its advertising spend – is correct, identifying different factors in its sales performance by combining both L’Oreal’s own data with data from outside markets to optimise media planning and investment for different channels.  

But equally important is data literacy and curiosity. L’Oreal runs masterclasses within the company to provide tailored training and the knowledge required at different levels.  

“We also basically create a data ecosystem, or repository, so people are able for find what they need in a data reference library.   

“We should have a data ecosystem where there are very well-defined data owners and we then have sessions around awareness and what we practice where we disseminate this information with everyone in the company.”  

The third piece of L’Oreal’s data work is the technology. The company is using Google Cloud and leveraging it to democratise and disseminate data, with data privacy and role-based security on top.   

“That’s more around creating assets on top of the technology to ensure that what we want to do to create awareness we can do on the platform in the right way.”  

But while L’Oreal is embracing data and analytics, Verma, who took on the role just four months ago, admits there are challenges, including the age-old chestnut of data silos, which is requiring some creativity to execute on analytics plans.  

“We want to prepare a good solution, to have data which is at the fingertips of data scientists so they can actually deliver their solution smoothly and also do it fast.  

“This has been a challenge for us because the data silos are one thing we need to solve through technology. Our data is fragmented and sits in different buckets, so in order to do analysis like the media mix model, which requires collection of different data sources, it takes a bit of time to bring all the data together, blend it and finally put something on top of it. It requires huge effort.”  

Verma says globally, L’Oreal has acknowledged those challenges and is on the journey to a global – rather than market- or country-specific – solution. 

The three-tiered solution will see the creation of a data lake, with a second layer where data gets cleansed and standardised, and the third layer focused on consumption, enabling data to be used by people based on their profile, requirements and the type of analysis they want to do.   

“But it is all a journey and we need to wait for that journey to complete in order to get rid of our first problem [data silos].”  

There are also challenges on the adoption side, with change management. Verma admits that changing long-established mindsets can prove challenging, but he says the growing body of success stories within the company is helping bring a stronger data culture into the organisation. 

“Data agility and data curiosity within any organisation requires leadership support and change management.  

“We have companies which have been doing tasks and specific projects on gut- feel and less on data, and they need to find out how to achieve better decision making through data,” he says.  

There’s a third part to the data and analytics equation too: Talent.  

Verma says data analytics teams need to have a mix of people who understand business, those who understand technology, those who understand the science of decision making and people who know the meaning of measurements or constructs.  

“They all need to come together to do this in a project for a company because if you don’t have the right talent, the data dissemination and distribution will become a challenge and it will be too difficult because when you do not know what you want to disseminate. Just sharing what you have in hand doesn’t solve the problem.   

“You need to do it fit for purpose for your organisation and that requires various capabilities to come together and do it in the right way,” he says.  

Data and analytics really is a team sport.  

The 2023 New Zealand Data & Analytics Summit takes place in Auckland on May 30. Find out more, and book, here.