As more people get comfortable buying big ticket Items like cars on the internet, Volkswagen Financial Services South Africa (VWFS SA) knew it needed to simplify the entire process. CIO Wilma Crosson was in charge of making this happen.

Improving its direct sales channel demanded that they come up with a way to, first of all, cut the time it takes for customers to complete the sales process. And, in doing so, VWFS SA made it easier for customers to buy a new car without ever having to set foot inside a dealership. 

Someone looking to buy a car can either go into a dealership and talk to a finance and insurance manager who helps them though the process, from drawing up sales contracts, to arranging payment for the car and offering them additional products. That’s one process. The other more direct route now is a customer visiting the website and doing everything there. Looking at the entire customer journey—from customer awareness to payment and delivery—was just one step in the chain Crosson wanted to improve. Discussing what drove the move, she outlines that the pandemic forced most companies to look at their digital capabilities. “We knew we needed to transform digitally to stay competitive,” she says. “We wanted to improve our online applications process because we weren’t getting a lot of traffic from this channel. When we looked at it more closely, we realized our online journey wasn’t very efficient, requiring customers to spend about 30 minutes filling out paperwork.”  

Finding the right solution

VWFS SA is owned by two shareholders Volkswagen Financial Services AG (Germany) and The First Rand Group. When it started talking about improving the online application process, it was lucky it could use software developed by one of these shareholders to make the application process a lot shorter. The solution uses APIs and AI to run an affordability background check so it can quickly verify if the customer qualifies for the deal. This meant VWFS SA could reduce the number of fields customers had to complete from 250 to just 10. “We were quite lucky we could just tailor this solution to meet our specific needs,” she says.  

To do so, the brand partnered with an external service provider. “I think it’s always quite daunting trying to choose the right service provider because you have to think about how the company aligns with your organization’s culture and with your future needs. So we had to come up with quite strict criteria,” she says, and according to Crosson, companies from different types of industries, different sizes, and with different levels of experience were in the running for the project. The final decision came down to what they needed now, as well as what would be needed in the future.

The business case for outsourcing

“Because of how our company is structured, I’ve outsourced most of my business-as-usual activities to an IT service provider so I don’t have in-house developers or a huge complement of IT staff that can execute for me,” says Crosson. “But we do need to have some skills in-house that our chosen IT service provider, SovTech, then supports.” Obviously, this comes with some challenges. Being a company that outsources a lot, VWFS SA had to get very good at ensuring their SLAs were well structured and well managed. “I use the term ‘managed’ because if you don’t meet with your service providers quarterly, or in the case of certain projects, monthly, and if you don’t have the necessary KPI-driven conversations, you’re kind of dead in the water,” she says, adding this is especially important when you work with multiple providers because they also need to work together.  

While she does admit this is where most of her challenges came from, she cites an agile approach to project management as being critical to the project’s success. “I promise you, having weekly meetings, where we were all are together and could discuss progress helped a lot,” she says.

The devil is in the data

When looking back on how the project went, she admits they had a lot of data-related challenges, because it all sits with their IT service provider. “If I, as the CIO, want to enable key business objectives, like streamlining our online journey, I need to be able to run a marketing campaign, for example,” she says. “But to do this, I need to know who my customers are and which ones have actually opted in to receive marketing content. So I need that data.”

But when the data sits in an external environment, this is a big challenge because someone needs to go through a third party to access it. Plus, Crosson says that when you outsource to a third party, you run on their migration timelines and you have to fit in their schedule. If these timelines interfere or conflict with a request you make, it can delay progress, which is exactly what VWFS SA experienced and it delayed their project by about three weeks. “The lesson learned for us was we need to be more aware of our service provider’s technical roadmaps so we can plan accordingly and, where possible, work around them,” she says.

Looking at some of the learnings from this project specifically, she adds that sometimes the answers to problems are right in front of you. “Our customers are digital, our competitors are digital, our employees are digital, so it made good business sense for us to be more digital too,” she says.

Automotive Industry, CIO, Digital Transformation, IT Leadership

What is the future of analytics and AI? And how can organizations thrive in an era of disruption? We asked Bryan Harris, Executive Vice President and Chief Technology Officer of analytics software company SAS, for his perspective.

Q: What is your advice to technology leaders for improving organizational resiliency?

A: Right now, we are all in a race against disruption and data. Customer buying habits have changed. Work-life balance has changed. The financial climate has changed. So, how do you establish a data-driven culture to identify and adapt to change? Or, in other words, what is the learning rate of your organization?

This is why executing a persistent data and analytics strategy is so important. It allows you to create a baseline of the past, identify when change happens, adapt your strategy, and make new, informed decisions. This process is your organization’s learning rate and competitive advantage.

Q: How can AI and analytics help business and technology leaders anticipate and adapt to disruption?

A: We are creating data that is outpacing human capacity. So the question becomes: how do you scale human observation and decision-making? AI is becoming the sensors for data in the world we’re in right now. So, we need analytics, machine learning and artificial intelligence (AI) to help scale decision-making for organizations.

Q: What best practices do you recommend around developing and deploying AI?

A: When we talk to customers, we first show them that the resiliency and agility of the cloud allows them to adapt quickly to the changing data environment.

The second step is lowering the barrier of entry for their workforce to become literate in analytics, modeling and decision-making through AI, so they can scale their decision-making. Everyone has a different maturity spot in that curve, but those who achieve this outcome will thrive – even in the face of disruption.

I recommend the following best practices:

Think about the ModelOps life cycle, or the analytics life cycle, as a strategic capability in your organization. If you can observe the world faster, and make and deploy insights and decisions as part of AI workloads faster, you can see the future ahead of time. This means you have a competitive advantage in the market.Innovate responsibly and be aware of bias. We give capabilities and best practices to our customers that allow them to understand the responsibility they have when scaling their business with AI. And we are taking a practical approach to helping customers adhere to the ethical AI legislative policies that are emerging.Ensure explainability and transparency in models. You won’t have adoption of AI unless there is trust in AI. To have trust in AI, you must have transparency. Transparency is critical to the process.

Q: What does the future hold for AI and analytics?

A: Synthetic data is a big conversation for us right now. One of the challenges with AI is getting data labeled. Right now, someone must label, for example, a picture of a car, a house or a dog to train a computer vision model. And then, you must validate the performance of the model against unlabeled data.

Synthetic data, in contrast, allows us to build synthetic data that is statistically congruent to real data. This advancement represents a huge opportunity to help us create more robust models — models that aren’t even possible today because conventional data labeling is too challenging and expensive. SAS lowers the cost of data acquisition and accelerates the time to a model.

If, because of this innovation, they get insights about the future, companies gain a competitive advantage. But they must do it responsibly, with awareness of the bias that AI may inadvertently introduce. That is why we provide capabilities and best practices to our customers that allow them to understand the responsibility they have when scaling their business with AI.

For more information, download the SAS report – “4 Winning Strategies for Digital Transformation” – here.

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