Within this super connected realm of free-flowing data, automation is one of the core focus areas of machine learning and artificial intelligence (AI) being developed by car manufacturers. Autonomous transport trucks will begin to come online by 2023 or 2024. This sets the stage for automation of personal transportation vehicles, which is not far behind. But with wide-ranging manufacturing, regulatory, and consumer changes required before automation can be adopted, these changes will likely not occur as a big bang but more as an evolution. Original Equipment Manufacturers (OEMs) and suppliers will have opportunities to create new experiences, platforms, and revenue streams to meet changing customer expectations.
In the immediate future, new passenger experiences will enable OEMs to differentiate themselves in partnership with telecom and media providers. The car may become a new entertainment device – children in the backseat will be able to start watching a movie at home and then switch to watching it in the car. Electric vehicle (EV) drivers waiting for a recharge will want to use their vehicle for work-related activities such as video conferencing. Cameras within the vehicle, combined with AI algorithms running in the mobile edge, will be able to detect distracted drivers and enable safety measures. Natural language processing capabilities will further reduce the swiping and typing needed to interact with onboard systems. Advances in flexible microchip printing and the use of 5G signals to deliver power mean that onboard sensors can provide exponentially more data in real time. Cameras will be able to report traffic, road, and weather conditions to the cloud, with more data points than Apple or Google have today. Performance data from just about every critical component could be measures, allowing for proactive service. Over-the-air (OTA) system updates could be pushed daily, if needed.
The Transformative Power of 5G
From a data and experience perspective, taking a hard look at ways of working along with organizing teams around data (i.e., the customer) is something Publicis Sapient helps customers with every day across all industry verticals. A data strategy that plots out a road map of use cases to execute against is crucial. It’s not just about standing up a customer data platform, it’s about how to execute relevant use cases in a timely manner. This allows you to create road maps to develop market-leading services that align to customer needs. It’s important to first make sense of how to use your data as an asset and to understand how your company culture considers return on investment (ROI).
From OEM to Mobility Company
This is the moment for OEMs to organize themselves to become data-driven tech-based mobility companies. Not only is this inevitable, it’s also crucial for taking advantage of the 37-billion-dollar automotive software industry over the next four years. Autonomy and faster network connections will enable software as a service to be at the forefront of the OEM business model. CMOs, CDOs, and CIOs are focused on determining what software to develop to service future customer needs as experience becomes the brand, moving away from incentives and vehicle capability as market differentiators.
How the customer experiences the product and how that experience enables them to feel fulfilled will take mainstage. Other industries have been in a transformation state for some time. If they are to stay ahead of the disruption seen over the two years, OEMs must put customer data at the core, find new ways of working across channels in a tier-less fashion, and establish an organizational structure that breaks down silos.
How Auto Industry Players Can Become Tech Orgs
As many OEMs look to create tech companies within their walls, they are doing so in a couple of different ways: joint venture start-ups and acquisitions.
In a joint venture scenario, the OEM and usually a mobility-focused tech partner come together to focus on common value-based outcomes. Both parties have a financial interest in the company and a share in the profits. In some cases, after the business model is established, the new org is evaluated and purchased back from the OEM, allowing them to operate in this new model. The benefit here is the OEM can break down silos by essentially starting a new way of working, leaving silo-driven objectives behind. They can quickly align teams to goals, leveraging tested agile tech company models coupled with OEM subject matter experts (SMEs). Both parties contribute respective SMEs to ensure the newly formed ways of working has context as they move at speed and scale to achieve value-based outcomes. The option is attractive because it enables the OEM to transform without the enormous effort it takes to change the current org. Gradually, once the new business model is established, the OEM can recast people into the newly formed org, achieving the desired outcome. The tech company provides modern ways of working, access to a large pool of engineering experts, and consulting and customer experience experts, organically transforming how the OEM works toward a desired future state.
In the acquisition model, companies are clear on what their vision is and have likely hired top talent from successful tech leaders to establish a baseline to start from. They then acquire a smaller tech firm that aligns to their goals. Both strategies can achieve the same outcomes; it really depends on the level of risk your organization wants to take on and the timeline you choose to help you achieve results. Joint ventures (JVs) are a model that our experience has told us gets you there faster. At the end of the day, think creatively, break status quo, experiment, learn from failures, be hands on, collaborate, and spread the knowledge.
As the customer experience becomes more competitive, making sense of how to enable data as an asset and build a company culture that is ROI-focused will allow the organization to stay in lockstep with customer needs.
Here are a few fundamentals to consider when thinking about getting your data strategy in place.
- Data-driven culture starts at the (very) top: Senior leadership practice fact-based decision-making.
- Choose metrics with care – and cunning: Create detailed metrics to make complete, informed, predictions.
- Don’t pigeonhole your data scientists: Bring data science closer to the business to organically impact the culture.
- Quantify uncertainty: Requiring teams to be explicit and quantitative pushes them to define uncertainty, attain a deeper understanding of their model, and run experiments.
- Fix basic data-access issues quickly by breaking the logjam: Grant universal access to just a few key measures at a time.
- Use analytics to help employees, not just customers: Allow access to data that helps employees see how they can be more efficient.
- Get in the habit of explaining analytical choices: Ask teams how they approached a problem and what alternatives they considered.
- Specialized training should be offered just in time: Offer training just before a project is kicking off as opposed to generally.
- Proofs of concept should be simple and robust: Ask teams to look at building POCs based on what they have to work with first before evolving.
- Privacy and security should be woven in from the start: Greater connectivity and more data mean more opportunities but also mean greater concerns about bad actors and unintended consequences.
Get Ready To Start Now
At the end of the day, OEMs must get their start-up business mentality ready to tap into the massive revenue experience 5G will help to unlock. It takes time to put these plans in motion, so starting now is crucial. As experiences become the brand and the marketing tool of the future, those who develop an org structure and ways of working that enable a data-led, test- and learn-centered culture focused on value-based outcomes at speed will be the ones that come out of the gate ahead of the competition. The reassuring thing is that OEMs can learn from the financial services and retail industries that have been experiencing disruption and have been putting transformation strategies into place for the past decade. Step one is looking at the org’s maturity and reflecting honestly upon where it is today. Being able to move past “well this is the way we do this” is a must for achieving desired results. Identifying a clear vision and value drivers that your people will organize around with the support of the top of the house is critical to ensure all stakeholders are moving in the same direction at speed. Then select a tech strategy and road map that works best for the nuances that exist within the company ecosystem. A year from now the industry will be talking 6G, so time to get started.
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North AmericaNelson PereiraGroup Vice President and Managing Partner, Publicis Sapient