In my previous blog post, I explored the transition from action intelligence in Special Forces to work intelligence on the shop floor at car dealerships.

With this second installment, I continue the journey we’re making together in an increasingly digital world where AI technology is playing an increasingly prominent role.

The automotive sector is evolving rapidly. Customers now demand seamless, digitally driven experiences, while retailers and OEMs are under increasing pressure to increase efficiency, reduce costs, and remain profitable. Addressing these challenges requires a new way of thinking – and artificial intelligence is proving to be the game changer.

Work intelligence isn’t so much digital transformation as digital harmonization. Instead of replacing or removing people, it’s about strengthening and continuously improving by applying both human and artificial intelligence in the right proportions. This is becoming an essential characteristic of a healthy car dealership.
Every dealership must make well-considered decisions to ensure effective and efficient operations. Not just today, but also tomorrow. Ideally, these decisions are supported by accurate and readily available data within the organization. However, this is often not the case. Instead, decisions are made based on the experience and insight of the decision-maker. This is purely due to the complexity and sheer volume of available data sources, making it nearly impossible to understand what’s happening at the process level, in communication, or in people’s minds. How often do you hear, “That’s what I’ve been told,” and yet no further thought is given to improving things? It is primarily up to management leadership to create a culture of doing better today than yesterday. With increasing, continuous pressure on people to do more work with the same number of people, or the same work with fewer people because those cars have to be delivered, simply automating less efficient work processes isn’t the solution to better results, at best it’s faster.

To improve processes, you need to consider how they contribute to the organization’s objectives. This means looking beyond departmental boundaries to understand how processes interact.

Generally speaking, the notion that everything must be automated until it reaches “hyperautomation” must be reversed. There is no doubt that automation plays a role in managing simple, repeatable tasks at scale. However, where processes require context to function correctly and desired paths yield thousands of process variants, work intelligence suggests that end-to-end automation is neither suitable nor desirable. Transformation as a goal should be replaced by harmonization.

Artificial intelligence must be approached with caution. Not so much in terms of whether it should be deployed, but rather how customers can manage it transparently and reliably. Where it is used, it should always “show its workings” when presenting results and, where possible, be adaptable by users, not just data scientists.

With Orioniq, we’ve built our first module with AI-supported technology that does exactly what I just described. The solution automatically recognizes the most commonly used document types, using the document data to automatically populate fields and directly assign the documents to the correct sales file. You can find the result directly in DocBase, and where the automatic recognition finds something missing or missing, an authorized user can add the missing data or verify the documents and forward them to the correct files. New document types can be deployed by users to train Orioniq for automatic recognition, so that these types can be added to sales files without human intervention in the future.

Bringing humans into the loop with AI for repetitive work delivers better, faster results, allowing people to focus on more enjoyable and meaningful activities.

Want to know how Digital Sales Records can work for your company or sales department?

Contact Rob