Data exhaust? No, not exhaustion from data. Simply put, data exhaust is the data that a business collects that it doesn’t currently think it can put to use. The biggest producers of data exhaust are manufacturers and sometimes retailers. Especially manufacturers of appliances, vehicles and equipment and large chain retailers. Most software or SaaS companies use almost all the data they collect as they are more likely to be keenly aware of their data and how to find value from it. For the purpose of this quick overview, I’ll focus on manufacturers.
Data Exhaust from Manufacturers
Take for example, vehicle manufacturers. They receive vast amounts of data on any given day. From dealers on warranty issues, crash and fault data, dealer maintenance information and so on. Much of that data they will use to inform changes in the next model from the UX through to engine parts.
But some of the data they get isn’t of much relevance to them, but it may be to their suppliers or someone else. There is always excess data that doesn’t get used by the manufacturer themselves. But a lot of the data collected is relevant through the supply chain. Data that can help with quality control or product performance. To Honda, Ford or Audi this may be “data exhaust” – data they don’t use or need, but the supply chain (OEM’s) can.
Data Exhaust is a Revenue Opportunity
So an auto manufacturer such as Honda, Ford or Audi, could then sell the data down the supply chain. Not just to one supplier but to multiple suppliers. In a highly competitive industry such as automotive manufacturing, it is in the interest of manufacturing leads to promote the use of Big Data through the supply chain for product improvements, quality assurance, cost efficiencies and innovation.
This model can have significant economic benefits to the manufacturer and supply chain. Even the supply chain can in turn sell the data to their supply chain or others who may be interested. This creates a whole new value chain. So exhaust data can be invaluable to others and help defray your data centre costs.