In 2021, oil will no longer be the most important resource, but data. But what does this new data mean for humanity?
For example, an aircraft with all kinds of imaging equipment that flies at a relatively low altitude and collects terabytes of data every day from visual images, images at millimeter and infrared wavelengths, radars that penetrate clouds, and so on.
With this data, they can begin to more accurately predict this year’s corn crop, or the FEMA can use this data to decide the order in which to evacuate civilians in the event of natural disasters.
Harvard Medical School published a study comparing the accuracy of machine learning systems with that of human pathologists in detecting breast cancer. The machine learning was 92% accurate, which is good. But people were 96% accurate. Case closed, right?
Harvard then combined the pathologists’ discoveries with the scans of the machine learning systems. Accuracy increased to 99.5%. That reduces errors by nearly an order of magnitude (from 40 per thousand to just 5 per thousand) and amounts to 56,000 fewer misread breast scans per year in the US alone.
Autonomous Vehicles (AVs) are coming. The benefits are well known: safer roads, a boost to the economy and less crowds during rush hour. But perhaps the biggest benefit is the reduction of greenhouse gases from cars. Research by professors from the University of Poznan estimates that autonomous vehicles could ultimately reduce greenhouse gas emissions by 40 to 60%. According to the Environmental Protection Agency, current transportation is responsible for 29% of the United States’ greenhouse gases, so this would be a significant advance.
How do we get into the AV future? You guessed it: data. In this case, it would take hundreds of petabytes of data to form the data lake from which the advanced machine learning solutions for self-driving traffic will emerge. And it doesn’t stop there. Each of these modern “computing platforms that happen to be mobile” will generate terabytes of data per week per vehicle. Even assuming a 75% reduction in the number of vehicles on the road, that’s many exabytes of data per year.
This is all data that you keep. It’s the new oil. If a vehicle accident occurs, you can query the images captured by the vehicles involved to decide what caused the accident and which AV algorithms need to be improved.
Sales and marketing data is also used to make life easier for employees. The sales and marketing team gains a better understanding of customer needs. This allows them to respond better to individual needs and requirements. This obviously results in more deals, which translates into more profit for the company. More targeted marketing campaigns can be set up with data acquired by the sales team. These targeted marketing campaigns generate better brand awareness in the right segments relevant to your business, more leads come in because the actions can be more specifically targeted to the right people or stakeholders with your product, … and so on.
How can this valuable data ultimately be acquired? SALES. The sales team has direct contact with leads or customers. They are, as it were, collectors of data in the field, and can collect the most interesting information for the company by asking the right questions and good relationships with customers. This is very important, but from experience it is known that a lot of data is lost here due to lack of easy input. Before, during and after the conversation, more specific tasks can also be performed by the seller to achieve this data extraction. However, there is a tool for this: SalesNote. This will support the salesperson before helping the (sales) conversation with important preparations, guiding the salesperson during the conversation and raising important questions that are crucial for acquiring crucial information about the needs of the customers. In addition, SalesNote will also support the seller with next-best actions to properly follow up the lead or customer.