Salesforce Announces Einstein AI and Analytics for Field Service Lightning
Salesforce today launched Einstein AI and Analytics for Field Service Lightning, a release that uses the company's artificial intelligence and analytical tools to empower mobile workers with new intelligence and insights.
The offering has three key features. First is Einstein Vision for Field Service, which uses artificial intelligence for image recognition. Companies can use pretrained image classifiers as well as train their own custom classifiers to accommodate a range of specialized use cases. The second is Field Service Equipment and Inventory Management, which uses scheduling automation to ensure that the correct work crews, equipment, and trucks are in place. The third is Field Service Analytics, which enables service managers to integrate all of their data into a single application with a complete view of their mobile workforce. Einstein Vision for Field Service is currently in pilot with expected general availability in the first half of 2018; the other two features are generally available today.
“A year ago we really identified an incredible opportunity for us and our customers, and that was in the area of field service. There’s a large number of customers that take advantage of connected solutions, but the field service solutions that we saw that were out there really tended to not operate in a really connected environment, even though customers are working in a more connected world,” says Mark Bloom, senior director of strategy and operations at Salesforce Service Cloud. “We saw organizations that were relying very heavily on manual processes to really drive their field service solutions. Hundreds or even thousands of technicians that were being managed by spreadsheets and whiteboards and a lot of manually printed documents to help drive their activity.”
With the release last year of Field Service Lightning, the company took the first step to “bring these organizations into the modern connected world, providing a solution that connected those field resources with their customers and with the organizations that were supporting them in the field,” Bloom says. But even as that solution worked to get the “right resource to the right location to work with customers to really ramp up the customer experience,” the challenges of maximizing efficiency and productivity remained, he says.
“There’s challenges that they face such as identifying specific parts or components among potentially hundreds or thousands that they may need to work with, ensuring that they have the right tools and parts and inventory on hand to take care of the customers that they are there to serve,” Bloom says. “And then finally that the organizations themselves that are delivering these services have the right insights so that they can manage their day-to-day work and looking forward to the future to make sure that they can adjust their strategies accordingly.”
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