The News: Salesforce announced several capabilities designed to help field service organizations more efficiently and proactively manage and maintain the lifecycle of their physical assets. The new capabilities offer access to real-time data and intelligence about their assets, as well as access to AI models that accurately predict potential failures, thereby helping organizations reduce unplanned downtime, extend the lifespan of their assets, and identify additional recurring revenue opportunities such as upsells and cross-sells.
You can read the press release detailing the news at Salesforce’s website.
Salesforce Announces Asset Management Tools Powered by Analytics AI
Analyst Take: Salesforce announced several new field service asset management capabilities designed to help organizations more efficiently and proactively manage physical assets throughout their lifecycle, incorporating real-time operational data and intelligence, as well as AI models that can predict potential failures. The features are designed to help organizations reduce unplanned downtime, extend the lifespan of their assets, and identify additional recurring cross-sell and upsell revenue opportunities.
Salesforce announced the following new capabilities:
Asset Health Score: This capability integrates real-time data from any source, including an organization’s enterprise resource planning (ERP), enterprise asset management (EAM), or other legacy system through Salesforce Data Cloud to calculate an asset’s overall health and performance based on factors such as age, usage, telemetry (e.g. temperature, speed), and repair history. Field technicians then have full visibility to this data through the mobile app, which can help them diagnose and repair the asset in the field with the most recent and trusted data available. Asset Health Score will be generally available with Einstein 1 Field Service Edition this summer, and Asset Health Score for mobile workers will be generally available this winter.
Asset Service Lifecycle Management: This enhancement combines pre-configured data kits for Data Cloud with a suite of specialized features designed for asset-intensive industries, usually in manufacturing, industrial, telecommunications, automotive, utilities, or other physical device-intensive verticals. These kits allow customers to oversee the entire asset service lifecycle to provide a unified view of all active service entitlements for each asset. This enables users to create and send work order-based quotes to customers on-site and centrally manage all service campaigns such as recalls or upgrades. Asset Service Lifecycle Management will be generally available this summer as a separate add-on.
Connected Assets: Generally available later this summer as a separate add-on, Connected Assets is designed to help organizations easily integrate asset data with customer information to surface calculated insights and orchestrate actions in response to real-time, bi-directional telematics events.
For example, when the Asset Health Score hits a certain threshold, it can trigger a self-healing event like updating the firmware based on the error code to proactively resolve the issue. If the firmware update did not resolve the issue, then a work order can be automatically created, and the asset can be added to an upsell campaign to drive additional revenue based on its usage and age. Operator safety can also be improved by providing immediate notifications of potential safety concerns.
New Salesforce AI Models: New training models are designed to identify common issues based on current asset data and service history of similar assets and predict the time of and reason for an asset failure, without additional training or tuning, which will be used to power Salesforce’s Asset Service prediction, scheduled for open beta in the winter.
Field Service Intelligence: This capability provides field service organizations with out-of-the-box dashboards for work orders, service appointments, and asset-related KPIs, including asset availability, reliability, and downtime. Field Service Intelligence will be generally available with Einstein 1 Field Service Edition this summer. Plus, since Data Cloud works with any third-party system, companies can make decisions based on a comprehensive and accurate representation of any business data that is available within Data Cloud, providing them with a more complete view of their operations.
Asset Status Data: With the Field Service Mobile App and remote access to Asset Health Scores and Einstein Pre-Work Briefs, technicians can now quickly understand key details of their work order including asset status and service history. With full visibility into what’s wrong with an asset, technicians can expedite triage and decide on a fix – resulting in faster job completion and higher first-time fix rates. Additionally, technicians will be able to see other assets with a low health status while onsite and proactively service those to prevent a future truck roll and reduce the chance of downtime.
Driving Organizational Efficiency and Revenue Sans Generative AI
While generative AI has garnered the lion’s share of attention over the past year, machine learning-based predictive and analytics-based AI remain a key driver of efficiency and productivity for many industries and use cases. Given the plethora of data generated by and captured from physical devices, it makes sense to incorporate this critical data into Data Cloud, and then make it available to field service technicians and asset managers to better monitor and manage their physical assets.
Salesforce has realized that the more data it can ingest from external sources, the more opportunities it will have to extend its reach into an organization. This land-and-expand strategy is key for Salesforce to continue to grow recurring revenue, particularly in an environment where vendor stickiness is often driven by the amount of application real estate consumed within an organization. Furthermore, Salesforce needs to continue to implement new features to ensure they can continue to compete against more vertically focused providers such as ServiceTitan, which have established a strong foothold in the market.
Salesforce is also smart to focus on the needs of field service workers, which increasingly are expecting to have access to a wide range of data, from the basic telemetry and service data that these enhancements are providing, to more advanced or information-rich information (such as service manuals or how-to guides), which we expect will be delivered via augmented-reality (AR) applications in the future. By establishing a strong field-service platform now, Salesforce will be well positioned to partner with and serve as the platform for delivery of advanced applications, such as AR or other enhanced technologies in the future.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Image Credit: Salesforce
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
