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With the advent of process automation and machine learning (ML) technologies, companies are increasingly faced with new data and information, as well as increasing pressure to use new tools that they may not know how to fully utilize.
In fact, in Deloitte’s State of AI in the Enterprise survey, 39% of respondents identified data issues as one of the top three challenges they face in AI initiatives. It’s like finding a needle in a haystack with a metal detector that’s too complicated to use – a waste of time and resources and a false sense of competition.
But how will industry innovators, such as field service organizations (FSOs), which typically send technicians to remote locations to install, repair or maintain equipment, rise to meet the challenges of an increasingly automated world? The answer lies in organizational changes to replace legacy technologies, break down data silos, and fully utilize artificial intelligence (AI) to its full potential.
Replace old technologies
FSOs have traditionally focused on optimizing efficiency and service quality through process improvements and management software updates. However, traditional methods are no longer sufficient to demonstrate business value to your customers.
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As companies begin to focus on delivering outcome-based service models, they must prepare to roll out services such as predictive maintenance so they don’t risk reverting to a fail/fix model where they are constantly upgrading legacy systems. However, evolving to an outcome-based model involves a level of digital transformation that presents several challenges. This can create an overly complex IT environment, containing multiple applications and systems with different update and release tracks or security features, often resulting in high IT maintenance costs and potential business disruptions.
Additionally, replacing an old system with one that cannot use data optimally while simultaneously promising AI compatibility can lead to project delays and additional costs.
Address the shortcomings of data-driven technology and artificial intelligence
Optimizing the productivity of a company’s workforce and providing a great customer experience in today’s on-demand world is challenging. To deliver greater business value to customers, FSOs must use data and intelligence to meet and anticipate customer needs. However, this type of innovation requires breaking down data silos and aligning processes across the organization to deliver customer insights to employees.
Additionally, with AI-embedded software, organizations have the ability to automate repetitive tasks, process complex data sets, and more. However, with 80% of companies already using some form of automation technology or planning to do so in the next year, starting the process of delivering the value AI promises without a third party guiding them through the best It can be difficult for them. Artificial intelligence and data solutions
Maximize data and AI investment
Using a combination of data and artificial intelligence has many benefits, especially for organizations such as FSOs that work to provide the best customer service by ensuring optimal scheduling of employees who are able to meet anticipated service tasks.
In cases like this, data and artificial intelligence go hand in hand. For example, data collected from IoT sensors can help AI predict asset performance and optimize scheduling using data such as maintenance history. Typically, empirical data also helps FSOs proactively respond to potential service issues by predicting when a customer’s product will need maintenance, thereby ensuring that parts and technicians are available in a timely manner. They are available at certain times.
AI also helps internal staff by automating customer interactions through improved chatbot and customer relationship management (CRM) tools.
As we move into a more modern and automated future, organizations need to understand their data silos to experience the full potential of AI. When data is effectively leveraged with AI, organizations can solve a wide variety of problems, paving the way for organizations to use predictive planning while meeting customer needs.
Kevin Miller is the Chief Technology Officer IFS.
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