How to leverage data and technology in an increasingly automated world

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With the advent of process automation and machine learning (ML) technologies, companies are increasingly exposed to new data and information, as well as increasing pressure to adopt new tools that they may not know how to take full advantage of.

In fact, in Deloitte’s enterprise AI study, 39% of respondents cited data issues as one of the top three challenges facing 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 competitiveness.

But how can industry innovators like field service organizations (FSOs), which typically send technicians to remote locations to install, repair or maintain equipment, meet the challenges of an increasingly automated world? The answer lies in organizational changes to replace legacy technologies, break up data silos, and fully exploit the potential of artificial intelligence (AI).

Replace old technologies

FSOs have traditionally focused on optimizing service efficiency and quality by improving processes and updating management software. However, traditional methods are no longer sufficient to demonstrate business value to your customers.

As companies move towards performance-based service models, they need to be prepared to start offering services like predictive maintenance so they don’t risk reverting to a break/fix model as they continually upgrade legacy systems. However, the evolution to a results-based model involves a level of digital transformation that presents several challenges. This can create an overly complex IT environment that includes many applications and systems with different update and release frequencies or security features, often resulting in high IT maintenance costs and potential business disruption.

In addition, replacing an old system with one that cannot make optimal use of data while promising AI compatibility can delay the project and add additional costs.

Address the gaps in data and AI-enabled technologies

Optimizing the productivity of a company’s workforce and delivering a great customer experience is challenging in today’s on-demand world. To offer greater business value to customers, FSOs must use data and information to meet and anticipate customer needs. However, this type of innovation requires disaggregating data silos and coordinating processes across the organization to deliver customer insights to employees.

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Additionally, using artificial intelligence software, organizations have the ability to automate repetitive tasks, process complex data sets, and more. However, while 80% of companies already use some form of automation technology or plan to do so in the coming years, they may struggle to begin the process of delivering value on the promise of AI without a third-party leveraging the best tools. AI and data solutions.

Maximize data and AI investments

The use of a combination of data and artificial intelligence has many benefits, especially for organizations like FSOs that aim to provide the best customer service by ensuring optimized workforce scheduling that can respond to expected service tasks.

In these cases, data and artificial intelligence work together; For example, data collected from IoT sensors can help AI predict asset performance and optimize scheduling using data such as maintenance history. Typically, experiential data also helps FSOs proactively respond to potential service issues by predicting when a customer’s product will need service, ensuring that parts and technicians are available at the right time.

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AI also helps internal employees by automating interactions with customers by improving chatbot and customer relationship management (CRM) tools.

As we move towards a more modern, automated future, organizations will need to understand their data hoards in order to experience the full potential of AI. When data is effectively used in conjunction with AI, organizations can solve a variety of problems end-to-end, enabling organizations to leverage predictive planning and meet customer needs.

Kevin Miller is CTO IFS.


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