How to leverage data and technology in an increasingly automated world

View all on-demand sessions from the Smart Security Summit here.

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

In fact, 39 percent of respondents to Deloitte’s State of AI in Enterprise survey cited data concerns as one of the top three challenges they face in their AI initiatives. It’s like looking for a needle in a haystack, with metal detectors too complicated to use – a waste of time and resources, and a false sense of competitiveness.

But how do industry innovators, such as 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 change to replace legacy technologies, break down data silos, and harness the full potential of artificial intelligence (AI).

replace legacy technology

FSOs have traditionally focused on optimizing service efficiency and quality through process improvement and managing software updates. However, traditional methods are no longer sufficient to demonstrate business value to customers.


Smart Security Summit On Demand

Learn about the critical role of AI and ML in cybersecurity and industry-specific case studies. Watch the on-demand session today.

look at the lord

As companies start to focus on delivering outcomes-based service models, they need to be prepared to roll out services like predictive maintenance so they don’t risk going back to a break/fix model of constantly upgrading legacy systems. However, the evolution to an outcomes-based model involves a degree of digital transformation, which presents some challenges. It can create an overly complex IT environment consisting of numerous applications and systems with varying update and release cadences or security features, often resulting in high IT maintenance costs and possible business disruption.

Additionally, replacing a legacy system with one that doesn’t make optimal use of data while promising AI compatibility can cause project delays and additional costs.

Addressing Data and AI-Enabled Technology Shortfalls

In today’s on-demand world, optimizing the productivity of your company’s workforce and delivering a great customer experience is challenging. To deliver greater business value to customers, FSOs need to leverage data and intelligence to meet and anticipate customer needs. However, this type of innovation requires breaking down data silos and coordinating processes across the organization in order to provide employees with customer insights.

Additionally, with AI-embedded software, organizations are able to automate repetitive tasks, process complex data sets, and more. However, while 80% of companies are already using some form of automation technology or plan to do so within the next year, without a third party to guide them through the optimal process, it may be difficult for them to begin the process of delivering the value AI promises AI and data solutions.

Maximize Data and AI Investments

There are many benefits to using data and AI together, especially for an organization like FSO that strives to best serve its customers by ensuring optimal scheduling of staff who can respond to predictive service tasks.

In this case, data and AI work hand in hand; for example, data collected from IoT sensors can help AI predict asset performance and plan optimization by using data such as maintenance history. Often, empirical data also helps FSOs to proactively respond to potential service issues by predicting when a customer’s product will require maintenance, ensuring parts and technicians are available at a given time.

AI is also helping internal employees by enhancing chatbots and customer relationship management (CRM) tools to automate customer interactions.

As we move toward a more modern, automated future, organizations will need to master their data silos to experience the full potential of artificial intelligence. When data is used effectively with AI, organizations can solve problems end-to-end, paving the way for organizations to leverage predictive scheduling while meeting customer needs.

Kevin Miller is Chief Technology Officer or international Finance Center.

data decision maker

Welcome to the VentureBeat Community!

DataDecisionMakers is where experts, including technologists who work with data, can share data-related insights and innovations.

If you want to learn about cutting edge thinking and the latest information, best practices and the future of data and data technology, join us at DataDecisionMakers.

You might even consider publishing an article of your own!

Read more from DataDecisionMakers

Source link