Companies are struggling to monetise and utilise big data and artificial intelligence (AI), a roundtable discussion at Aftermarket 2018 concluded.

Author | Copperberg

The benefits of AI and machine learning in providing insights into customer needs and behaviour, as well as its ability to streamline corporate processes was apparent to the delegates at the Berlin talk shop. But many said they were sitting on treasure troves of information they didn’t know how to use.

“I think data is important and means we can do more and measure more, but data is there, it’s available, but the difficult thing is that we don’t know yet how to utilise that data to improve ourselves,” said Ozen Ergezer, head of own retail in Turkey for truckmakers MAN.

Her comments were echoed by Daria Baryshnikova, senior rail project manager at German railway brakes maker Knorr Bremse.

“The data is not the problem, we’ve got gigabytes of data the challenge is to identify what’s interesting and you can’t do that without the customer so we require a lot data to come from them in order to draw any analysis. After all, they don’t want to buy basic data from us, they are willing to pay for data that’s going to help them with they day to day operations and help them reduce their running costs.”

For truck maker Hyster-Yale Group, the challenge comes in convincing its largely traditional customer base of the benefits of the new technology.

“We find that a lot of our customers don’t know what they want – we know there’s a lot of latent need but the customers don’t know what they would like to see,” said TCO project coordinator Jos Verbeek. “We have to pick them very carefully because we don’t want to overload their system with data.”

The fast and free flow of data across companies poses many security risks, and service management companies are finding challenges in guaranteeing safe data use.

“Our customers operate major gas plants, nuclear and chemical plants and cyber security and security of plants is one of their major concerns,” said Nave Orgad, director of lifecycle services in Europe for Emerson Automation Solutions. “Data security is a must, if you don’t have it in place then customers won’t agree to share it with you or give access to it.”

Discussion moderator Gaurav Garg of IBM sought to put delegates’ minds at rest on the matter of AI robbing humans of roles in the workplace. IBM’s Watson system has found wide adoption within the field services industry and the technology company sees that trend expanding.

Garg said the popular perception of AI as artificial intelligence was wrong and that IBM preferred to regard it as “augmented intelligence, that works alongside humans”.

Christian Schaal, area support manager for German medical technology company Brainlab, was less than convinced.

“We are focusing so much on data that in the end we lose sight of the customer,” Schaal said. “We should never forget that we are dealing with humans.”

There was wide agreement that AI had the potential to be good for the aftermarket sector, but it needed to be directed. Chief among the areas in which it should be focused was simplification of business processes, said Luca Menardi, EMEA market intelligence specialist at Dutch capital goods company CNH Industrial.

“Simplicity should be a given,” he said. “Every time that we don’t fulfil that we lose, this should be starting point.”

The most optimistic tone was struck by Thomas Leistiko, sales vice president of Danish defence and aerospace equipment manufacturer Terma. He said he believed that while the benefits of crunching big data may not be immediately apparent, they would be in the near future.

“Data, AI etc will transform our organisations,” he said. “The sales guys will become part of the product team and remove some of the old boundaries and change the way companies work and the roles that we have.

“It will make us more efficient and able to hit the right market with the right product at the right time,” he added “Right now the opportunities seem daunting but in five years or 10 years time it will be perfectly normal.”

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