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From pop up stores to smart chillers: How Frucor builds an innovation pipeline

Divina Paredes | June 30, 2016
Object lessons from Frucor on engaging the whole enterprise in the shift to become a digital business.

For example, if there are a thousand Facebook, Instagram and Twitter information posts about your company and your product, and you are looking for a sentiment about your company.

"You can keep on reading until you get to an idea that everybody hates you or everybody loves you. The sentiment engines can get the sentiment analysis done and you can monitor it every day.''

The next level is to manage the sentiment, like working on the issue, or talking to the parties involved, he says. "A negative sentiment that is unmanaged will mushroom to bigger one.

"But if you have started to see the sentiment when only three people were talking about it, you can pinpoint the three followers and resolve the issue. You can reply and collaborate with them and say, here is the reason why it happened. Or you can say you made a mistake. You can control the sentiment right there."

He says in print media, the swelling of sentiment can happen, but will take a bit longer. "In the digital space, in social media, it gets blown up quickly."

He says big data is also important in other parts of the organisation. For instance, in every factory and logistics operations, you can tap the data from every step of the operations and see how effective they are.

"You can start seeing things you have not seen. You can get the 'sentiment' on what you are doing internally, as much as what is happening to your customers."

Reducing the digital divide

Companies that have missed the boat "a little bit" on digitalisation on the leading edge can exploit the next big event, which he says is around Internet of Things.

"Imagine if devices start talking to each other," he says. "Then data and algorithms start to do things for you or find out things for you. Like worms travelling between devices between machines between the Internet of Things, finding things for you.''

For example, if you want to buy a shirt, you can walk on Queen Street and the . algorithm is going to find where to take you to the right shop.

''Right now I can google the shops. Or I can say, find me the right shirt and have it delivered to me.''

"As the engines and data management become really smart and become faster and faster, AI becomes stronger and stronger for me. That AI algorithm will be my virtual agent and I can say, find me the right shirt, for my stocky size and height in the colours it knows I like, without asking it."

It might then be talking to the tag on the t-shirt in one of the stores and searching if there is a shirt your size on the rack or to try a particular size, like a search engine would.


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