The crystal data ball of Sashiko and her colleagues

When an aircraft needs maintenance, it is grounded. Ideally, this shouldn't take too long: our planes are made for flying. That's why we do everything possible to carry out maintenance as efficiently as possible, including using the help of big data. That's where analytics translator Sashiko comes in: she helped develop a data model that can predict with relative accuracy when parts need to be replaced, and therefore when a new part should be available. As a result, purchases are made only when necessary, saving a lot of money and space in the stockroom.

Data-driven stock management

'Previously, we could do a reasonable job of predicting when certain parts would be needed,' begins Sashiko, analytics translator in the Big Data team at Engineering & Maintenance (E&M). 'But in doing so, we mainly relied on estimates, our own experiences and manufacturers' promises. Thanks to the rise of big data, this can be done much smarter and more realistically. We track exactly how long parts last: not only how much time, but also how many flights, flight metres or times they can be used - think of a coffee machine that makes an average of 10,000 cups. Moreover, we also take climatic factors into account: an aircraft engine runs less smoothly if it is frequently in sandy or icy environments.'

Impact on the floor

Sashiko knows exactly what an innovation like the predictive supply chain (PSC) means for her colleagues. 'As an analytics translator, I stand between the business and the developers. I speak to the supply chain specialists regularly and they tell me what they need, which I translate - together with the product owner - into technical requirements. When the solution is developed, I present it to colleagues on the floor and make sure they can work with it, for instance by organising workshops.'

'Most colleagues are really happy with the smarter way of working,' Sashiko continues. But it doesn't always go smoothly: sometimes people work against change a bit, in most cases unconsciously. 'I don't find that strange at all. Many people within E&M have been working there for years and have been doing the same thing for a long time. It takes some getting used to when these colleagues have to change the way they work. But in the end, a solution only works if everyone works with it. I like the challenge of getting teams on board and letting them experience how it makes their work easier. That's why we work a lot with key users: representative colleagues who test our solutions extensively.'

Endless data possibilities

So the solution by Sashiko and her colleagues helps get a grip on parts inventory. But both the tool and the data behind it can offer so much more. Sashiko lists: 'Keeping maintenance manuals updated and up to date, for example, or preventing parts from travelling too many kilometres between our Schiphol location and outstations. Improvements in predicting when our Component Shops will get busy, understanding the effects of climatic conditions on different components, determining when we can submit claims to manufacturers because manufacturers' warranties prove structurally unrealistic. Long story short: there is still a lot of work ahead of us!'