Fact number one: “innovation” has become one of the most over-used words in the business lexicon. We all feel compelled to do it and if we aren’t doing it then we should at least pretend. I suppose you could say that innovation it is a bit like sex: when all is said and done, more is often said than done. So if you are in the camp of denial and are secretly looking for some innovation Viagra, then read on…
Fact number two: logistics is a mature industry where innovation might not be given a comfortable seat. Of course, all of our customers will demand that we innovate and there will be no end of consultants and coaches who claim to have the gift of the alchemist when it comes to innovation. Yet those breakthrough ideas often remain as elusive as ever.
Fact number three: despite all of the above, we can and should keep innovating if we want to grow our businesses. So here is an idea that might help if you are struggling to know where to start to generate that spark of innovation.
Every few years heralds the start of a new theme in our world. At first glance, the new theme might not seem relevant to your sector. But can that really be true? After all – if it truly is a new and fundamental theme, then surely it will hit your space eventually?
Thinking like this can be a great way to provoke innovation. Let me give a specific example. A few months ago we posed this question: “What does Big Data mean to ByBox”? On the face of it, you could think: “absolutely nothing”. ByBox is a specialist logistics company managing supply chains for companies in the field service sector. Big Data is all about aggregating and analysing massive and unstructured data sources to glean insight that can be put to some commercial use. Poles apart – surely? Maybe. But if you force yourself to find a connection then interesting things can happen.
Many of our customers are responsible for fixing broken machines. Machines like ATMs, medical devices and self-service ticket machines in train stations. I live just outside Oxford and use the train a lot. Sometimes, when I buy a ticket from the train station one of the eight ticket machines is broken. How will it be fixed? Depending on when the machine broke, the fix might demand a sameday delivery of the replacement part to the station.
Delivering anything to the middle of Oxford is tough – but if it is in the middle of a busy Saturday leading up to Christmas then it is particularly challenging. And let’s not ignore one of the other global themes: traffic and pollution. So we have to expect that it won’t be too long before hammering through any high street in a sameday vehicle to drop something off at a train station will result in a hefty surcharge – and our customers certainly won’t want that. So you can already see the halo of innovation starting to glow over this problem.
As always, the interesting question is: “Why”? Why did the ticket machine break – and what could we have done to predict it happening with a worthwhile degree of certainty? This is where the link to Big Data becomes more interesting. Is there a correlation between the machine breaking and other external factors that could have helped us predict the failure? An obvious example would be weather. Do the ticket machines fail when the weather is extreme? If so, we should be mining weather data sources to predict the failure (whilst feeding the fundamental fault back to the manufacturer). But what else? Is there a correlation between high usage of the ticket machine and subsequent failure? If so – how can we get ahead of this high usage? Maybe by mining data sources around events that are due to happen in places on a direct train line from Oxford? Or when planes land at Heathrow during the holiday season – resulting in higher levels of tourists coming to see the Dreaming Spires. And so on.
If we can identify these correlations and design ways of accessing Big Data to predict them, then we can start to think of ways of dynamically positioning the replacement parts close to the station outside of peak times (such as in the middle of the night to a nearby locker). No more sameday deliveries during the day. No more premium surcharges. No more stressed supply chains.
Realistically, the first iteration of any new innovation rarely works. But you have to go through those early iterations in order to find the killer idea that suddenly sets your business on a new adventure – and delights your customers along the way.
Of course, Big Data is just one example of a major theme that could be used to trigger innovation in any sector – including logistics. Forcing your business to find the connection to these themes can be a liberating way to spark innovation and – in due course – some very sexy solutions.
Stuart Miller, CEO and Co-founder of ByBox
