Regular readers will now be familiar with my recent musings about why and how Sports should embrace and engage with Analytics. While sports are an inspiration already, I’ve been struck by the parallels in objectives, challenges and outcomes with various manufacturing processes. Lately we have been thinking about the impact of IoT on demand planning, which has led to this review.
Focus on what really matters
It sounds obvious to say this, but many organizations are not clear about what really matters. They could learn a lot from sports teams. The UK Rowing team, for example, took as their mantra ‘Will it make the boat go faster?’. Before anything was changed, it needed to give a positive answer to this question. If the answer was no, then they didn’t make the change.
In the same way, every IoT and analytics deployment should improve the way the organization works. In this case, it means it should improve demand planning, reducing over- and under-ordering. That’s all that matters.
Believe in your data
Especially when first introducing a new system, it can be tempting to default back to your previous position or rely on gut feeling. This is, of course, especially true if the data is telling you something that you don’t really want to hear. The problem with that is that if something goes wrong, you no longer have a solid base of evidence to back up your decision. Decisions, and indeed, strategy, backed up by analytics means that you have a base that you can rely on. Emotions are therefore less likely to drive decisions, which is especially important if the changes that you have made do not at first seem to be paying off. Change can be a long process.
You have to be able to respond quickly to what the data are telling you
Sports teams often have pretty obvious deadlines: Olympic Games, world championships, and the like. But in between, they have plenty of smaller events at which to test themselves, and particularly to measure their progress against their competitors. They know that it is no good waiting until you have failed to win a medal at the Olympics before changing your tactics.
Whenever you spot something in the data that could make a difference, you need to act on it straightaway. And you need to be able to see the data quickly too: real time is best, but ‘quite quickly’ is better than ‘not for several months.
Small changes can add up to big effects
British Cycling is arguably the most successful team in history, certainly in terms of Olympic gold medals. The man behind the team, David Brailsford, has also made history by establishing a new cycling team, Team Sky, that has produced a British winner of the Tour de France not once, but several times. How have these successes been achieved? By a strategy of ‘incremental improvements’.
In other words, a recognition that it is not only big changes that matter, and that focusing on one area alone will not be enough. Many small changes made right across the board, and over a period of time, add up. In demand planning, this might mean not solely focusing on demand, but also using data about supply as well, if that offers you a helpful insight. Whether it is fractions of seconds round a cycling track, or a reduction of three items in your stockpile of inventory, it all helps.
Customers (or fans) really matter and should make a difference to the way that you operate
Sports teams, especially commercial ones, rely almost totally on their fans. They need fans to turn up to games or meets, because they need the gate receipts to pay their players. Engaging fans is therefore essential for survival. Analytics is allowing sports teams to understand fan behavior and preferences, and provide personalized communications that improve engagement, and make continued attendance more likely.
Demand planning matters for customers too, and is affected by their behavior. Get it wrong, and the product that your customers want will not be available. Use analytics to forecast customer behavior effectively, and the product will be there when your customers want it.
Look in odd places
Sports and demand planning may not seem obvious bed-fellows. This article shows that there are important lessons that demand planners can take from the way that sports teams have used analytics. But perhaps the most important lesson may be that sometimes you may find help in the least obvious places.
Also, take a look at the e-book Internet of Things: Visualise the Impact to explore how European early adopters are facing the IoT challenges.
Read also Christer's other posts about sports analytics: