We think of ourselves as individuals but in fact what we do can be predicted. Every time we text, use our credit cards and shop data is created that allows our movements and plans to be tracked.
Temperature can change how we act and how we eat. When it is colder we eat more. We also want to eat and drink hotter food and drink when the temperature drops. Porridge sells millions more when the weather is cold. Demand planners are people who have to predict what we will buy all year round. They have to know how much advent calendars will sell at Christmas so that they have enough for everyone but are not left with lots of stock. Demand planners also have to be able to work out where the most advent calendars will sell so that they have the correct amount of stock in each shop. However, demand planners do not need to be able to work out what we will buy at special times of the year, they need to do this all year round. Demand planners need to constantly predict how much stock each shop with sell all year round. To do this they need to analysis previous stock sold, the temperature outside, the area of the country and the time of year. If we eat more or crave more hot foods when the temperature drops then that means that demand planners need to be able to predict when this is going to happen. During “Human Swarm” on Channel 4 they talk about how weather affects what we buy. Ross Eggleton who works at the biggest warehouse in the UK tells us that “we basically capture every single transaction that every individual makes in every single store every moment of every day. And if you overlay that then with what the weather conditions were outside at the time they made the purchase,
it obviously gives you a lot of information and data that you can then use to build a picture of what those patterns are going to be the next time.” This shows how the food that we buy correlates with the weather outside and shows how demand planners then use this information. Eggleton also says that the hardest time to predict what we are going to buy is when there is a sudden change in the weather. On a low temperature weekend 246% more pies were bought than on a normal weekend. This shows how important demand planners job is. If they were not able to predict this, then the supermarkets would run out of these popular items like soup and pies that we like to eat when it is cold. This is a perfect example of how important mathematics is. Without being able to collect all of this data, demand planning would not be able to happen. This is another example of how math is used in the real world and it shows how important it really is.
Business simulation
During this input Richard came up with a way for us to have a go at demand planning. He gave us a selection of product that we could buy and a budget to start with. in groups we got to decide what to buy, how much of each thing to buy and how much we were going to spend. Richard then told us what percentage of stock we had sold, what we could carry over (non-perishable items) and is any stock was discontinued. I found this simulation lots of fun but the buying the items was pretty stressful incase you picked the wrong items. Finding out how much of the stock was sold was also nerve wracking as you might have picked the wrong items then they went off. We did this over a full year so that we got a different idea of the seasons. At the end, my group actually did pretty well and we had the third highest amount at the end out of everyone.
Below are my groups sheets from the simulation.
I think this is a fun thing that you could do with children in a classroom. Using a more simple version of this would be a great example for children how maths can be used in this industry in the real world. It would also give children an insight into food ordering and supermarkets would could be useful for their future.
References
BBC (2002) Autumn’s Supermarket Secrets. Available at: https://learningonscreen.ac.uk/ondemand/index.php/clip/27113 (Accessed: 21 November 2016).
Doherty, J. (2013) Human Swarm. Available at: https://learningonscreen.ac.uk/ondemand/index.php/prog/037BDBED?bcast=97003675# (Accessed: 21 November 2016).
