The story of one paperboy’s intelligent business

The main character of our story is a paperboy. Every morning, he is confronted with the same problem: “How many newspapers should I buy at the corner stand?” The paperboy would like to maximize his profit for the day. If he buys too many papers, at the end of the day, he might be left with worthless excess stock, bringing down his profit. Nothing is older than yesterday’s newspaper. Then again, if he doesn't buy enough papers, he runs the risk of missed sales opportunities and dissatisfied customers. That’s not good for business either. There’s nothing worse than having to pass up on business opportunities because of a lack of resources. What makes the paperboy’s problem so tough is the variation in demand. For example, if the issue includes a big item of news, the paper will sell much better than it does with just the usual news.

Frustrated, the paperboy decides to ask the clever girl next door. She takes a logical approach to the problem and tries to understand what his options are: “What are the variables that affect the demand for newspapers? Which of these variables can you yourself influence?” She concludes that while it’s pretty hard for a paperboy to influence the news, he can choose his sales territory, the time he spends selling papers and how much effort he devotes to marketing. She produces a list of variables, associated dependencies and incoming cost factors, forming the basis for a mathematical model. Based on a standardized reference model, these are combined to create a mathematical framework that produces an optimal recommendation for how many papers to buy up every morning. This recommendation is geared towards the paperboy’s goals and adapted according to the basic conditions as they change from day to day.

Intelligent services geared towards a specific value-creating benefit help you make decisions when it comes to complex tasks.

Just like the paperboy’s clever young neighbor, COSMO CONSULT is an experienced consultant. With our team of experts in data science, we take proven mathematical decision-making procedures and adapt them to meet our customers’ needs. Working closely with our customers, we start with standardized intelligent services that can be integrated into existing systems using premade interfaces and then customize them for specific tasks. Just like in our story about the paperboy, the first step is to jointly determine the key data and influenceable variables at the outset. In order to create mathematical models that can be used to help support and streamline decision-making, you need a solid database.