Algorithms, algorithms, algorithms. Everywhere we turn people seem to be talking about algorithms. This algorithmization can be seen not least in the context of artificial intelligence. But do you actually know what an algorithm is? And how they can help you to achieve better business deals? The easiest way to describe this concept in broad terms is: an instruction for how something is to be done.
When you bake a cake and follow a recipe you are working from an algorithm. When you choose a route and mode of transportation to get to work and repeat it every day, that is an algorithm. In both cases, you systematically follow various steps to reach a destination. An algorithm is a methodical set of steps that can be used for performing calculations, solving problems, and making decisions.
Algorithms are used all the time in mathematics and data processing. The algorithm for calculating the average of two numbers is to add the two numbers together and divide by two. A slightly more complicated example is a cooking recipe. An algorithm for making pancakes could be:
- combine and whip the eggs and half of the milk;
- add the flour and blend until lump free;
- blend in the rest of the milk and the salt;
- melt the butter and stir into the batter;
- heat the griddle;
- pour a thin layer of the batter onto the griddle. A recipe can’t make the pancakes, but a person can read the recipe and follow the steps, and in this way become more effective.
Algorithms are a prerequisite to automation. In 2018 the company Moley Robotics launched an entirely automated cooking robot – a robot kitchen that has unlimited access to chefs and their recipes from the entire world. This robot chef will not only be able to make pancakes for you, but hundreds of other meals – and then clean up after itself.
Alongside the rapid development of ever more powerful computers with huge calculating capacities, algorithms have also become significantly more advanced. Today we use algorithms constantly, often without being aware of it. For example, Google has algorithms to determine the order that search results are displayed. At Amazon you receive product suggestions based on algorithms. Algorithms are practically everywhere, especially for online services and not least in purchasing and sales processes.
Every creature is a living instruction that runs the algorithm of nature. | Joey Lawsin, researcher, writer and heuristic philosopher
Stock trading is an area that was early to introduce technical algorithms that decide when to buy and sell stocks. Today, purchasing via algorithms is normal all over the world Computers are taking over areas from stock brokers and algorithms in trading (also referred to as robotic trade) can be called the finance industry’s answer to the digital revolution. According to a report from Thomson Reuters, 75 percent of all stock trades worldwide are steered by algorithms, and that figure is rising steadily.1 The big advantage of algorithms is that they do the work much faster than humans. According to Professor Steinar Thorvaldsen, the Swiss stock exchange offers an average response time of 34 microseconds, that is 34 millionths of a second.2
A purchasing process can be carried out in the same way as with the examples above, where mathematical calculations, a recipe or robotics in e-commerce follow a number of algorithmic steps. For example, an analysis of the customer’s needs that leads to a recommendation or a product suggestion often follows a number of methodical steps and is built, thereby, on an algorithm. An algorithm can also be used to calculate the probability of a customer making a purchase from us, based on the data that the algorithm collects. Take a simple example. You walk into a sporting goods store to choose a pair of running shoes. The shop’s sales rep can then ask a number of pre-defined questions. What size do you wear? How much do you weigh? How often and how far do you run? What type of surface do you run on? And do you have any medical considerations? The shop’s sales rep may let the customer take a test to evaluate their stride. Based on this information, the sales rep can recommend which shoes will fit the customer best.
With this algorithmic procedure, it doesn’t matter who takes on the role of sales rep. With a little training and education, pretty much anyone can perform this analysis, which means that it either can simplify the sales rep’s work (the customer is asked to answer questions in advance) or completely automate it via, for example, e-commerce. As long as the algorithm is followed, the chances are good that the customer will buy a pair of shoes that meets their needs.
Understanding the opportunities for algorithms to calculate, solve problems, and help us make better decisions opens up enormous possibilities, not least in interactions with customers. With algorithms, we can find patterns in large quantities of customer data and draw valuable conclusions. If we add to that machine learning (which we write about in the next chapter), algorithms can begin to teach themselves about customers’ problems, needs and histories, and thereby become even better advisors. There are great opportunities here for those who choose to be on the cutting edge.
1 McGrath, J. (2016, 26 July). The rise of AI and algorithms in the financial services sector. [blog post]. Downloaded 2018-10-22 from: https://www.raconteur.net/technology/the-rise-of-ai-and-algorithms-in-the-financial-services-sector
2 Stenberg-Gustafsson, N. (2015, 21 November). Algoritmer styr din vardag. YLE. Available: https://svenska.yle.fi/artikel/2015/11/21/algoritmer-styr-din-vardag