The sources of data that businesses can collect have grown dramatically, from sensors in machines on the factory floor to social media streams. Algorithms make great use of the resulting data, but companies must clean and organize the data for it to be valuable.
To be effective, an algorithm has to include the right mix of mathematics and assumptions about the world. Adjust algorithms over time by weeding out incorrect assumptions and accounting for real-world situations and changing conditions.
People who use the results of an analytical process need to know what to do with them. That’s as true for a veteran company executive as it is for a frontline worker or a person with a PhD in mathematics.
Success with algorithms starts with a strategic commitment at the C level, but getting lower-level buy-in means rewarding performance tied to using analytics to benefit the business.
To avoid angering customers, companies must comply with privacy rules and honor usage agreements. In addition, when companies create a new algorithm-based product or service, they must weigh its value against the risk of exposing the algorithm to competitors.